- PID: Permanent Identifier
- GUID: Globally Unique Identifier
- Search Index
- Access protocol
In 2016, the |FAIR Guiding Principles|_ for scientific data management and stewardship were published in Scientific Data. Read it. Its short.
- F1. (meta)data are assigned a globally unique and persistent identifier
- F2. data are described with rich metadata (defined by R1 below)
- F3. metadata clearly and explicitly include the identifier of the data it describes
- F4. (meta)data are registered or indexed in a searchable resource
- A1. (meta)data are retrievable by their identifier using a standardized communications protocol
- A1.1 the protocol is open, free, and universally implementable
- A1.2 the protocol allows for an authentication and authorization procedure, where necessary
- A2. metadata are accessible, even when the data are no longer available
- I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
- I2. (meta)data use vocabularies that follow FAIR principles
- I3. (meta)data include qualified references to other (meta)data
- R1. meta(data) are richly described with a plurality of accurate and relevant attributes
- R1.1. (meta)data are released with a clear and accessible data usage license
- R1.2. (meta)data are associated with detailed provenance
- R1.3. (meta)data meet domain-relevant community standard
The CARE principles for Indigenous Data Governance were drafted at the International Data Week and Research Data Alliance Plenary co-hosted event “Indigenous Data Sovereignty Principles for the Governance of Indigenous Data Workshop,” 8 November 2018, Gaborone, Botswana.
- Collective Benefit
- C1. For inclusive development and innovation
- C2. For improved governance and citizen engagement
- C3. For equitable outcomes
- Authority to Control
- A1. Recognizing rights and interests
- A2. Data for governance
- A3. Governance of data
- R1. For positive relationships
- R2. For expanding capability and capacity
- R3. For Indigenous languages and worldviews
- E1. For minimizing harm and maximizing benefit
- E2. For justice
- E3. For future use
FAIR - TLC¶
- Traceable, Licensed, and Connected
- The need for metrics: https://zenodo.org/record/203295#.XkrzTxNKjzI
Which do you think is the hardest, F, A, I, or R, and why?
What is the best way to cite data?
What are the relative values of a data publication verus a peer-reviewed paper?
What role do ontologies play in FAIR-TLC?