FAIR self-assessment tool

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

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.

In 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.

1 - General
1.1 - Identifier
23
1.2 - URL type
URI
1.3 - URL
https://ardc.edu.au/resources/working-with-data/fair-data/fair-self-assessment-tool/
1.4 - Title
FAIR self-assessment tool
1.5 - Language
en
1.6 - 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.")
1.7 - Keywords
fair data
data management
fair assessment
1.8 - Geographical availability
("en_US","Not available")
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
ARDC - Australian Research Data Commons
2.4 - Date
Not available
3 - Educational
3.1 - Interactivity type
Active
3.2 - Learning resource type
Questionnaire
3.3 - Interactivity level
Low
3.4 - Semantic density
Low
3.5 - Target group
Learner
3.6 - Context
Training
3.7 - Expertise level
Very easy
3.8 - Typical learning time
10M
3.9 - Learning outcome(s)
3.10 - Access rights
Copyright © 2020 ARDC. ACN 633 798 857.
3.11 - Cost
No
3.12 - Copyright and other restrictions
Yes
3.13 - Conditions of use
("en_US","Copyright © 2020 ARDC. ACN 633 798 857.")
4 - Technical
4.1 - Size
Not available
4.2 - Scientific domain and subdomain
4.3 - Topic codes
G1: Introduction to FAIR principles
G3: Performing a FAIRness self-assessment
5 - Relation
5.1 - Kind
5.2 - Entry
Access the resource

Details

Code23
Uploaded byLucia Vaira
Available since24/01/20 17:18

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