Best practices for creating reusable data publications

This catalogue respects all FAIR guidelines and best practices and use the IEEE Standard for Learning Object Metadata (IEEE 2002).

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.

1 - General
1.1 - Identifier
3
1.2 - Catalog
URL
1.3 - Entry
https://datadryad.org/stash/best_practices
1.4 - Title
Best practices for creating reusable data publications
1.5 - Language
en
1.6 - 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.
1.7 - Keywords
data research
data management
best practices
1.9 - Coverage
2019
2 - Life Cycle
2.1 - Version
Not available
2.2 - Status
Final
2.3 - Contribute
2.3.1 - Role
Author
2.3.2 - Entity
Dryad
2.4 - Date
2019
3 - Educational
3.1 - Interactivity type
Expositive
3.2 - Learning resource type
Narrative text
3.3 - Interactivity level
Low
3.4 - Semantic density
Low
3.5 - Intended end user role
Author
3.6 - Context
Training
3.7 - Difficulty
Easy
3.8 - Typical learning time
PT12M45S
3.9 - Rights
Copyright (c) 2019 Dryad
3.10 - Cost
No
3.11 - Copyright and other restrictions
Yes
3.12 - Conditions of use
Free use
4 - Technical
4.1 - Location
https://datadryad.org/stash/best_practices#organize
4.2 - Size
Not available
4.3 - 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
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Uploaded byLucia Vaira
Available since10/12/19 11:49

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