{ "lo_X_y3xQ4pc4": { "external_id": "X_y3xQ4pc4", "code": "3", "title": "Best practices for creating reusable data publications", "subtitle": "", "description": "These best practices help you share your research with the scientific community to increase its visibility and foster collaborations by making your datasets as Findable, Accessible, Interoperable, and Reusable (FAIR) as possible.\r\n", "general": { "identifier": "3", "url_type": "URL", "url": "https://datadryad.org/stash/best_practices", "title": "(\"en_US\",\"Best practices for creating reusable data publications\")", "language": [ "en" ], "description": "(\"en_US\",\"These best practices help you share your research with the scientific community to increase its visibility and foster collaborations by making your datasets as Findable, Accessible, Interoperable, and Reusable (FAIR) as possible.\")", "keywords": [ "(\"en_US\",\"data research\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"best practices\")" ], "geographical_availability": [ "(\"en_US\",\"2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "Dryad" ] }, "date": "2019" }, "educational": { "interactivity_type": "Expositive", "access_rights": "Copyright (c) 2019 Dryad", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Free use\")", "learning_resource_type": "Narrative text", "interactivity_level": "Low", "semantic_density": "Low", "target_group": [ "Author" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "PT12M45S" }, "technical": { "size": "Not available", "topic_codes": [ "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "G5: Basic Research Data Management (RDM)", "R1: Access control (Authorization-Authentication-Identification, or AAI) methods", "R8: Licenses & policies for data use", "R13: Provenance tracing" ] } }, "lo_Fz-JVAiWHN": { "external_id": "Fz-JVAiWHN", "code": "4", "title": "Data and the FAIR Principles", "subtitle": "", "description": "This module provides five lessons focused on best practices aimed at ensuring that a researcher’s data is properly managed and published to ensure it enables reproducible research.\r\n", "general": { "identifier": "4", "url_type": "URL", "url": "http://www.repronim.org/module-FAIR-data/", "title": "(\"en_US\",\"Data and the FAIR Principles\")", "language": [ "en" ], "description": "(\"en_US\",\"This module provides five lessons to ensure that a researcher’s data is properly managed and published to ensure it enables reproducible research.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"fair principles\")" ], "geographical_availability": [ "(\"en_US\",\"2016\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ReproNim" ] }, "date": "2016" }, "educational": { "interactivity_type": "Expositive", "access_rights": "Copyright © 2016 Neurohackweek and ReproNim", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"This module provides five lessons to ensure that a researcher’s data is properly managed and published to ensure it enables reproducible research.\")", "learning_resource_type": "Lecture", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "G5: Basic Research Data Management (RDM)", "R9: Linked Data and ontologies", "R16: Workflow engines for automated data processing" ] } }, "lo_79UvbkfXpL": { "external_id": "79UvbkfXpL", "code": "7", "title": "Data FAIRNESS - International Summer School", "subtitle": "", "description": "This module includes the website of the International Summer School for Environmental and Earth Science Infrastructure that has been held in Lecce from 1st to 5th July 2019.\r\n", "general": { "identifier": "7", "url_type": "URI", "url": "https://training.envri.eu/course/view.php?id=43", "title": "(\"en_US\",\"INTERNATIONAL SUMMER SCHOOL Data FAIRness in Environmental and Earth Science Infrastructures: theory and practice\")", "language": [ "en" ], "description": "(\"en_US\",\"In recent years, one of the major challenges in the Environmental and Earth Science has been managing and searching larger volumes of complex data, collected across multiple disciplines. Many different standards, technologies and common practices have been developed to support each phase of the Data Lifecycle (Data Acquisition, Data Curation, Data Publishing, Data Processing and Data (Re)Use. The course will focus on the creation and reuse of FAIR data and services in the Environmental and Earth sciences. It is built as a five-day summer school where leading scientists will address various topics from different perspectives.\")", "keywords": [ "(\"en_US\",\"data fairness\")", "(\"en_US\",\"data\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"learningpath01\")" ], "geographical_availability": [ "(\"en_US\",\"2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "2019-07-01" }, "educational": { "interactivity_type": "Active", "access_rights": "Copyright LifeWatch ERIC 2018", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Copyright LifeWatch ERIC 2018\")", "learning_resource_type": "Lecture", "interactivity_level": "High", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G2: Metrics for FAIRness evaluation", "G3: Performing a FAIRness self-assessment", "R2: API (Application Program Interface) design for data & metadata access", "R3: Cataloguing - design & implementation", "R6: Data Management Plans", "R8: Licenses & policies for data use", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R11: PID allocation & use (including citation support, bibliometry, provenance)", "R12: Portal design & operation", "R13: Provenance tracing", "R16: Workflow engines for automated data processing" ] } }, "lo_34ECV3ZASY": { "external_id": "34ECV3ZASY", "code": "8", "title": "Data Management Expert Guide", "subtitle": "", "description": "This module is a best practices guide designed by European experts to help social science researchers make their research data Findable, Accessible, Interoperable and Reusable (FAIR).\r\n\r\nYou will be guided by different European experts who are - on a daily basis - busy ensuring long-term access to valuable social science datasets, available for discovery and reuse at one of the CESSDA social science data archives.\r\n", "general": { "identifier": "8", "url_type": "URI", "url": "https://www.cessda.eu/Training/Training-Resources/Library/Data-Management-Expert-Guide", "title": "(\"en_US\",\"Data Management Expert Guide\")", "language": [ "en" ], "description": "(\"en_US\",\"This guide is written for social science researchers who are in an early stage of practising research data management. With this guide, CESSDA wants to contribute to professionalism in data management and increase the value of research data.\")", "keywords": [ "(\"en_US\",\"data management\")", "(\"en_US\",\"process\")", "(\"en_US\",\"plan\")", "(\"en_US\",\"archive\")", "(\"en_US\",\"discover\")", "(\"en_US\",\"store\")", "(\"en_US\",\"publish\")" ], "geographical_availability": [ "(\"en_US\",\"2017-2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Publisher", "entity": [ "CESSDA ERIC" ] }, "date": "2017-2019" }, "educational": { "interactivity_type": "Expositive", "access_rights": "CESSDA Training Working Group (2017 - 2019). CESSDA Data Management Expert Guide. ", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "(\"en_US\",\"Creative Commons Attribution-ShareAlike 4.0 International License\")", "learning_resource_type": "Narrative text", "interactivity_level": "Low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "15H" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R3: Cataloguing - design & implementation", "R4: Certification schemes for repositories (CoreTrustSeal)", "R6: Data Management Plans", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)" ] } }, "lo_zA-mUH9ZW2": { "external_id": "zA-mUH9ZW2", "code": "9", "title": "Data Management in Environmental and Earth Science Infrastructures", "subtitle": "", "description": "International Summer School, Lecce, Italy, July 2018\r\n", "general": { "identifier": "9", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=68", "title": "(\"en_US\",\"Data Management in Environmental & Earth Science Infrastructures\")", "language": [ "en" ], "description": "(\"en_US\",\"In recent years, one of the major challenges in the Environmental and Earth Science has been managing and searching larger volumes of complex data, collected across multiple disciplines. Many different standards, technologies and common practices have been developed to support each phase of the Data Lifecycle (Data Acquisition, Data Curation, Data Publishing, Data Processing and Data (Re)Use. The course will focus on the creation and reuse of FAIR data and services in the Environmental and Earth sciences. It is built as a five-day summer school where leading scientists will address various topics from different perspectives.\")", "keywords": [ "(\"en_US\",\"data management\")", "(\"en_US\",\" environmental science\")", "(\"en_US\",\" earth science\")", "(\"en_US\",\"infrastructure\")", "(\"en_US\",\"theory and practice\")" ], "geographical_availability": [ "(\"en_US\",\"2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "2019-07-01" }, "educational": { "interactivity_type": "Active", "access_rights": "Copyright LifeWatch ERIC 2018", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Copyright LifeWatch ERIC 2018\")", "learning_resource_type": "Lecture", "interactivity_level": "Very low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R3: Cataloguing - design & implementation", "R5: Cloud computing (Virtual Machines & containers) for data processing", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R11: PID allocation & use (including citation support, bibliometry, provenance)", "R13: Provenance tracing" ] } }, "lo_TCqi_cueaV": { "external_id": "TCqi_cueaV", "code": "10", "title": "Data Management Planning", "subtitle": "", "description": "Life science projects are becoming more and more data-intensive, with both data volume and complexity increasing. Therefore, life scientists need to construct a proper data management plan (DMP) before they start a research project. This plan should be updated regularly during the research project. This is also rapidly becoming a condition to obtain research funds.This resource includes a set of best practices aimed at ensuring that an effective DMP is created.\r\n", "general": { "identifier": "10", "url_type": "URI", "url": "https://www.dtls.nl/fair-data/research-data-management/data-management-planning/", "title": "(\"en_US\",\"\tData Management Planning\")", "language": [ "en" ], "description": "(\"en_US\",\"Life science projects are becoming more and more data-intensive, with both data volume and complexity increasing. Therefore, life scientists need to construct a proper data management plan (DMP) before they start a research project. This plan should be updated regularly during the research project. This is also rapidly becoming a condition to obtain research funds.\")", "keywords": [ "(\"en_US\",\"\tdata management plan\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"data management\")" ], "geographical_availability": [ "(\"en_US\",\"\t2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "Rob Hooft, DTL Data programme manager, rob.hooft@dtls.nl" ] }, "date": "2020" }, "educational": { "interactivity_type": "Mixed", "access_rights": "© 2020 Dutch Techcentre for Life Sciences. All rights reserved.", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"© 2020 Dutch Techcentre for Life Sciences. All rights reserved.\")", "learning_resource_type": "Lecture", "interactivity_level": "Low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R6: Data Management Plans" ] } }, "lo_SMQ3_q15Du": { "external_id": "SMQ3_q15Du", "code": "11", "title": "Data Management Training (DMT) Clearinghouse", "subtitle": "", "description": "The Data Management Training (DMT) Clearinghouse is a registry for online learning resources and best practices focusing on research data management.  \r\nIt was created in a collaboration between the U.S. Geological Survey's Community for Data Integration, the Earth Sciences Information Partnership (ESIP), and DataONE.\r\n", "general": { "identifier": "11", "url_type": "URI", "url": "http://dmtclearinghouse.esipfed.org", "title": "(\"en_US\",\"\tData Management Training Clearinghouse\")", "language": [ "en" ], "description": "(\"en_US\",\"The DMT Clearinghouse is a registry for online learning resources about research data management. Initial seed funding was provided by the U.S. Geological Survey's Community for Data Integration. Subsequent funding has been granted by an Institute of Museum and Library Services National Leadership Grant (LG-70-18-0092-18). Developed in collaboration with the Earth Sciences Information Partnership (ESIP) Federation, and DataONE, with subsequent support from the University of New Mexico Libraries Research Data Services, the DMT Clearinghouse is available for searching, browsing, and submitting information about learning resources on data management topics. \")", "keywords": [ "(\"en_US\",\"\tdata management training\")", "(\"en_US\",\"data\")", "(\"en_US\",\" data management\")" ], "geographical_availability": [ "(\"en_US\",\"\t2012-2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Publisher", "entity": [ "Clearinghouse" ] }, "date": "2012-2019" }, "educational": { "interactivity_type": "Active", "access_rights": "Copyright © 2016 Federation of Earth Science Information Partners. All rights reserved.", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Copyright © 2016 Federation of Earth Science Information Partners. All rights reserved.\")", "learning_resource_type": "Lecture", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R6: Data Management Plans", "R10: Metadata standards & schemas (including geospatial, instruments, variables)" ] } }, "lo_vgvl5Px_aG": { "external_id": "vgvl5Px_aG", "code": "12", "title": "Data science and reproducibility", "subtitle": "", "description": "Slides on data science and reproducibility issues from lectures and workshops given by Michel Dumontier, professor in Data Science at Maastricht University.\r\n", "general": { "identifier": "12", "url_type": "URI", "url": "https://training.incf.org/course/data-science-and-reproducibility", "title": "(\"en_US\",\"Data science and reproducibility\")", "language": [ "en" ], "description": "(\"en_US\",\"2 lessons: slides on data science and reproducibility issues from lectures given by Michel Dumontier, professor in Data Science at Maastricht University.\")", "keywords": [ "(\"en_US\",\"data science\")", "(\"en_US\",\"scientific reproducibility\")", "(\"en_US\",\"fair principles\")", "(\"en_US\",\" fair metrics\")" ], "geographical_availability": [ "(\"en_US\",\"2017\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "Michel Dumontier, professor in Data Science at Maastricht University" ] }, "date": "2017-01-26" }, "educational": { "interactivity_type": "Expositive", "access_rights": "© Copyright INCF.org 2020. All Rights Reserved.", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"© Copyright INCF.org 2020. All Rights Reserved.\")", "learning_resource_type": "Slide", "interactivity_level": "Very low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "3H" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G3: Performing a FAIRness self-assessment", "G5: Basic Research Data Management (RDM)" ] } }, "lo__MMLRIo983": { "external_id": "_MMLRIo983", "code": "13", "title": "Data Stewardship Wizard", "subtitle": "", "description": "DTL’s Rob Hooft has developed a Data Stewardship Wizard in collaboration with colleagues from the Czech ELIXIR node. The Data Stewardship Wizard converts a lengthy data management questionnaire into an effective flowchart, saving you research time and money, and enhancing the quality of your Data Management Plan. Check the this tutorial to learn ho to use it.\r\n", "general": { "identifier": "13", "url_type": "URI", "url": "https://ds-wizard.org", "title": "(\"en_US\",\"Data Stewardship Wizard\")", "language": [ "en" ], "description": "(\"en_US\",\"DTL’s Rob Hooft has developed a Data Stewardship Wizard in collaboration with colleagues from the Czech ELIXIR node. The Data Stewardship Wizard converts a lengthy data management questionnaire into an effective flowchart, saving you research time and money, and enhancing the quality of your Data Management Plan.\")", "keywords": [ "(\"en_US\",\"\tdata management plan\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"data management\")", "(\"en_US\",\" open science\")" ], "geographical_availability": [ "(\"en_US\",\"2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DSW" ] }, "date": "2020" }, "educational": { "interactivity_type": "Active", "access_rights": "© Copyright 2020, DSW", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"© Copyright 2020, DSW\")", "learning_resource_type": "Questionnaire", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R6: Data Management Plans" ] } }, "lo_3oBSI-v4Vb": { "external_id": "3oBSI-v4Vb", "code": "14", "title": "DataONE Best Practices database", "subtitle": "", "description": "The DataONE Best Practices database provides individuals with recommendations on how to effectively work with their data through all stages of the data lifecycle. Users can access best practices within the database by either clicking on a stage of the lifecycle or selecting keywords under search.\r\n\r\nBest Practices Primer\r\nFor students and others new to data management, we provide a Best Practices Primer as an introduction to the DataONE Best Practices database and data management in general.\r\n\r\nPublic Participation in Science Research Data Management Guide\r\nWe also provide a Data Management Guide written specifically for the Citizen Science community that takes the users through the steps of the data lifecycle and links to various DataONE Best Practices online.\r\n", "general": { "identifier": "14", "url_type": "URI", "url": "https://www.dataone.org/best-practices", "title": "(\"en_US\",\"\tDataONE Best Practices database\")", "language": [ "en" ], "description": "(\"en_US\",\"The DataONE Best Practices database provides individuals with recommendations on how to effectively work with their data through all stages of the data lifecycle. Users can access best practices within the database by either clicking on a stage of the lifecycle or selecting keywords under search. Best Practices Primer For students and others new to data management, we provide a Best Practices Primer as an introduction to the DataONE Best Practices database and data management in general. Public Participation in Science Research Data Management Guide We also provide a Data Management Guide written specifically for the Citizen Science community that takes the users through the steps of the data lifecycle and links to various DataONE Best Practices online.\")", "keywords": [ "(\"en_US\",\"data lifecycle\")", "(\"en_US\",\"data\")", "(\"en_US\",\"database\")" ], "geographical_availability": [ "(\"en_US\",\"\tNot available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Technical validator", "entity": [ "FOAF" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "DataONE", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"DataONE\")", "learning_resource_type": "Narrative text", "interactivity_level": "Low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R6: Data Management Plans", "R10: Metadata standards & schemas (including geospatial, instruments, variables)" ] } }, "lo_cK8UZJ2Yf6": { "external_id": "cK8UZJ2Yf6", "code": "15", "title": "DataONE Best Practices of Data Management", "subtitle": "", "description": "DataONE is committed to educating the community about data stewardship, including outlining best practices for data management, providing educational materials for use by those that support researchers, and linking to tools and resources available from DataONE and its partners. Below are the different approaches to education taken by DataONE.\r\n", "general": { "identifier": "15", "url_type": "URI", "url": "https://dataoneorg.github.io/Education/bestpractices/", "title": "(\"en_US\",\"DataONE Education\")", "language": [ "en" ], "description": "(\"en_US\",\"DataONE is committed to educating the community about data stewardship, including outlining best practices for data management, providing educational materials for use by those that support researchers, and linking to tools and resources available from DataONE and its partners. Below are the different approaches to education taken by DataONE.\")", "keywords": [ "(\"en_US\",\"education\")", "(\"en_US\",\"data stewardship\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"learningpath01\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DataONE" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "DataONE", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"DataONE\")", "learning_resource_type": "Lecture", "interactivity_level": "Low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)" ] } }, "lo_71WODClDiZ": { "external_id": "71WODClDiZ", "code": "16", "title": "EGI Webinar Programme", "subtitle": "", "description": "In March 2013 EGI established an EGI Webinar Programme whereby web based presentations and workshops are arranged for the benefit of those who wish to expand and enhance their use of EGI's distributed computing and data facilities at large. Each Webinar event delivers an interactive presentation by a guest lecturer who is eminent in a specialist field relevant to the EGI community. Each lecture will include a Questions and Answers session. Recordings of the webinars are shared on the EGI YouTube channel or made available in raw recording on the individual event agendas.\r\n", "general": { "identifier": "16", "url_type": "URI", "url": "https://wiki.egi.eu/wiki/EGI_Webinar_Programme", "title": "(\"en_US\",\"\tEGI Webinar Programme\")", "language": [ "en" ], "description": "(\"en_US\",\"In March 2013 EGI established an EGI Webinar Programme whereby web based presentations and workshops are arranged for the benefit of those who wish to expand and enhance their use of EGI's distributed computing and data facilities at large. Each Webinar event delivers an interactive presentation by a guest lecturer who is eminent in a specialist field relevant to the EGI community. Each lecture will include a Q&A session. Recordings of the webinars are shared on the EGI YouTube channel or made available in raw recording on the individual event agendas.\")", "keywords": [ "(\"en_US\",\"webinar\")", "(\"en_US\",\"grid infrastructure\")", "(\"en_US\",\" cloud infrastructure\")" ], "geographical_availability": [ "(\"en_US\",\"\t2013-2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "EGI" ] }, "date": "2019-04-18" }, "educational": { "interactivity_type": "Active", "access_rights": "EGI.eu", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"EGI.eu\")", "learning_resource_type": "Lecture", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R5: Cloud computing (Virtual Machines & containers) for data processing", "R15: Virtual Research Environments for data analysis (design & implementation)", "R16: Workflow engines for automated data processing" ] } }, "lo_znd2n5sphy": { "external_id": "znd2n5sphy", "code": "17", "title": "Enabling FAIR Data – FAQs", "subtitle": "", "description": "This FAQ is a companion to the Enabling FAIR Data Commitment Statement and the Author Guidelines being implemented by publishers who are signatories. (“FAIR” is defined as findable, accessible, interoperable, and reusable in the FAIR Guiding Principles.) This FAQ is not meant to contradict anything stated in either the Commitment Statement or the Author Guidelines. Instead, it is meant to help provide answers to common questions and best practices.\r\n", "general": { "identifier": "17", "url_type": "URI", "url": "http://www.copdess.org/enabling-fair-data-project/enabling-fair-data-faqs/", "title": "(\"en_US\",\"Enabling FAIR Data – FAQs\")", "language": [ "en" ], "description": "(\"en_US\",\"\tThis FAQ is a companion to the Enabling FAIR Data Commitment Statement and the Author Guidelines being implemented by publishers who are signatories. (“FAIR” is defined as findable, accessible, interoperable, and reusable in the FAIR Guiding Principles.)\")", "keywords": [ "(\"en_US\",\"\tfair data\")", "(\"en_US\",\"fairness\")", "(\"en_US\",\"faq\")" ], "geographical_availability": [ "(\"en_US\",\"\tNot available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "COPDESS - Coalition for Publishing Data in the Earth and Space Sciences" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "COPDESS", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "(\"en_US\",\"Free access\")", "learning_resource_type": "FAQ", "interactivity_level": "Very low", "semantic_density": "Very low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Very easy", "typical_learning_time": "10M" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_Z17mANuAL_": { "external_id": "Z17mANuAL_", "code": "18", "title": "Essential 4 Data Support", "subtitle": "", "description": "Essentials 4 Data Support is an introductory course and tutorial for those people who (want to) support researchers in storing, managing, archiving and sharing their research data.\r\nEssentials 4 Data Support is a product of Research Data Netherlands.\r\n", "general": { "identifier": "18", "url_type": "URI", "url": "https://datasupport.researchdata.nl/en/", "title": "(\"en_US\",\"Essentials 4 Data Support\")", "language": [ "en" ], "description": "(\"en_US\",\"The Essentials 4 Data Support course aims to contribute to professionalization of data supporters and coordination between them. Data supporters are people who support researchers in storing, managing, archiving and sharing their research data.\")", "keywords": [ "(\"en_US\",\"research data\")", "(\"en_US\",\"data management\")", "(\"en_US\",\" data lifecycle\")" ], "geographical_availability": [ "(\"en_US\",\"2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "Research Data Netherlands" ] }, "date": "2020" }, "educational": { "interactivity_type": "Active", "access_rights": "Research Data Netherlands ", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Creative Commons Attribution-ShareAlike 4.0 International License\")", "learning_resource_type": "Exercise", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "50H" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_VVwUhl5bm0": { "external_id": "VVwUhl5bm0", "code": "19", "title": "FAIR Data Training - DTL", "subtitle": "", "description": "With the FAIR Data principles gaining momentum, many people want to learn more about FAIR Data.\r\n\r\nThis FAIR Data training may be generic (i.e., applicable in all research domains for all researchers) or tailored to specific domain experts and data (e.g., medical researchers with patient data). Training related to Data Management and Data Stewardship is also part of this tutorial training.\r\n", "general": { "identifier": "19", "url_type": "URI", "url": "https://www.dtls.nl/fair-data/fair-data-training/", "title": "(\"en_US\",\"FAIR Data Training\")", "language": [ "en" ], "description": "(\"en_US\",\"With the FAIR Data principles gaining momentum, many people want to learn more about FAIR Data. This FAIR Data training may be generic (i.e., applicable in all research domains for all researchers) or tailored to specific domain experts and data (e.g., medical researchers with patient data). Training related to Data Management and Data Stewardship is also part of this training.\")", "keywords": [ "(\"en_US\",\"\tdata management\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"data stewardship\")" ], "geographical_availability": [ "2013-2020" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DTL - Dutch Techcentre for Life Sciences" ] }, "date": "2013-2020" }, "educational": { "interactivity_type": "Active", "access_rights": "© 2020 Dutch Techcentre for Life Sciences", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"© 2020 Dutch Techcentre for Life Sciences\")", "learning_resource_type": "Lecture", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_pxMdAHrAk0": { "external_id": "pxMdAHrAk0", "code": "21", "title": "FAIR for Beginners", "subtitle": "", "description": "A school to learn about the FAIR principles and why they are important, gain insight into how they are used and find FAIR tools you can use in your research.\r\n", "general": { "identifier": "21", "url_type": "URI", "url": "https://www.deic.dk/en/data-management/instructions-and-guides/FAIR-for-Beginners", "title": "(\"en_US\",\"FAIR for Beginners\")", "language": [ "en; dn" ], "description": "(\"en_US\",\"Learn about the FAIR principles and why they are important, gain insight into how they are used and find FAIR tools you can use in your research.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"data mangement\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"learningpath01\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DeiC" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Active", "access_rights": "Danish e-infrastructure Cooperation (DeiC) ", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"\tFree access\")", "learning_resource_type": "Lecture", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_SLWIUyMfLY": { "external_id": "SLWIUyMfLY", "code": "22", "title": "FAIR Principles Training - PARTHENOS ", "subtitle": "", "description": "Eight training modules related to FAIR principles.\r\n\r\nAlthough they have been organised as a school to suit self-learners as well, the PARTHENOS Project training materials are primarily intended as ‘train-the-trainers’ support materials.  Although research infrastructures and projects are becoming more and more of a destination for DH graduates, their operations are often at one remove from the academic units providing their training.  The materials on this web site are intended to assist in bridging that gap, overcoming the general inclination within infrastructure projects to provide only training on tools, rather than finding effective ways to transfer a greater bulk of our experiential knowledge.\r\n", "general": { "identifier": "22", "url_type": "URI", "url": "http://training.parthenos-project.eu/sample-page/manage-improve-and-open-up-your-research-and-data/introduction-to-research-data-management/the-fair-principles/", "title": "(\"en_US\",\"FAIR Principles Training - PARTHENOS\")", "language": [ "en" ], "description": "(\"en_US\",\"Although they have been organised to suit self-learners as well, the PARTHENOS Project training materials are primarily intended as ‘train-the-trainers’ support materials. Although research infrastructures and projects are becoming more and more of a destination for DH graduates, their operations are often at one remove from the academic units providing their training. The materials on this web site are intended to assist in bridging that gap, overcoming the general inclination within infrastructure projects to provide only training on tools, rather than finding effective ways to transfer a greater bulk of our experiential knowledge.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"data mangement\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "PARTHENOS" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Active", "access_rights": "PARTHENOS Project", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Creative Commons Attribution 4.0 International license CC BY\")", "learning_resource_type": "Lecture", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "G5: Basic Research Data Management (RDM)", "R4: Certification schemes for repositories (CoreTrustSeal)", "R6: Data Management Plans", "R8: Licenses & policies for data use", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)" ] } }, "lo_Ytb7016Ijs": { "external_id": "Ytb7016Ijs", "code": "23", "title": "FAIR self-assessment tool", "subtitle": "", "description": "The ANDS-Nectar-RDS FAIR data self-assessment tool enables you to assess the 'FAIRness' of a dataset and determine how to enhance its FAIRness (where applicable).\r\n\r\nThis self-assessment tool has been designed predominantly for data librarians and IT staff, but could be used by software engineers developing FAIR data tools and services, and researchers provided they have assistance from research support staff.\r\n\r\nIn this workshop-like resource, you will be asked questions related to the principles underpinning Findable, Accessible, Interoperable and Reusable. Once you have answered all the questions in each section you will be given a ‘green bar’ rating based on your answers in that section, and when all sections are completed, an overall 'FAIRness' rating is provided.\r\n", "general": { "identifier": "23", "url_type": "URI", "url": "https://ardc.edu.au/resources/working-with-data/fair-data/fair-self-assessment-tool/", "title": "(\"en_US\",\"FAIR self-assessment tool\")", "language": [ "en" ], "description": "(\"en_US\",\"The ANDS-Nectar-RDS FAIR data self-assessment tool enables you to assess the 'FAIRness' of a dataset and determine how to enhance its FAIRness (where applicable). This self-assessment tool has been designed predominantly for data librarians and IT staff, but could be used by software engineers developing FAIR data tools and services, and researchers provided they have assistance from research support staff. You will be asked questions related to the principles underpinning Findable, Accessible, Interoperable and Reusable. Once you have answered all the questions in each section you will be given a ‘green bar’ rating based on your answers in that section, and when all sections are completed, an overall 'FAIRness' rating is provided.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"fair assessment\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ARDC - Australian Research Data Commons" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Active", "access_rights": "Copyright © 2020 ARDC. ACN 633 798 857.", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Copyright © 2020 ARDC. ACN 633 798 857.\")", "learning_resource_type": "Questionnaire", "interactivity_level": "Low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Very easy", "typical_learning_time": "10M" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G3: Performing a FAIRness self-assessment" ] } }, "lo_kHhx9jiEZn": { "external_id": "kHhx9jiEZn", "code": "24", "title": "FAIR Training - Phortos", "subtitle": "", "description": "A key element of the transition to pervasive FAIR data is training up a new generation of data specialists that enable and support researchers. Phortos Consultants has developed curriculums for the following key positions in this FAIR Data ecosystem:\r\n\r\n- FAIR Readiness Program Manager: oversees the end-to-end readiness program that is executed when organisations decide to implement a FAIR Data approach.\r\n- FAIR Data Steward: Oversees the data life cycle in general and those of specific projects once a FAIR data approach is operational.\r\n- FAIR Data & Services Operator: Operationally manages and executes FAIR data tooling.\r\n- FAIR Data & Services Engineer: Develops tooling & apps.\r\n\r\nFor each of these roles there are different types of training and workshops.\r\n", "general": { "identifier": "24", "url_type": "URI", "url": "https://www.phortosconsultants.com/training", "title": "(\"en_US\",\"FAIR Training - Phortos\")", "language": [ "en" ], "description": "(\"en_US\",\"5 days courses which include the 1-day Fair Awareness course. The courses are given by leading experts in the area of FAIR data, ontological & semantic technologies, data stewardship and their practical application in enabling data driven research.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"fair\")", "(\"en_US\",\"data mangement\")", "(\"en_US\",\"data stewardship\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "Phortos Consultants" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Active", "access_rights": "CC BY 2019 - Phortos Consultants", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"CC BY 2019 - Phortos Consultants\")", "learning_resource_type": "Lecture", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G2: Metrics for FAIRness evaluation", "G3: Performing a FAIRness self-assessment", "R3: Cataloguing - design & implementation", "R8: Licenses & policies for data use", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R13: Provenance tracing", "R16: Workflow engines for automated data processing" ] } }, "lo_lsj7UAfIo9": { "external_id": "lsj7UAfIo9", "code": "25", "title": "FAIRsharing.org", "subtitle": "", "description": "A curated, informative and educational tutorial on data and metadata standards, inter-related to databases and data policies.\r\n", "general": { "identifier": "25", "url_type": "URI", "url": "https://fairsharing.org", "title": "(\"en_US\",\"FAIRsharing.org\")", "language": [ "en" ], "description": "(\"en_US\",\"A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies\")", "keywords": [ "(\"en_US\",\"databases\")", "(\"en_US\",\"policies\")", "(\"en_US\",\"standard\")", "(\"en_US\",\"fair data\")", "(\"en_US\",\"collections\")", "(\"en_US\",\"reccomendations\")" ], "geographical_availability": [ "(\"en_US\",\"2009-2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "FAIRsharing" ] }, "date": "2020-01-24" }, "educational": { "interactivity_type": "Active", "access_rights": "FAIRsharing ", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Creative Commons by Share Alike 4.0 International\")", "learning_resource_type": "Lecture", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G2: Metrics for FAIRness evaluation", "G3: Performing a FAIRness self-assessment", "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "G5: Basic Research Data Management (RDM)", "G6: Writing technical documentation for services", "G7: Other" ] } }, "lo_BkdUUrwxcH": { "external_id": "BkdUUrwxcH", "code": "26", "title": "GO FAIR - FAQs", "subtitle": "", "description": "Seven frequently asked and very useful questions with simple answers and best practices suggestions.\r\n", "general": { "identifier": "26", "url_type": "URI", "url": "https://www.go-fair.org/faq/", "title": "(\"en_US\",\"GO FAIR - FAQs\")", "language": [ "en" ], "description": "(\"en_US\",\"Seven frequently asked and very useful questions with simple answers.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"open data\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "GO FAIR" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "GO FAIR", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "(\"en_US\",\"Creative Commons Attribution 4.0 License\")", "learning_resource_type": "FAQ", "interactivity_level": "Very low", "semantic_density": "Very low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Very easy", "typical_learning_time": "10M" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles" ] } }, "lo_3oBSI4VbkJ": { "external_id": "3oBSI4VbkJ", "code": "27", "title": "Farm Data Train", "subtitle": "", "description": "The Farm Data Train project aims to connect agricultural data to make them more usable. It is a joint initiative of DTL, GODAN, CABI, and Wageningen UR. Access the video tutorial here.\r\n", "general": { "identifier": "27", "url_type": "URI", "url": "https://vimeo.com/215975839", "title": "(\"en_US\",\"Farm Data Train\")", "language": [ "en" ], "description": "(\"en_US\",\"The Farm Data Train project aims to connect agricultural data to make them more usable. It is a joint initiative of DTL, GODAN, CABI, and Wageningen UR.\")", "keywords": [ "(\"en_US\",\"agricultural data\")", "(\"en_US\",\"data training\")" ], "geographical_availability": [ "(\"en_US\",\"2018\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DTL - Dutch TechCentre for Life Sciences" ] }, "date": "2018" }, "educational": { "interactivity_type": "Expositive", "access_rights": "DTL - Dutch TechCentre for Life Sciences", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"DTL - Dutch TechCentre for Life Sciences\")", "learning_resource_type": "Video", "interactivity_level": "Very low", "semantic_density": "Very low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Very easy", "typical_learning_time": "PT2M33S" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "R1: Access control (Authorization-Authentication-Identification, or AAI) methods", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R11: PID allocation & use (including citation support, bibliometry, provenance)" ] } }, "lo_Z17mANuAgD": { "external_id": "Z17mANuAgD", "code": "28", "title": "GO FAIR Training", "subtitle": "", "description": "The High Level Expert Group report on the EOSC mentions an urgent need to educate and equip up to 500 thousand data stewards in Europe. Hence, GO FAIR will strongly focus on training. The​ ​GO TRAIN​ ​pillar will coordinate​ ​training and workshop to use​ ​and provide FAIR​ ​data​ ​and services.\r\n", "general": { "identifier": "28", "url_type": "URI", "url": "https://www.go-fair.org/training/", "title": "(\"en_US\",\"GO FAIR Training\")", "language": [ "en" ], "description": "(\"en_US\",\"The High Level Expert Group report on the EOSC mentions an urgent need to educate and equip up to 500 thousand data stewards in Europe. Hence, GO FAIR will strongly focus on training. The​ ​GO TRAIN​ ​pillar will coordinate​ the ​training to use​ ​and provide FAIR​ ​data​ ​and services.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"data stewards\")", "(\"en_US\",\"training\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "GO FAIR" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "GO FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Creative Commons Attribution 4.0 License\")", "learning_resource_type": "Narrative text", "interactivity_level": "Very low", "semantic_density": "Very low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Very easy", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_VVwU5bm0hB": { "external_id": "VVwU5bm0hB", "code": "29", "title": "How to make your data FAIR - Guide for Researchers", "subtitle": "", "description": "Why are the FAIR principles needed? The increasing availability of online resources means that data need to be created with longevity in mind. Providing other researchers with access to your data facilitates knowledge discovery and improves research transparency. Learn about best practices to achieve this objective.\r\n", "general": { "identifier": "29", "url_type": "URI", "url": "https://www.openaire.eu/how-to-make-your-data-fair?rCH=2", "title": "(\"en_US\",\"How to make your data FAIR - Guide for Researchers\")", "language": [ "en" ], "description": "(\"en_US\",\"Why are the FAIR principles needed? The increasing availability of online resources means that data need to be created with longevity in mind. Providing other researchers with access to your data facilitates knowledge discovery and improves research transparency.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"data stewardship\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "OpenAIRE" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "OpenAIRE", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"CC ATTRIBUTION 4.0 INTERNATIONAL LICENSE\")", "learning_resource_type": "Narrative text", "interactivity_level": "Very low", "semantic_density": "Low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_pxMdAHrAg0": { "external_id": "pxMdAHrAg0", "code": "30", "title": "Personal Health Train", "subtitle": "", "description": "The Personal Health Train is a video tutorial designed to make health data more accessible to anyone.\r\n", "general": { "identifier": "30", "url_type": "URI", "url": "https://vimeo.com/143245835", "title": "(\"en_US\",\"Personal Health Train\")", "language": [ "en" ], "description": "(\"en_US\",\"The Personal Health Train objective is to make health data more accessible to anyone.\")", "keywords": [ "(\"en_US\",\"health data\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"data access\")", "(\"en_US\",\"personal health data\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DTL - Dutch Techcentre for Life Sciences" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "DTL - Dutch Techcentre for Life Sciences", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"DTL - Dutch Techcentre for Life Sciences\")", "learning_resource_type": "Video", "interactivity_level": "Very low", "semantic_density": "Very low", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Very easy", "typical_learning_time": "PT2M50S" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "R1: Access control (Authorization-Authentication-Identification, or AAI) methods", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R11: PID allocation & use (including citation support, bibliometry, provenance)" ] } }, "lo_FdW84TkcrM": { "external_id": "FdW84TkcrM", "code": "31", "title": "RDM Starter Kit ", "subtitle": "", "description": "Starter Kit for research data management (RDM). It lists resources, workshops, tutorials and best practices designed to help researchers get started to organize their data.\r\n", "general": { "identifier": "31", "url_type": "URI", "url": "https://www.go-fair.org/resources/rdm-starter-kit/", "title": "(\"en_US\",\"RDM Starter Kit\")", "language": [ "en" ], "description": "(\"en_US\",\"Starter Kit for research data management (RDM). It lists resources designed to help researchers get started to organize their data.\")", "keywords": [ "(\"en_US\",\"fair data\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"guidelines for researchers\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "GO FAIR" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "GO FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Creative Commons Attribution 4.0 License\")", "learning_resource_type": "Narrative text", "interactivity_level": "Very low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R6: Data Management Plans", "R8: Licenses & policies for data use", "R11: PID allocation & use (including citation support, bibliometry, provenance)" ] } }, "lo_6rUvbkfXpL": { "external_id": "6rUvbkfXpL", "code": "32", "title": "TeSS: ELIXIR's Training Portal", "subtitle": "", "description": "This portal allows browsing, discovering and organising life sciences training resources, tutorials and workshops, aggregated from ELIXIR nodes and 3rd-party providers.\r\n", "general": { "identifier": "32", "url_type": "URI", "url": "https://tess.elixir-europe.org", "title": "(\"en_US\",\"TeSS: ELIXIR's Training Portal\")", "language": [ "en" ], "description": "(\"en_US\",\"This portal allows browsing, discovering and organising life sciences training resources, aggregated from ELIXIR nodes and 3rd-party providers.\")", "keywords": [ "(\"en_US\",\"training portal\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"machine leraning\")", "(\"en_US\",\"simulations\")", "(\"en_US\",\"data analysis\")" ], "geographical_availability": [ "(\"en_US\",\"2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"1.0.0\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ELIXIR TeSS" ] }, "date": "2020" }, "educational": { "interactivity_type": "Active", "access_rights": "ELIXIR project", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ELIXIR project\")", "learning_resource_type": "Narrative text", "interactivity_level": "Medium", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R8: Licenses & policies for data use", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R16: Workflow engines for automated data processing" ] } }, "lo_SMQ3q_15Du": { "external_id": "SMQ3q_15Du", "code": "33", "title": "DANS Training", "subtitle": "", "description": "The expertise built up in national and European projects is reflected in the training courses, best practices and advice provided by DANS, intended for researchers, research institutions, research funders, data professionals and other archives.\r\n", "general": { "identifier": "33", "url_type": "URI", "url": "https://dans.knaw.nl/en/about/services/training-consultancy/training", "title": "(\"en_US\",\"DANS Training\")", "language": [ "en" ], "description": "(\"en_US\",\"The expertise built up in national and European projects is reflected in the training courses and advice provided by DANS, intended for researchers, research institutions, research funders, data professionals and other archives.\")", "keywords": [ "(\"en_US\",\"data reuse\")", "(\"en_US\",\"data sharing\")", "(\"en_US\",\"data management\")", "(\"en_US\",\"fair data\")", "(\"en_US\",\"persistent identifiers\")", "(\"en_US\",\"data management plan\")", "(\"en_US\",\" data repositories\")" ], "geographical_availability": [ "(\"en_US\",\"2018-2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DANS - Data Archiving and Networked Services" ] }, "date": "2018-2019" }, "educational": { "interactivity_type": "Expositive", "access_rights": "DANS - Data Archiving and Networked Services", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"DANS - Data Archiving and Networked Services\")", "learning_resource_type": "Narrative text", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo_3oBSI-v5Vb": { "external_id": "3oBSI-v5Vb", "code": "34", "title": "CESSDA Training Resources", "subtitle": "", "description": "To facilitate teaching in the social sciences and to support continuous learning and training, the CESSDA Training Working Group designs various training materials, tutorials and resources for finding, managing and preserving data.\r\n", "general": { "identifier": "34", "url_type": "URI", "url": "https://www.cessda.eu/Training/Training-Resources", "title": "(\"en_US\",\"CESSDA Training Resources\")", "language": [ "en" ], "description": "(\"en_US\",\"To facilitate teaching in the social sciences and to support continuous learning and training, the CESSDA Training Working Group designs various training materials and resources for finding, managing and preserving data.\")", "keywords": [ "(\"en_US\",\"data management\")", "(\"en_US\",\" data preservation\")", "(\"en_US\",\"data finding\")", "(\"en_US\",\"data discovery\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "CESSDA - Consortium of European Social Science Data Archives" ] }, "date": "Not available" }, "educational": { "interactivity_type": "Expositive", "access_rights": "CESSDA Training Working Group", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"CESSDA Training Working Group\")", "learning_resource_type": "Narrative text", "interactivity_level": "Very low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)" ] } }, "lo__MMLRIo97e": { "external_id": "_MMLRIo97e", "code": "35", "title": "EDI Webinars", "subtitle": "", "description": "The Environmental Data Initiative is an NSF-funded project, actively promoting and enabling curation and re-use of environmental data. Through webinars and workshops, we assist researchers from field stations, individual laboratories, and research projects of all sizes to archive and publish their environmental data. EDI is committed to enable data that is Findable, Accessible, Interoperable, and Reusable.\r\n", "general": { "identifier": "35", "url_type": "URI", "url": "https://edirepository.org/webinars/webinars-grid", "title": "(\"en_US\",\"EDI Webinars\")", "language": [ "en" ], "description": "(\"en_US\",\"The Environmental Data Initiative is an NSF-funded project, actively promoting and enabling curation and re-use of environmental data. We assist researchers from field stations, individual laboratories, and research projects of all sizes to archive and publish their environmental data. EDI is committed to enable data that is Findable, Accessible, Interoperable, and Reusable.\")", "keywords": [ "(\"en_US\",\"environmental data\")", "(\"en_US\",\"data management\")", "(\"en_US\",\" fair data\")", "(\"en_US\",\"data processing\")", "(\"en_US\",\" metadata\")", "(\"en_US\",\"data repositories\")" ], "geographical_availability": [ "(\"en_US\",\"2017-2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "EDI - Environmental Data Initiative" ] }, "date": "2017-2019" }, "educational": { "interactivity_type": "Expositive", "access_rights": "2019 Environmental Data Initiative", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"2019 Environmental Data Initiative\")", "learning_resource_type": "Webinar", "interactivity_level": "Low", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R2: API (Application Program Interface) design for data & metadata access", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R15: Virtual Research Environments for data analysis (design & implementation)" ] } }, "lo_kMFdW84Tkc": { "external_id": "kMFdW84Tkc", "code": "36", "title": "EBI/EMBL Webinars", "subtitle": "", "description": "This webinar series is a freely accessible collection of live seminars and workshops focused on EMBL-EBI resources. They provide both brief introductions to a range of databases and more in-depth coverage of new features and tools to assist you in your research.\r\n", "general": { "identifier": "36", "url_type": "URI", "url": "https://www.ebi.ac.uk/training/webinars", "title": "(\"en_US\",\"EBI/EMBL Webinars\")", "language": [ "en" ], "description": "(\"en_US\",\"This webinar series is a freely accessible collection of live seminars focused on EMBL-EBI resources. They provide both brief introductions to a range of databases and more in-depth coverage of new features and tools to assist you in your research.\")", "keywords": [ "(\"en_US\",\"data management\")", "(\"en_US\",\"fair \")", "(\"en_US\",\"data\")", "(\"en_US\",\" scientific data\")", "(\"en_US\",\"workshop\")" ], "geographical_availability": [ "(\"en_US\",\"2007-2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "EMBL-EBI Training Programme" ] }, "date": "2007-2020" }, "educational": { "interactivity_type": "Expositive", "access_rights": "EMBL 2020", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"EMBL 2020\")", "learning_resource_type": "Webinar", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R9: Linked Data and ontologies", "R13: Provenance tracing" ] } }, "lo_vgvl5Px_aL": { "external_id": "vgvl5Px_aL", "code": "37", "title": "NASA EARTH Data - Webinars and Tutorials", "subtitle": "", "description": "Data recipes are tutorials that include step-by-step instructions to help users learn how to discover, access, subset, visualize and use Earth science data, information, tools and services. These tutorials cover many different data products across the Earth science disciplines and different data discovery and data access tools, including programming languages and related software.\r\n", "general": { "identifier": "37", "url_type": "URI", "url": "https://earthdata.nasa.gov/learn/user-resources/webinars-and-tutorials", "title": "(\"en_US\",\"NASA EARTH Data - Webinars and Tutorials\")", "language": [ "en" ], "description": "(\"en_US\",\"Data recipes are tutorials that include step-by-step instructions to help users learn how to discover, access, subset, visualize and use Earth science data, information, tools and services. These tutorials cover many different data products across the Earth science disciplines and different data discovery and data access tools, including programming languages and related software.\")", "keywords": [ "(\"en_US\",\"data management\")", "(\"en_US\",\"data resources\")", "(\"en_US\",\"fair data\")", "(\"en_US\",\"data discovery\")", "(\"en_US\",\"data access\")", "(\"en_US\",\"earth science\")" ], "geographical_availability": [ "(\"en_US\",\"2013-2019\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "NASA Earth Data" ] }, "date": " Jan 14, 2020" }, "educational": { "interactivity_type": "Expositive", "access_rights": "NASA Earth Data", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"NASA Earth Data\")", "learning_resource_type": "Video", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Knowledge-dependent", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R17: Other" ] } }, "lo_Fz-JVAiWhf": { "external_id": "Fz-JVAiWhf", "code": "40", "title": "Terminologies for ENVRIs: why, what and how", "subtitle": "", "description": "Presentations and course material from the ENVRI FAIR workshop session "Terminologies for ENVRIs: why, what and how" held physically in Dresden on 5 February 2020, with the possibility connect remotely. \r\n", "general": { "identifier": "40", "url_type": "URI", "title": "(\"en_US\",\"Terminologies for ENVRIs: why, what and how\")", "language": [ "en" ], "description": "(\"en_US\",\"Presentations and course material from the ENVRI FAIR training session Terminolgies for ENVRIs: why, what and how held physically in Dresden on 5 February 2020 with the possibility to connect remotely.\")", "keywords": [ "(\"en_US\",\"Semantic web\")", "(\"en_US\",\" Ontologies\")", "(\"en_US\",\"ENVRI week\")" ], "geographical_availability": [ "(\"en_US\",\"Ontologies and semantic web\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "5 February 2020" }, "educational": { "interactivity_type": "Expositive", "access_rights": "ENVRI FAIR project 2020", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Not available\")", "learning_resource_type": "Webinar", "interactivity_level": "Low", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "3 hours" }, "technical": { "size": "Not available", "topic_codes": [ "R9: Linked Data and ontologies" ] } }, "lo_FdW84TkcDs": { "external_id": "FdW84TkcDs", "code": "41", "title": "DANUBIUS-RI Functioning of River-Sea Systems", "subtitle": "Lecture 1 ", "description": "DANUBIUS-RI’s Mission is to facilitate and contribute excellent science on understanding the continuum from river source to sea to provide interdisciplinary knowledge and data for sustainable management, use and protection of River-Sea Systems. Lecture 1 - Documentary (video tutorial).\r\n", "general": { "identifier": "41", "url_type": "URI", "url": "https://www.youtube.com/watch?v=LoqZvSll4O0", "title": "(\"en_US\",\"Lecture 1 Functioning of River-Sea Systems\")", "language": [ "en" ], "description": "(\"en_US\",\"In this video the first lecture on River-Sea Systems is provided.\")", "keywords": [ "(\"en_US\",\"River-Sea Systems\")", "(\"en_US\",\"Ecosystem Functioning\")" ], "geographical_availability": [ "(\"en_US\",\"Not available\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "DANUBIUS" ] }, "date": "2019-11-19" }, "educational": { "interactivity_type": "Expositive", "access_rights": "Not available", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"free\")", "learning_resource_type": "Video", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Other", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "R6: Data Management Plans" ] } }, "lo_38ECV3ZASY": { "external_id": "38ECV3ZASY", "code": "43", "title": "Towards the ENVRI Community International Winter School DATA FAIRness - Webinar Programme", "subtitle": "July - September 2020", "description": "For two years in a row already, the ENVRI Community International Summer School on Data FAIRness has been assembling in Lecce, in the middle of the summer season, those researchers, experts and technical staff from different environmental and research infrastructures who want to deepen their knowledge on this topic. Unfortunately, the ongoing COVID-19 restrictions have ordained the postponement of the current edition until the beginning of next year, when the ‘ENVRI Community Winter School on Data FAIRness' will take place, always in Lecce. The delay has created the opportunity to enrich our training offerings on the subject, with a series of online workshops dedicated to data management, leading the way ‘Towards the ENVRI community Winter School'.\r\n\r\nThree webinars on Data FAIRness have been jointly organised by ENVRI-FAIR and LifeWatch ERIC from July to September 2020, with a focus on helping end users, particularly ENVRI-FAIR project partners and data centre staff, make the best use of their data.\r\n\r\nUnder the heading of ‘Towards the ENVRI Community Winter School', the online training series debuts on Monday 13 July 2020. The first broadcast is presented by Zhiming Zhao, from the University of Amsterdam, and will go to air from 9:30 to 12:00 CEST, providing ‘An introduction to Cloud Computing'. \r\n\r\nThe second webinar on ‘Workflows Orchestration and Execution' will follow on Tuesday 14 July, from 10:00-12:00, presented by Nicola Fiore and Lucia Vaira, both from LifeWatch ERIC. \r\n\r\nThe third webcast is scheduled for 22 September and will feature Claudio D'Onofrio and Karolina Pantazatou, both from ICOS ERIC, with ‘An Introduction to Jupyter'.\r\n", "general": { "identifier": "43", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=46", "title": "(\"en_US\",\"Towards the ENVRI Community International Winter School DATA FAIRness - Webinar Programme\")", "language": [ "en" ], "description": "(\"en_US\",\"For two years in a row already, the ENVRI Community International Summer School on Data FAIRness has been assembling in Lecce, in the middle of the summer season, those researchers, experts and technical staff from different environmental and research infrastructures who want to deepen their knowledge on this topic. Unfortunately, the ongoing COVID-19 restrictions have ordained the postponement of the current edition until the beginning of next year, when the ‘ENVRI Community Winter School on Data FAIRness' will take place, always in Lecce. The delay has created the opportunity to enrich our training offerings on the subject, with a series of online webinars dedicated to data management, leading the way ‘Towards the ENVRI community Winter School'. Three webinars on Data FAIRness have been jointly organised by ENVRI-FAIR and LifeWatch ERIC from July to September 2020, with a focus on helping end users, particularly ENVRI-FAIR project partners and data centre staff, make the best use of their data. Under the heading of ‘Towards the ENVRI Community Winter School', the online training series debuts on Monday 13 July 2020. The first broadcast is presented by Zhiming Zhao, from the University of Amsterdam, and will go to air from 9:30 to 12:00 CEST, providing ‘An introduction to Cloud Computing'. The second webinar on ‘Workflows Orchestration and Execution' will follow on Tuesday 14 July, from 10:00-12:00, presented by Nicola Fiore and Lucia Vaira, both from LifeWatch ERIC. The third webcast is scheduled for 22 September and will feature Claudio D'Onofrio and Karolina Pantazatou, both from ICOS ERIC, with ‘An Introduction to Jupyter'.\")", "keywords": [ "(\"en_US\",\"ENVRI\")", "(\"en_US\",\"FAIRNESS\")", "(\"en_US\",\"Cloud Computing\")", "(\"en_US\",\"Workflow\")", "(\"en_US\",\"Jupyter\")", "(\"en_US\",\"Data\")", "(\"en_US\",\"Webinar\")" ], "geographical_availability": [ "(\"en_US\",\"2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "July - September 2020" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR project Work Package 6 Core Team", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR project Work Package 6 Core Team\")", "learning_resource_type": "Webinar", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "PT6H" }, "technical": { "size": "Not available", "topic_codes": [ "R5: Cloud computing (Virtual Machines & containers) for data processing", "R15: Virtual Research Environments for data analysis (design & implementation)", "R16: Workflow engines for automated data processing" ] } }, "lo_34ECV3ZAgc": { "external_id": "34ECV3ZAgc", "code": "44", "title": "FAIR the smart way: Introducing the ENVRI Knowledge Base", "subtitle": "", "description": "An introduction and demonstration of the ENVRI Knowledge Base, the available information, information integration, the tools that support exploring the information and thoughts on how you can contribute.\r\n\r\nThe workshop, organised by ENVRI-FAIR Work Packages 5 and 6, has been held in June 3rd 2020 for Research Infrastructure developers, managers, and anyone interested in FAIR Research Infrastructures and has been presented by Markus Stocker.\r\n", "general": { "identifier": "44", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=65", "title": "(\"en_US\",\"FAIR the smart way: Introducing the ENVRI Knowledge Base\")", "language": [ "en" ], "description": "(\"en_US\",\"An introduction and demonstration of the ENVRI Knowledge Base, the available information, information integration, the tools that support exploring the information and thoughts on how you can contribute. The webinar, organised by ENVRI-FAIR Work Packages 5 and 6, has been held in June 3rd 2020 for Research Infrastructure developers, managers, and anyone interested in FAIR Research Infrastructures and has been presented by Markus Stocker.\")", "keywords": [ "(\"en_US\",\"\tFAIRNESS\")", "(\"en_US\",\"Data\")", "(\"en_US\",\"Knowledge Base\")", "(\"en_US\",\"Webinar\")" ], "geographical_availability": [ "(\"en_US\",\"June 2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2020-06-03" }, "educational": { "interactivity_type": "Expositive", "access_rights": "ENVRI-FAIR Project Work Packages 5 and 6", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"\tENVRI-FAIR Project Work Packages 5 and 6\")", "learning_resource_type": "Webinar", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Easy", "typical_learning_time": "PT1H30M" }, "technical": { "size": "Not available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R14: Repository design, operation & sustainability", "R17: Other" ] } }, "lo_68ECV3ZASY": { "external_id": "68ECV3ZASY", "code": "46", "title": "ENVRI-FAIR Task Force 1 Service Catalogue tutorial", "subtitle": "", "description": "In this tutorial, the ENVRI-FAIR Task Force 1 team introduced the ENVRI-FAIR Service Catalogue. In particular, after an overview of the Data Catalogue Vocabulary Application profile (DCAT-AP) and its extension (EPOS-DCAT-AP) in the solid-Earth domain, the team presented the DCAT metadata editor and a demo of the service catalogue.\r\n", "general": { "identifier": "46", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=48", "title": "(\"en_US\",\"ENVRI-FAIR Task Force 1 Service catalogue tutorial session\")", "language": [ "en" ], "description": "(\"en_US\",\"In this tutorial, the ENVRI-FAIR Task Force 1 team introduced the ENVRI-FAIR Service Catalogue. In particular, after an overview of the Data Catalogue Vocabulary Application profile (DCAT-AP) and its extension (EPOS-DCAT-AP) in the solid-Earth domain\")", "keywords": [ "(\"en_US\",\"ENVRI-FAR\")", "(\"en_US\",\"Service catalogue\")", "(\"en_US\",\"DCAT-AP\")", "(\"en_US\",\"EPOS\")", "(\"en_US\",\"EPOS-DCAT-AP\")", "(\"en_US\",\"Task Force 1\")", "(\"en_US\",\"Cataloguing\")", "(\"en_US\",\"solid-Earth domain\")", "(\"en_US\",\" metadata standard\")", "(\"en_US\",\" metadata editor\")" ], "geographical_availability": [ "(\"en_US\",\"2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2020-10-27" }, "educational": { "interactivity_type": "Expositive", "access_rights": "ENVRI-FAIR Project WP5 Task Force 1", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR Project WP5 Task Force 1\")", "learning_resource_type": "Slide", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "PT1H30M" }, "technical": { "size": "3.1 MB", "topic_codes": [ "R3: Cataloguing - design & implementation" ] } }, "lo_kgDsE0fzws": { "external_id": "kgDsE0fzws", "code": "47", "title": "ENVRI Community International Winter School on data FAIRness", "subtitle": "", "description": "The 2021 ENVRI Community International Winter School from January 11-22 attracted 32 participants from all around the world, predominantly data centre staff, researchers and PhD candidates. Centred on the FAIR principles of data management, the online curriculum covered semantic navigation, Jupyter environments for visualisation and data discovery, resource access tools and cloud computing.\r\nIn recognition of the difficulties of distance learning, the organisers structured 40 hours of presence (including preparations) over a two-week period, with scheduled lectures and presentations in the mornings (09-11), followed by associated group and individual work time (11-12). The relevance of the content to the participants' work ensured a high level of commitment and a great sense of camaraderie developed. \r\nFAIR data are data which meet the principles of findability, accessibility, interoperability and reusability. The presentation of real-life use cases using state-of-the-art technologies demonstrated how essential it is to support end users in making the best use of the data, and to develop good user interfaces and services. The time the participants spent together created a new knowledge-exchange network for these data professionals.\r\nThe team of teachers behind the "ENVRI-FAIR Resources: Access & Discoverability" Winter School was also international, with up-to-the-minute experience in the application of new technologies to enhance data centre functionality.\r\nDr Antonio José Saenz-Albanes (ICT Infrastructure Operations Coordinator at LifeWatch ERIC) and Dr Jos√© Maria Garcia-Rodriguez (Associate Professor of Applied Software Engineering at the University of Seville) dealt with how semantics enrich data resources and increase their FINDability by making them machine-actionable;\r\nDr Ute Karstens and Dr Claudio Onofrio, respectively researcher and data scientist at Lund University, Sweden, gave a presentation on a fully integrated VRE application at ICOS Carbon Portal, called the atmospheric transport model STILT, running through a full life cycle for an 'on demand' model and visualising results as an interactive map;\r\nDr Karolina Pantazatou and Ida Storm also work at ICOS Carbon Portal, Lund University, as scientific programmer and project assistant. Their workshop on using GIS-tools and Python-programming and user friendly Jupyter notebooks that process and analyse ICOS data products, had students tweeting in delight: "What a great workspace to document (text, images, links), write code & visualize data - all open and shareable!";\r\nInformatic engineers with the LifeWatch ERIC Service Centre in Lecce, Italy, Nicola Fiore and Lucia Vaira kicked off the second week with a presentation on the LifeWatch ERIC Metadata Catalogue, explaining the entire process behind the creation and publication of new resources and how to access them; and\r\nDr Zhiming Zhao, assistant professor at the University of Amsterdam, used examples from the ENVRIplus and ENVRI-FAIR projects to illustrate how to develop and operate data management services in cloud environments, from running a legacy and native cloud applications, to automating their deployment. Students were able to practice on the cloud infrastructures at EOSC and LifeWatch.\r\nThe final presentations allowed participants to demonstrate just how much they had learned in professional terms, but there was no sad good-bye at the end. Students had been given the recipe for pasticciotti, the characteristic Lecce pastry, the week before, and everyone cheered as the winner of the ENVRI Chef Challenge was announced.\r\n", "general": { "identifier": "47", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=52", "title": "(\"en_US\",\"ENVRI Community International Winter School on data FAIRness\")", "language": [ "en" ], "description": "(\"en_US\",\"The 2021 ENVRI Community International Winter School from January 11-22 attracted 32 participants from all around the world, predominantly data centre staff, researchers and PhD candidates. Centred on the FAIR principles of data management, the online curriculum covered semantic navigation, Jupyter environments for visualisation and data discovery, resource access tools and cloud computing. In recognition of the difficulties of distance learning, the organisers structured 40 hours of presence (including preparations) over a two-week period, with scheduled lectures and presentations in the mornings (09-11), followed by associated group and individual work time (11-12). The relevance of the content to the participants' work ensured a high level of commitment and a great sense of camaraderie developed. FAIR data are data which meet the principles of findability, accessibility, interoperability and reusability. The presentation of real-life use cases using state-of-the-art technologies demonstrated how essential it is to support end users in making the best use of the data, and to develop good user interfaces and services. The time the participants spent together created a new knowledge-exchange network for these data professionals. The team of teachers behind the ENVRI-FAIR Resources: Access & Discoverability Winter School was also international, with up-to-the-minute experience in the application of new technologies to enhance data centre functionality.\")", "keywords": [ "(\"en_US\",\"ENVRI-FAIR\")", "(\"en_US\",\"FAIRNESS\")", "(\"en_US\",\"Cloud Computing\")", "(\"en_US\",\"VRE\")", "(\"en_US\",\"Jupyter\")", "(\"en_US\",\"Data\")", "(\"en_US\",\"Semantics\")", "(\"en_US\",\"Metadata\")", "(\"en_US\",\"Winter school\")", "(\"en_US\",\"learningpath02\")" ], "geographical_availability": [ "(\"en_US\",\"2021\")" ] }, "life_cycle": { "version": "(\"en_US\",\"not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "January 11-22 2021" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR project Work Package 6 Core Team", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR project Work Package 6 Core Team\")", "learning_resource_type": "Lecture", "interactivity_level": "High", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "PT40" }, "technical": { "size": "not available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "R2: API (Application Program Interface) design for data & metadata access", "R3: Cataloguing - design & implementation", "R5: Cloud computing (Virtual Machines & containers) for data processing", "R9: Linked Data and ontologies", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R15: Virtual Research Environments for data analysis (design & implementation)" ] } }, "lo_Sgc1fW4LDo": { "external_id": "Sgc1fW4LDo", "code": "48", "title": "ENVRI WEEK 2021 - Training session", "subtitle": "PIDs for instruments and GDPR in context", "description": "Presentations and course material from the ENVRI Week 2021 training and workshop session held online on 4 February 2021.\r\n", "general": { "identifier": "48", "url_type": "URI", "url": "https://training.envri.eu/course/view.php?id=53", "title": "(\"en_US\",\"ENVRI WEEK 2021 - Training session\")", "language": [ "en" ], "description": "(\"en_US\",\"Presentations and course material from the ENVRI Week 2021 training session held online on 4 February 2021.\")", "keywords": [ "(\"en_US\",\"PIDs\")", "(\"en_US\",\"Persistent Identifiers\")", "(\"en_US\",\"GDPR\")", "(\"en_US\",\"ENVRI week\")", "(\"en_US\",\"PIDs for instruments\")", "(\"en_US\",\"General Data Protection Regulation\")" ], "geographical_availability": [ "(\"en_US\",\"2021\")" ] }, "life_cycle": { "version": "(\"en_US\",\"\tNot available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2021-02-04" }, "educational": { "interactivity_type": "Expositive", "access_rights": "ENVRI-FAIR project Work Package 6 Core Team", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"Not available\")", "learning_resource_type": "Webinar", "interactivity_level": "High", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "PT40" }, "technical": { "size": "Not available", "topic_codes": [ "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "R11: PID allocation & use (including citation support, bibliometry, provenance)" ] } }, "lo_o-1EDuQiPM": { "external_id": "o-1EDuQiPM", "code": "49", "title": "Training Provenance Tracing in ENVRI Research Infrastructures", "subtitle": "", "description": "Using the very relevant outcomes of the ENVRIplus project as written down in Deliverable D8.5 (Data provenance and tracing for environmental sciences: system design), we have put together a series of events all focussing on this topic:\r\n\r\nAn introductory webinar addressing the basic theoretical background:\r\n\r\n- What is provenance\r\n\r\n- Why is it important\r\n\r\n- What does provenance relate to\r\n\r\n- How is provenance recorded\r\n\r\n- Recording methods\r\n\r\n- Provenance and FAIRness;\r\n\r\nThree technical demonstrators of provenance tracing:\r\n\r\nThe PROV Template approach – Doron Goldfarb\r\n\r\nThe ENVRI-FAIR demonstrator focusing on provenance, and modeling a specific data production/processing workflow used at NILU – Markus Stocker\r\n\r\nThe EPOS Approach using the main catalogue – Keith Jeffery, Daniele Bailo;\r\n\r\nA workshop-type session in collaboration with WP7 to discuss cases, issues, problems and questions collected from the community, working towards practical support and -possibly- solutions.\r\n\r\nDuring the technical demonstrator sessions, we aim to collect input for the final workshop, like concrete cases, questions, requests for help on specific issues from the ENV RI’s.\r\n", "general": { "identifier": "49", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=47", "title": "(\"en_US\",\"Training Provenance Tracing in ENVRI Research Infrastructures\")", "language": [ "en" ], "description": "(\"en_US\",\"From an inventory among the various subdomain work packages in ENVRI-FAIR, WP6 concluded that Provenance Tracing was high on the priority list of training requirements for RI’s. Using the very relevant outcomes of the ENVRIplus project as written down in Deliverable D8.5 (Data provenance and tracing for environmental sciences: system design), we have put together a series of events all focussing on this topic: An introductory webinar addressing the basic theoretical background: What is provenance Why is it important What does provenance relate to How is provenance recorded Recording methods Provenance and FAIRness; Three technical demonstrators of provenance tracing: The PROV Template approach – Doron Goldfarb The ENVRI-FAIR demonstrator focusing on provenance, and modeling a specific data production/processing workflow used at NILU – Markus Stocker The EPOS Approach using the main catalogue – Keith Jeffery, Daniele Bailo; A workshop-type session in collaboration with WP7 to discuss cases, issues, problems and questions collected from the community, working towards practical support and -possibly- solutions. During the technical demonstrator sessions, we aim to collect input for the final workshop, like concrete cases, questions, requests for help on specific issues from the ENV RI’s.\")", "keywords": [ "(\"en_US\",\"Provenance Tracing, ENVRI\")", "(\"en_US\",\"learningpath02\")" ], "geographical_availability": [ "(\"en_US\",\"2020\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2020" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR project Work Package 6 Core Team", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR project Work Package 6 Core Team\")", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "R13: Provenance tracing" ] } }, "lo_Rxyfvr50z2": { "external_id": "Rxyfvr50z2", "code": "51", "title": "ENVRI-FAIR International School 2021", "subtitle": "Services for FAIRness", "description": "Organised by ENVRI-FAIR and LifeWatch ERIC, the school is at its fourth edition, having established itself as an unmissable opportunity to learn about FAIRness in the framework of Research Infrastructures. Having gone into depth on data FAIRness and data management during previous editions, this year the school will focus on Services for FAIRness, from their design to their development and publication.\r\nThe School is organised over a two-week period, on average dedicating around 50 hours in total (including preparations and self-study). It is structured around daily activities, with scheduled lectures and presentations in the mornings (09-13), followed by associated group and individual work time.\r\n", "general": { "identifier": "51", "url_type": "URL", "url": "https://training.envri.eu/enrol/index.php?id=54", "title": "(\"en_US\",\"ENVRI FAIR International School 2021 Services for FAIRness\")", "language": [ "en" ], "description": "(\"en_US\",\"Organised by ENVRI-FAIR and LifeWatch ERIC, the school is at its fourth edition, having established itself as an unmissable opportunity to learn about FAIRness in the framework of Research Infrastructures. Having gone into depth on data FAIRness and data management during previous editions, this year the school will focus on Services for FAIRness, from their design to their development and publication. The School is organised over a two-week period, on average dedicating around 50 hours in total (including preparations and self-study). It is structured around daily activities, with scheduled lectures and presentations in the mornings (09-13), followed by associated group and individual work time.\")", "keywords": [ "(\"en_US\",\"International School\")", "(\"en_US\",\"ENVRI\")", "(\"en_US\",\"Web Services\")", "(\"en_US\",\"FAIRNESS\")" ], "geographical_availability": [ "(\"en_US\",\"2021\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "September-October 2021" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR project Work Package 6 Core Team", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR project Work Package 6 Core Team\")", "learning_resource_type": "Lecture", "interactivity_level": "High", "semantic_density": "High", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "G1: Introduction to FAIR principles", "G5: Basic Research Data Management (RDM)", "G6: Writing technical documentation for services", "R2: API (Application Program Interface) design for data & metadata access", "R3: Cataloguing - design & implementation", "R16: Workflow engines for automated data processing" ] } }, "lo_C7DlBMDbD-": { "external_id": "C7DlBMDbD-", "code": "52", "title": "ENVRI-FAIR policy workshop for the ENVRI community Research Infrastructures", "subtitle": "", "description": "Speakers:\r\n\r\nAri Asmi (U. Helsinki)\r\n\r\nKeith G Jeffery (BGS/UKRI)\r\n\r\n \r\n\r\nProgramme:\r\n\r\n- Introduction to the Workshop\r\n\r\n     - Why this is relevant and to whom?\r\n\r\n     - Goals of the workshop\r\n\r\n     - Future of the policy work in ENVRI (FAIR)\r\n\r\n- Some examples of policy work in the EPOS ERIC\r\n\r\n- Introduction to group work\r\n\r\n    - Group work on policies\r\n\r\n- Returning together and discussion\r\n", "general": { "identifier": "52", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=55", "title": "(\"en_US\",\"1st ENVRI-FAIR policy workshop for the ENVRI community Research Infrastructures\")", "language": [ "en" ], "description": "(\"en_US\",\"Speakers: Ari Asmi (U. Helsinki) Keith G Jeffery (BGS/UKRI) Programme: Introduction to the Workshop Why this is relevant and to whom? Goals of the workshop Future of the policy work in ENVRI (FAIR) Some examples of policy work in the EPOS ERIC Introduction to group work Group work on policies Returning together and discussion\")", "keywords": [ "(\"en_US\",\"Policy\")", "(\"en_US\",\"ENVRI FAIR\")", "(\"en_US\",\"Interoperability\")", "(\"en_US\",\"learningpath03\")" ], "geographical_availability": [ "(\"en_US\",\"2021\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "24th September 2021" }, "educational": { "interactivity_type": "Expositive", "access_rights": "ENVRI-FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR \")", "learning_resource_type": "Lecture", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Other", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "R6: Data Management Plans", "R8: Licenses & policies for data use" ] } }, "lo_haS1J1qcUl": { "external_id": "haS1J1qcUl", "code": "54", "title": "FAIR Implementation Profile Workshop", "subtitle": "FIP workshop", "description": "During this series of workshops the experts provide an overview of the variety of options and technologies that are available to address each of the FAIR principles. Then, using state of the art tools, they assist us in producing a set of machine-readable FAIR Implementation Profiles that support and inform FAIRification efforts both within, as well as between, ENVRI subdomain communities.\r\n", "general": { "identifier": "54", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=56", "title": "(\"en_US\",\"FAIR Implementation Profile Workshop\")", "language": [ "en" ], "description": "(\"en_US\",\"During this series of workshops the experts provide an overview of the variety of options and technologies that are available to address each of the FAIR principles. Then, using state of the art tools, they assist us in producing a set of machine-readable FAIR Implementation Profiles that support and inform FAIRification efforts both within, as well as between, ENVRI subdomain communities.\")", "keywords": [ "(\"en_US\",\"FAIR Implementation Profiles\")", "(\"en_US\",\"FIP\")", "(\"en_US\",\"FAIR principles\")", "(\"en_US\",\"learningpath02\")" ], "geographical_availability": [ "(\"en_US\",\"2022\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2022" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR\")", "learning_resource_type": "Webinar", "interactivity_level": "High", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Other", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "R3: Cataloguing - design & implementation", "R10: Metadata standards & schemas (including geospatial, instruments, variables)", "R16: Workflow engines for automated data processing" ] } }, "lo_qh2XjmZ9Vi": { "external_id": "qh2XjmZ9Vi", "code": "55", "title": "ENVRI-FAIR 2nd policy workshop for the ENVRI community Research Infrastructures", "subtitle": "2nd policy workshop", "description": "This 2nd ENVRI policy workshop concentrates on the newly created ENVRI Policy Framework. It looks at some of the key policy drivers relevant to ENVRI data service providers – originating in the EOSC Rules of Participation, the FAIR Principles and developments such as the ENVRI-Hub – and derives requirements and best practises for ENVRI RIs policies needed to be compliant with these. \r\n", "general": { "identifier": "55", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=57", "title": "(\"en_US\",\"ENVRI-FAIR 2nd policy workshop for the ENVRI community Research Infrastructures\")", "language": [ "en" ], "description": "(\"en_US\",\"This 2nd ENVRI policy workshop concentrates on the newly created ENVRI Policy Framework. It looks at some of the key policy drivers relevant to ENVRI data service providers – originating in the EOSC Rules of Participation, the FAIR Principles and developments such as the ENVRI-Hub – and derives requirements and best practises for ENVRI RIs policies needed to be compliant with these. \")", "keywords": [ "(\"en_US\",\"Policy workshop\")", "(\"en_US\",\"ENVRI community Research Infrastructures\")", "(\"en_US\",\"FAIR\")", "(\"en_US\",\"learningpath03\")" ], "geographical_availability": [ "(\"en_US\",\"2022\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2022" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR \")", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Other", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "R6: Data Management Plans", "R8: Licenses & policies for data use" ] } }, "lo_xzD5PkDdzu": { "external_id": "xzD5PkDdzu", "code": "56", "title": "I-Adopt Framework Workshop", "subtitle": " ", "description": "The RDA I-ADOPT framework offers a way to compile clear and unambiguous definitions of variables in a standardised way. It helps you to describe concepts at different levels, ranging from overarching classes (“soil composition”) down to the very detailed (“soil water content, measured in a mineral soil matrix below root depth”).  You can create and register your own definitions, or reuse those of others, and once in place use them to tag your RI’s datasets.The formalized descriptions empower FAIR in many ways, for example by facilitating searches across data portals (F+A) and enabling machine-driven interpretation and use of data and metadata (I+R).\r\n", "general": { "identifier": "56", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=58", "title": "(\"en_US\",\"I-Adopt Framework Workshop\")", "language": [ "en" ], "description": "(\"en_US\",\"The RDA I-ADOPT framework offers a way to compile clear and unambiguous definitions of variables in a standardised way. It helps you to describe concepts at different levels, ranging from overarching classes (“soil composition”) down to the very detailed (“soil water content, measured in a mineral soil matrix below root depth”). You can create and register your own definitions, or reuse those of others, and once in place use them to tag your RI’s datasets.The formalized descriptions empower FAIR in many ways, for example by facilitating searches across data portals (F+A) and enabling machine-driven interpretation and use of data and metadata (I+R).\")", "keywords": [ "(\"en_US\",\"framework\")", "(\"en_US\",\"ENVRI FAIR\")", "(\"en_US\",\"ontology\")", "(\"en_US\",\"learningpath02\")" ], "geographical_availability": [ "(\"en_US\",\"2022\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2022" }, "educational": { "interactivity_type": "Active", "access_rights": "ENVRI-FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR \")", "learning_resource_type": "Video", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "G5: Basic Research Data Management (RDM)", "R3: Cataloguing - design & implementation", "R4: Certification schemes for repositories (CoreTrustSeal)", "R10: Metadata standards & schemas (including geospatial, instruments, variables)" ] } }, "lo_ejWrV71JUX": { "external_id": "ejWrV71JUX", "code": "57", "title": "Webinars on Designing and Developing Data Services for End Users", "subtitle": "", "description": "Two webinars on “Designing and Developing Data Services for End Users” organized in preparation for the ENVRI Community International Summer School 2022 "Road to a FAIR ENVRI-Hub: Designing and Developing Data Services for End Users”.\r\n\r\nThe workshops, aimed at IT architects, Research Infrastructure (RI) service developers and user support staff, and RI staff working on user interaction and community/network building, can also be taken as stand-alone sessions.\r\n", "general": { "identifier": "57", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=60", "title": "(\"en_US\",\"Webinars on Designing and Developing Data Services for End Users\")", "language": [ "en" ], "description": "(\"en_US\",\"Two webinars on “Designing and Developing Data Services for End Users” organized in preparation for the ENVRI Community International Summer School 2022 Road to a FAIR ENVRI-Hub: Designing and Developing Data Services for End Users”. The webinars, aimed at IT architects, Research Infrastructure (RI) service developers and user support staff, and RI staff working on user interaction and community/network building, can also be taken as stand-alone sessions.\")", "keywords": [ "(\"en_US\",\"data services\")", "(\"en_US\",\"web services\")", "(\"en_US\",\"ENVRI FAIR\")" ], "geographical_availability": [ "(\"en_US\",\"2022\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "2022" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR \")", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Training", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "G3: Performing a FAIRness self-assessment", "G6: Writing technical documentation for services" ] } }, "lo_lw5ZVYuM11": { "external_id": "lw5ZVYuM11", "code": "58", "title": "ENVRI Community Summer School 2022: Road to a FAIR ENVRI-Hub: Designing and Developing Data Services for End Users", "subtitle": "", "description": "The Summer School, now at its fifth edition, is organised by ENVRI-FAIR and LifeWatch ERIC and will take place in Lecce, Italy, from 10–15 July. It covers topics such as user interfaces, packaging of services, reusability and validation of services, and building and supporting networks through the lens of the ENVRI-Hub approach.\r\n", "general": { "identifier": "58", "url_type": "URL", "url": "https://training.envri.eu/enrol/index.php?id=61", "title": "(\"en_US\",\"ENVRI Community Summer School 2022: Road to a FAIR ENVRI-Hub: Designing and Developing Data Services for End Users\")", "language": [ "en" ], "description": "(\"en_US\",\"The Summer School, now at its fifth edition, is organised by ENVRI-FAIR and LifeWatch ERIC and will take place in Lecce, Italy, from 10–15 July. It covers topics such as user interfaces, packaging of services, reusability and validation of services, and building and supporting networks through the lens of the ENVRI-Hub approach.\")", "keywords": [ "(\"en_US\",\"ENVRI-Hub\")", "(\"en_US\",\"ENVRI-FAIR\")", "(\"en_US\",\"Data services\")", "(\"en_US\",\"Validation\")", "(\"en_US\",\"Interoperability\")", "(\"en_US\",\"Reusability\")", "(\"en_US\",\"learningpath03\")" ], "geographical_availability": [ "(\"en_US\",\"2022\")" ] }, "life_cycle": { "version": "(\"en_US\",\"Not available\")", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR and LifeWatch ERIC" ] }, "date": "July 2022" }, "educational": { "interactivity_type": "Mixed", "access_rights": "ENVRI-FAIR project Work Package 6 Core Team", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "(\"en_US\",\"ENVRI-FAIR project Work Package 6 Core Team\")", "learning_resource_type": "Lecture", "interactivity_level": "High", "semantic_density": "Medium", "target_group": [ "Learner" ], "context": "Higher education", "expertise_level": "Medium", "typical_learning_time": "Knowledge-dependent " }, "technical": { "size": "Not Available", "topic_codes": [ "G6: Writing technical documentation for services", "R2: API (Application Program Interface) design for data & metadata access" ] } }, "lo_EWMMvqHez7": { "external_id": "EWMMvqHez7", "code": "63", "title": "ENVRI-FAIR 3rd Policy Workshop for the ENVRI community Research Infrastructures", "subtitle": "3rd policy workshop", "description": "This 3rd ENVRI policy workshop, based on the work done by the Policy Group within EPOS which is used as an example, focuses on concentrates on creating policies from policy statements and creating guidelines and on their IT implementation. In doing so, it discusses the three key documents related to policy, taking into account the deficiencies discovered in analysis of the Policy framework and its policy statements, and incorporating those aspects of policy.\r\n", "general": { "identifier": "63", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=62", "title": "(\"en_US\",\"ENVRI-FAIR 3rd Policy Workshop for the ENVRI community Research Infrastructures\")", "language": [ "en" ], "description": "(\"en_US\",\"This 3rd ENVRI policy workshop, based on the work done by the Policy Group within EPOS which is used as an example, focuses on concentrates on creating policies from policy statements and creating guidelines and on their IT implementation. In doing so, it discusses the three key documents related to policy, taking into account the deficiencies discovered in analysis of the Policy framework and its policy statements, and incorporating those aspects of policy.\")", "keywords": [ "(\"en_US\",\"Policy workshop\")", "(\"en_US\",\"ENVRI community Research Infrastructures\")", "(\"en_US\",\"FAIR\")", "(\"en_US\",\"learningpath03\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not available", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2022" }, "educational": { "interactivity_type": "Mixed", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "ENVRI-FAIR", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Research Infrastructure" ], "context": "Other", "expertise_level": "Intermediate", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not available", "topic_codes": [ "R6: Data Management Plans", "R8: Licenses & policies for data use" ] } }, "lo_uGlUDUciOa": { "external_id": "uGlUDUciOa", "code": "64", "title": "ENVRI-FAIR 4th Policy Workshop for the ENVRI community Research Infrastructures", "subtitle": "4th policy workshop", "description": "This 4th ENVRI policy workshop, held during the ENVRIWeek 2023, focuses on the definition of the policy target for ENVRI RIs and ENVRI-Hub. It examines the progress made in ENVRI on policies, through a overview on the process to create policies and guidelines, and establishes a roadmap and integrated plan for policy in ENVRI. In this sense, the workshop also discussed the need for the three key policies (personal data privacy, terms and conditions, cookies) to be implemented in the ENVRI-Hub. \r\n", "general": { "identifier": "64", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=63", "title": "(\"en_US\",\"ENVRI-FAIR 4th Policy Workshop for the ENVRI community Research Infrastructures\")", "language": [ "en" ], "description": "(\"en_US\",\"This 4th ENVRI policy workshop, held during the ENVRIWeek 2023, focuses on the definition of the policy target for ENVRI RIs and ENVRI-Hub. It examines the progress made in ENVRI on policies, through a overview on the process to create policies and guidelines, and establishes a roadmap and integrated plan for policy in ENVRI. In this sense, the workshop also discussed the need for the three key policies (personal data privacy, terms and conditions, cookies) to be implemented in the ENVRI-Hub. \")", "keywords": [ "(\"en_US\",\"Policy workshop\")", "(\"en_US\",\"ENVRI community Research Infrastructures\")", "(\"en_US\",\"FAIR\")", "(\"en_US\",\"learningpath03\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not Available", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-FAIR" ] }, "date": "2023" }, "educational": { "interactivity_type": "Mixed", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "ENVRI-FAIR", "learning_resource_type": "Slide", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Research Infrastructure" ], "context": "Other", "expertise_level": "Intermediate", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not Available", "topic_codes": [ "R6: Data Management Plans", "R8: Licenses & policies for data use" ] } }, "lo_bvlk-6r6LC": { "external_id": "bvlk-6r6LC", "code": "65", "title": "How FAIRsharing can help FAIRify your standards, databases and data policies", "subtitle": "FAIRsharing", "description": "A workshop on how to make research data compliant with the FAIR principles organized by the ENVRI-FAIR project’s work package on training & skills building delivered by Peter McQuilton from FAIRsharing.org. FAIRsharing is a manually curated online registry of repositories and knowledgebases, linked to the models, formats, reporting guidelines, identifier schemata, and terminologies that they use, and the data policies from funders and journal publishers that endorse or recommend their use. This webinar discusses how you can use FAIRsharing to make your resource more Findable, Accessible, Interoperable and Re-usable.\r\n", "general": { "identifier": "65", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=64", "title": "(\"en_US\",\"How FAIRsharing can help FAIRify your standards, databases and data policies\")", "language": [ "en" ], "description": "(\"en_US\",\"A webinar on how to make research data compliant with the FAIR principles organized by the ENVRI-FAIR project’s work package on training & skills building delivered by Peter McQuilton from FAIRsharing.org. FAIRsharing is a manually curated online registry of repositories and knowledgebases, linked to the models, formats, reporting guidelines, identifier schemata, and terminologies that they use, and the data policies from funders and journal publishers that endorse or recommend their use. This webinar discusses how you can use FAIRsharing to make your resource more Findable, Accessible, Interoperable and Re-usable.\")", "keywords": [ "(\"en_US\",\"ENVRI FAIR\")", "(\"en_US\",\"FAIR principles\")", "(\"en_US\",\"FAIR standards\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not Available", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI FAIR" ] }, "date": "2019" }, "educational": { "interactivity_type": "Mixed", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "ENVRI-FAIR", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Researchers", "Research projects", "Research organisations", "Research Infrastructure", "Publishers", "Other" ], "context": "Training", "expertise_level": "Intermediate", "typical_learning_time": "Knowledge-dependent" }, "technical": { "size": "Not Available", "topic_codes": [ "G1: Introduction to FAIR principles", "G2: Metrics for FAIRness evaluation", "G5: Basic Research Data Management (RDM)", "G7: Other general FAIR-related topics" ] } }, "lo_OMA120j-NQ": { "external_id": "OMA120j-NQ", "code": "66", "title": "Writing effective service descriptions (for EOSC)", "subtitle": "", "description": "ENVRI-FAIR-dedicated training workshop on how to write useful service descriptions for inclusion in catalogues like the EOSC Marketplace and the ENVRI Catalogue of Services. The contents were based on materials developed for EOSC Future’s "training for service providers” programme.\r\n\r\nThe workshop gives an overview of documentation types, and discusses some strategies for creating sustainable and effective service descriptions. Then a practical hands-on exercises focuses on how to prepare service descriptions following the requirements of the EOSC service onboarding protocol.\r\n", "general": { "identifier": "66", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=66", "title": "(\"en_US\",\"Writing effective service descriptions (for EOSC)\")", "language": [ "en" ], "description": "(\"en_US\",\"ENVRI-FAIR-dedicated training workshop on how to write useful service descriptions for inclusion in catalogues like the EOSC Marketplace and the ENVRI Catalogue of Services. The contents were based on materials developed for EOSC Future’s “training for service providers” programme. The workshop gives an overview of documentation types, and discusses some strategies for creating sustainable and effective service descriptions. Then a practical hands-on exercises focuses on how to prepare service descriptions following the requirements of the EOSC service onboarding protocol.\")", "keywords": [ "(\"en_US\",\"ENVRI FAIR\")", "(\"en_US\",\"documentation\")", "(\"en_US\",\"EOSC\")", "(\"en_US\",\"service documentation\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not Available", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI FAIR" ] }, "date": "2023" }, "educational": { "interactivity_type": "Mixed", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "ENVRI-FAIR", "learning_resource_type": "Other", "interactivity_level": "Medium", "semantic_density": "Low", "target_group": [ "Research projects", "Research organisations", "Providers", "Research Infrastructure" ], "context": "Training", "expertise_level": "Intermediate", "typical_learning_time": "knowledge-dependent" }, "technical": { "size": "not Available", "topic_codes": [ "G6: Writing technical documentation for services" ] } }, "lo_TmEKnm8FT9": { "external_id": "TmEKnm8FT9", "code": "67", "title": "Requirements Elicitation - Identify and address end users expectations", "subtitle": "", "description": "The FAIR Service LifeCycle starts with Requirements Elicitation. As a first, foundational, phase, Requirements Elicitation is crucially important in the design and development of any new application. Poor or wrong decisions during the elicitation phase lead to critical failures of the systems. At the same time, it is basically impossible to identify appropriate requirements and address the users’ needs without the help of elicitation techniques and processes. The most common challenge for analysts during the elicitation process is ensuring an effective communication between themselves and the users. Indeed, system errors and failures frequently originate from poor communication between users and analysts.\r\n\r\nA 90-minute interactive training session (workshop) will focus on presenting the main elicitation techniques, examining their implementation in the design and development of FAIR services, and discussing main challenges and lessons learned.\r\n", "general": { "identifier": "67", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=67", "title": "(\"en_US\",\"Requirements Elicitation - Identify and address end users expectations\")", "language": [ "en" ], "description": "(\"en_US\",\"The FAIR Service LifeCycle starts with Requirements Elicitation. As a first, foundational, phase, Requirements Elicitation is crucially important in the design and development of any new application. Poor or wrong decisions during the elicitation phase lead to critical failures of the systems. At the same time, it is basically impossible to identify appropriate requirements and address the users’ needs without the help of elicitation techniques and processes. The most common challenge for analysts during the elicitation process is ensuring an effective communication between themselves and the users. Indeed, system errors and failures frequently originate from poor communication between users and analysts. A 90-minute interactive training session (workshop) will focus on presenting the main elicitation techniques, examining their implementation in the design and development of FAIR services, and discussing main challenges and lessons learned.\")", "keywords": [ "(\"en_US\",\"LifeCycle\")", "(\"en_US\",\"requirements elicitation\")", "(\"en_US\",\"ENVRI FAIR\")", "(\"en_US\",\"ENVRI Week\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not Available", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI FAIR" ] }, "date": "2023" }, "educational": { "interactivity_type": "Mixed", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "Yes", "conditions_of_use": "ENVRI FAIR", "learning_resource_type": "Slide", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Research projects", "Research organisations", "Research Infrastructure", "Other" ], "context": "Training", "expertise_level": "Intermediate", "typical_learning_time": "knowledge-dependent" }, "technical": { "size": "Not Available", "topic_codes": [ "G7: Other general FAIR-related topics", "R2: API (Application Program Interface) design for data & metadata access", "R3: Cataloguing - design & implementation", "R12: Portal design & operation" ] } }, "lo_oKYtvnE_mq": { "external_id": "oKYtvnE_mq", "code": "", "title": "GDPR Compliance in ENVRI-Hub NEXT: A Practical Guide", "subtitle": "", "description": "As the ENVRI-Hub NEXT continues to evolve as a central access point for environmental data and services provided by the ENVRI Community, ensuring best practices in data protection and transparency becomes essential. This webinar walks you through the principles, structure, and practical implications of the ENVRI-Hub privacy policy, and shows you how it supports both legal compliance and user trust.\r\n", "general": { "identifier": "68", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=73", "title": "(\"en_US\",\"GDPR Compliance in ENVRI-Hub NEXT: A Practical Guide\")", "language": [ "en" ], "description": "As the ENVRI-Hub NEXT continues to evolve as a central access point for data and services, ensuring the protection of data and maintaining transparency are essential. This webinar walks you through the principles, structure, and practical implications of the ENVRI-Hub privacy policy, and shows you how it supports both legal compliance and user trust.", "keywords": [ "(\"en_US\",\"GDPR compliance\")", "(\"en_US\",\"privacy policy\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not available", "status": "Final", "contribute": { "role": "Content provider", "entity": [ "ENVRI-Hub NEXT", "Yin Chen" ] }, "date": "2025-09-23" }, "educational": { "interactivity_type": "Expositive", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "Not available", "learning_resource_type": "Webinar", "interactivity_level": "Low", "semantic_density": "Medium", "target_group": [ "Research projects" ], "context": "Training", "expertise_level": "Intermediate", "typical_learning_time": "1H", "learning_outcomes": [ "Define overall scope and foundational principles of the EU’s General Data Protection Regulation (GDPR)", "Identify GDPR requirements for a Horizon Europe project", "Review the GDPR compliance checklist in the context of ENVRI-Hub NEXT, including roles, responsibilities, and processes for privacy policy and agreements management" ] }, "technical": { "size": "Not available", "scientific_domain_and_subdomain": "Social Sciences - Law", "topic_codes": [ "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "G5: Basic Research Data Management (RDM)", "R6: Data Management Plans", "R8: Licenses & policies for data use" ] } }, "lo_1KOqvxMZC9": { "external_id": "1KOqvxMZC9", "code": "", "title": "Ethical Challenges in the ENVRI-Hub design", "subtitle": "AI, Data Stewardship and User Rights", "description": "This ENVRI-Hub NEXT webinar was organised to deepen the understanding of the ethical responsibilities that come with developing, maintaining, and using an environmental research hub. In this training session, external ethics experts guide you on how to manage data responsibly, apply ethical research practices, engage with stakeholders meaningfully, and develop trustworthy AI tools. Workshop\r\n", "general": { "identifier": "70", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=72", "title": "(\"en_US\",\"Ethical Challenges in the ENVRI-Hub design\")", "language": [ "en" ], "description": "This ENVRI-Hub NEXT webinar was organised to deepen the understanding of the ethical responsibilities that come with developing, maintaining, and using an environmental research hub. In this training session, external ethics experts guide you on how to manage data responsibly, apply ethical research practices, engage with stakeholders meaningfully, and develop trustworthy AI tools.", "keywords": [ "(\"en_US\",\"open science\")", "(\"en_US\",\"ethics framework\")", "(\"en_US\",\"user data\")", "(\"en_US\",\"ethics by design\")", "(\"en_US\",\"ethics of use\")", "(\"en_US\",\"legal governance\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Not available", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-Hub NEXT" ] }, "date": "2025-06-23" }, "educational": { "interactivity_type": "Expositive", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "CC BY-NC-SA 4.0", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Low", "target_group": [ "Researchers", "Research projects", "Research managers", "Research organisations" ], "context": "Training", "expertise_level": "Intermediate", "typical_learning_time": "1H30M", "learning_outcomes": [ "Define the ethical expectations for a Horizon Europe project in environmental research", "Identify the ethical challenges related to data collection, integration and reuse for environmental research infrastructures", "Discuss the concepts of Ethics by Design and Ethics of Use", "Develop a project governance framework covering both legal rules and broader bio-ethical principles " ] }, "technical": { "size": "Not available", "scientific_domain_and_subdomain": "Other - Other", "topic_codes": [ "G4: GDPR (General Data Protection Regulation) issues related to data sharing", "G7: Other general FAIR-related topics", "R6: Data Management Plans", "R8: Licenses & policies for data use" ] } }, "lo_o27TkmhYEL": { "external_id": "o27TkmhYEL", "code": "", "title": "Research Software Quality Assessment", "subtitle": "From local development to production environments", "description": "This joint training webinar was organised as part of the training activities of the EVERSE Network and the ENVRI-Hub NEXT project.\r\n\r\nThis hands-on training workshop provided developers with a practical approach to code quality assurance (QA), including: research software FAIRness and sustainability, containerisation, and security assessment of their applications, all integrated within GitLab CI pipelines.\r\n\r\nThe main goal was to equip developers with the tools and procedures needed to maintain code quality, build secure container images, and automate deployments efficiently from local development to production environments.\r\n", "general": { "identifier": "71", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=71", "title": "(\"en_US\",\"Research Software Quality Assessment\")", "language": [ "en" ], "description": "This joint training webinar was organised as part of the training activities of the EVERSE Network and the ENVRI-Hub NEXT project. This hands-on training workshop provided developers with a practical approach to code quality assurance (QA), including: research software FAIRness and sustainability, containerisation, and security assessment of their applications, all integrated within GitLab CI pipelines. The main goal was to equip developers with the tools and procedures needed to maintain code quality, build secure container images, and automate deployments efficiently from local development to production environments", "keywords": [ "(\"en_US\",\"CI/CD pipeline\")", "(\"en_US\",\"research software quality\")", "(\"en_US\",\"sonarqube\")", "(\"en_US\",\"GitLab\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Final", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-Hub NEXT", "EVERSE" ] }, "date": "2025-05-21" }, "educational": { "interactivity_type": "Active", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "CC BY-NC-SA 4.0", "learning_resource_type": "Other", "interactivity_level": "High", "semantic_density": "Medium", "target_group": [ "Other" ], "context": "Training", "expertise_level": "Advanced", "typical_learning_time": "1H", "learning_outcomes": [ "Compare good practices for code deployment, management, and monitoring.", "Use a preconfigured pipeline to assess your code", "Run a quality pipeline in your own environment" ] }, "technical": { "size": "n/a", "scientific_domain_and_subdomain": "Engineering & Technology - Other engineering and technology sciences", "topic_codes": [ "R5: Cloud computing (Virtual Machines & containers) for data processing", "R14: Repository design, operation & sustainability" ] } }, "lo_t79jhk3ZMe": { "external_id": "t79jhk3ZMe", "code": "", "title": "How to generate UI/UX requirements", "subtitle": "Do the right thing, do the thing right", "description": "The ENVRI-Hub development managed by the ENVRI-Hub NEXT consortium entails both evaluating and consolidating existing ENVRI-Hub demonstrators, while also, in parallel, generating user needs and establishing requirements for new ENVRI-Hub use cases, including their integration.\r\n\r\nThis training session introduces ENVRI-Hub developers and ENVRI-Hub service owners to the concept of user personas, the definition of generative and evaluative user research, and their different scope. In the second part of the training session, a workshop-style exercise provided participants with practical tips on how to run a user interview and collect actionable insights.\r\n", "general": { "identifier": "72", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=70", "title": "(\"en_US\",\"How to generate UI/UX requirements\")", "language": [ "en" ], "description": "The ENVRI-Hub development managed by the ENVRI-Hub NEXT consortium entails both evaluating and consolidating existing ENVRI-Hub demonstrators, while also, in parallel, generating user needs and establishing requirements for new ENVRI-Hub use cases, including their integration. This training session introduces ENVRI-Hub developers and ENVRI-Hub service owners to the concept of user personas, the definition of generative and evaluative user research, and their different scope. In the second part of the training session, a workshop-style exercise provided participants with practical tips on how to run a user interview and collect actionable insights.", "keywords": [ "(\"en_US\",\"user persona design\")", "(\"en_US\",\"UX\")", "(\"en_US\",\"UI\")", "(\"en_US\",\"elicitive user research\")", "(\"en_US\",\"user requirements\")", "(\"en_US\",\"generative user research\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Final", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-Hub NEXT" ] }, "date": "2024-12-09" }, "educational": { "interactivity_type": "Mixed", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "CC BY-NC-SA 4.0", "learning_resource_type": "Webinar", "interactivity_level": "Medium", "semantic_density": "Medium", "target_group": [ "Research projects", "Innovators" ], "context": "Training", "expertise_level": "Beginner", "typical_learning_time": "1H", "learning_outcomes": [ "Defining realistic personas for the ENVRI-Hub service user groups", "Listing expected outcomes from interaction with user groups", "Choosing most effective formats of interaction with user groups" ] }, "technical": { "size": "n/a", "scientific_domain_and_subdomain": "Social Sciences - Other social sciences", "topic_codes": [ "R3: Cataloguing - design & implementation", "R7: Landing page design", "R12: Portal design & operation", "R14: Repository design, operation & sustainability" ] } }, "lo_y3qdGVFmwP": { "external_id": "y3qdGVFmwP", "code": "", "title": "Jira for Cross-team Sprints in Research Projects ", "subtitle": "", "description": "The heterogeneity of the research community involved in the ENVRI-Hub development is reflected in the geographical distribution of ENVRI-Hub developers and in the diverse expertise across the consortium. The coordination of such different development workgroups requires continuous feedback and the support of collaborative work tools.The ENVRI-Hub NEXT consortium has therefore adopted a number of best practices from the Agile methodology, such as SCRUM, namely: 1) the usage of Jira, a ticketing system to track activities, issues, and requests; 2) the adoption Git, a distributed code versioning system; 3) the implementation of continuous integration, delivery, and deployment practices; and 4) the general adoption of brief and informal communication practices among workgroups.\r\n\r\nTo support such practices, this video tutorial introduces project partners to the use of Jira.\r\n", "general": { "identifier": "73", "url_type": "URL", "url": "https://training.envri.eu/course/view.php?id=69", "title": "(\"en_US\",\"Jira for Cross-team Sprints in Research Projects \")", "language": [ "en" ], "description": "The heterogeneity of the research community involved in the ENVRI-Hub development is reflected in the geographical distribution of ENVRI-Hub developers and in the diverse expertise across the consortium. The coordination of such different development workgroups requires continuous feedback and the support of collaborative work tools.The ENVRI-Hub NEXT consortium has therefore adopted a number of best practices from the Agile methodology, such as SCRUM, namely: 1) the usage of Jira, a ticketing system to track activities, issues, and requests; 2) the adoption Git, a distributed code versioning system; 3) the implementation of continuous integration, delivery, and deployment practices; and 4) the general adoption of brief and informal communication practices among workgroups. To support such practices, this video tutorial introduces project partners to the use of Jira.", "keywords": [ "(\"en_US\",\"SCRUM framework\")", "(\"en_US\",\"Jira\")", "(\"en_US\",\"ticketing system\")", "(\"en_US\",\"digital project management\")", "(\"en_US\",\"Agile methodology\")", "(\"en_US\",\"sprints\")" ], "geographical_availability": [ "WW" ] }, "life_cycle": { "version": "Final", "status": "Final", "contribute": { "role": "Author", "entity": [ "ENVRI-Hub NEXT" ] }, "date": "2024-10-16" }, "educational": { "interactivity_type": "Expositive", "access_rights": "Open access", "cost": "No", "copyright_and_other_restrictions": "No", "conditions_of_use": "CC BY-NC-SA 4.0", "learning_resource_type": "Video", "interactivity_level": "Medium", "semantic_density": "Low", "target_group": [ "Research projects", "Research organisations", "Businesses", "Research Infrastructure", "Managers" ], "context": "Training", "expertise_level": "Intermediate", "typical_learning_time": "1H", "learning_outcomes": [ "Explain Jira ticket types and their hierarchy", "Describe Jira ticket anatomy, including ticket attributes, description, and relations", "Plan a Jira ticket according to the Agile methodology and the SCRUM framework" ] }, "technical": { "size": "n/a", "scientific_domain_and_subdomain": "Generic - Generic", "topic_codes": [ "G6: Writing technical documentation for services" ] } } }