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Short description
FAIR (meta)data requires globally unique and persistent identifiers (principle F1). Such identifiers remove ambiguity in the meaning of your data by assigning a unique identifier to every element of metadata and every concept/measurement in your dataset [GOFAIR_F1]. In this context, an identifier consists of an internet link, such as a URL, which can be resolved. Identifiers can help both humans and computers interpreting your data.
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Furthermore, many specialised identifier services exist, which can help map from one identifier to another. BridgeDB, for example, is a framework to map identifiers between various biological databases and related resources [BRIDGEDB]. It provides mappings for genes, proteins, metabolites, metabolic reactions, diseases, complexes and publications.
Working Group
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This section could describe the expertise required. Perhaps the Build Your Team step could then be an aggregation of all the “Expertise requirements for this step” steps that someone needs to fulfil his/her FAIRification goals.
How to
FAIRPlus[FAIRInAction]: Select the identifier scheme
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Identifiers.org provides resolvable identifiers in the form of URIs and CURIEs: http://identifiers.org
Universally unique identifier: https://en.wikipedia.org/wiki/Universally_unique_identifier
Persistent URLs: http://www.purlz.org
Digital Object Identifier: http://www.doi.org
Archival Resource Key: https://escholarship.org/uc/item/9p9863nc
Research Resource Identifiers: https://scicrunch.org/resources
Identifiers for funding organisations (see F3 & R1): https://www.crossref.org/services/funder-registry/
Identifiers for the world’s research organisations (see F3 & R1): https://www.grid.ac
Practical Examples from the Community
This section should show the step applied in a real project. Links to demonstrator projects.
References & Further reading
[FAIRopoly] FAIRopoly https://www.ejprarediseases.org/fairopoly/
[Generic] A Generic Workflow for the Data FAIRification Process: https://direct.mit.edu/dint/article/2/1-2/56/9988/A-Generic-Workflow-for-the-Data-FAIRification
[Elixir] https://faircookbook.elixir-europe.org/content/recipes/introduction/fairification-process.html
[Elixir2] A framework for FAIRification processes: https://faircookbook.elixir-europe.org/content/recipes/introduction/metadata-fair.html
[GOFAIR] https://www.go-fair.org/fair-principles/f2-data-described-rich-metadata/
[RDMkit] https://rdmkit.elixir-europe.org/machine_actionability.html
[GOFAIR_F1] https://www.go-fair.org/fair-principles/f1-meta-data-assigned-globally-unique-persistent-identifiers/
[SSSOM] https://github.com/mapping-commons/sssom
[BRIDGEDB] https://www.bridgedb.org/
Authors / Contributors
Experts whom you can contact for further information
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Expertise requirements for this step
This section could describe the expertise required. Perhaps the Build Your Team step could then be an aggregation of all the “Expertise requirements for this step” steps that someone needs to fulfil his/her FAIRification goals.
Practical examples from the community
This section should show the step applied in a real project. Links to demonstrator projects.
Training
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