Data and the FAIR Principles
This catalogue respects all FAIR guidelines and best practices. It is based on the IEEE Standard for Learning Object Metadata (IEEE 2002) that has been customised in order to be compliant with the EOSC Training Resource Profile - Data Model.
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.
1 - General
1.1 - Identifier
4
1.2 - URL type
URL
1.3 - URL
http://www.repronim.org/module-FAIR-data/
1.4 - Title
Data and the FAIR Principles
1.5 - Language
en
1.6 - 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.")
1.7 - Keywords
fair data
fair principles
fair principles
1.8 - Geographical availability
("en_US","2016")
2 - Life Cycle
2.1 - Version
("en_US","Not available")
2.2 - Status
Final
2.3 - Contribute
2.3.1 - Role
Author
2.3.2 - Entity
ReproNim
2.4 - Date
2016
3 - Educational
3.1 - Interactivity type
Expositive
3.2 - Learning resource type
Lecture
3.3 - Interactivity level
Low
3.4 - Semantic density
Medium
3.5 - Target group
Learner
3.6 - Context
Training
3.7 - Expertise level
Knowledge-dependent
3.8 - Typical learning time
Knowledge-dependent
3.9 - Learning outcome(s)
3.10 - Access rights
Copyright © 2016 Neurohackweek and ReproNim
3.11 - Cost
No
3.12 - Copyright and other restrictions
Yes
3.13 - 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.")
4 - Technical
4.1 - Size
Not available
4.2 - Scientific domain and subdomain
4.3 - 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
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
5 - Relation
5.1 - Kind
5.2 - Entry
Access the resource
Details
| Code | 4 |
|---|---|
| Uploaded by | Lucia Vaira |
| Available since | 10/12/19 12:14 |