> For the complete documentation index, see [llms.txt](https://fairsharing.gitbook.io/fairsharing/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://fairsharing.gitbook.io/fairsharing/alignment-with-community-efforts.md). # Alignment with Community Efforts ## Alignment with FAIR The [FAIR Principles](https://doi.org/10.1038/sdata.2016.18) provide high-level guidance for making digital objects **Findable, Accessible, Interoperable and Reusable**. Although originally developed for research data and metadata, they are equally relevant to the standards, databases and policies that enable FAIR research. FAIRsharing contributes to FAIR in two complementary ways. As a curated registry, FAIRsharing implements many aspects of the FAIR Principles through its own metadata, services and technical infrastructure. FAIRsharing also helps standards, databases and policies become more FAIR-enabling by collecting structured metadata that supports their discovery, understanding and reuse. The sections below summarise both perspectives. Practical guidance on the characteristics currently used to describe FAIR-enabling databases is available in the [**FAIR-enabling databases**](/fairsharing/fair-assistance/fair-enabling-databases.md) section. Guidance for additional FAIRsharing record types will be added as equivalent characteristics are developed. Additionally, the [**FAIR support and definitions**](/fairsharing/fair-assistance/fair-support-and-definitions.md) describes FAIRsharing's interpretation of key FAIR concepts and terminology. ### Findable {% columns %} {% column %} **How FAIRsharing implements FAIR** FAIRsharing improves the discoverability of its own records through rich, structured metadata, persistent identifiers and machine-readable representations. Approved records are assigned DOIs, maintainers may be linked to their ORCID identifiers, organisations may be linked to [ROR](/fairsharing/record-sections-and-fields/organisations-and-grants/importing-ror-organisations.md), and FAIRsharing records are indexed by search engines using semantic markup including schema.org and Bioschemas. Users can discover resources through [free text search, faceted search, advanced search](/fairsharing/how-to/searching-and-browsing.md), subject browsing, collections and the FAIRsharing relation graph. *FAIRsharing assigns DOIs to all records within its three registries (standards, databases and data policies) according to this* [*DOI minting schedule*](https://fairsharing.gitbook.io/fairsharing/#getting-a-record-doi)*.* *We integrate with the* [*ORCID*](https://orcid.org/) *registry as a* [*trusted organisation*](https://blog.fairsharing.org/?p=191)*.* {% endcolumn %} {% column %} **How FAIRsharing enables FAIR** FAIRsharing encourages resource providers to describe their standards, databases and policies using rich metadata that supports discovery by both people and software. This includes information such as resource names, descriptions, homepages, subject classifications, identifiers and relationships among resources. Together, these metadata help researchers identify resources that are appropriate for their community and use case. *The current* [***FAIR-enabling databases***](/fairsharing/fair-assistance/fair-enabling-databases.md) *guidance provides the most detailed operationalisation of these concepts for database records, including characteristics relating to identifiers, descriptive metadata and discoverability.* {% endcolumn %} {% endcolumns %} ### Accessible {% columns %} {% column %} **How FAIRsharing implements FAIR** FAIRsharing records are accessible through standard web technologies via both the FAIRsharing website and programmatic interfaces. Metadata are exposed through the [FAIRsharing API](/fairsharing/programmatic-access/fairsharing-data-access.md) using open web protocols, and semantic markup supports machine access to record metadata. FAIRsharing maintains its metadata independently of the continued availability of the resources it describes, allowing records to remain informative even if a resource changes or is no longer available. {% endcolumn %} {% column %} **How FAIRsharing enables FAIR** FAIRsharing encourages resource providers to document how their resources can be accessed, including access conditions, programmatic interfaces, and documentation. Recording this information allows users to understand how a resource may be accessed and whether it meets their requirements. *The current* [***FAIR-enabling databases***](/fairsharing/fair-assistance/fair-enabling-databases.md) *guidance expands these concepts for database records by describing characteristics relating to repository access, computational interfaces, preservation and sustainability.* {% endcolumn %} {% endcolumns %} ### Interoperable {% columns %} {% column %} **How FAIRsharing implements FAIR** FAIRsharing promotes interoperability through the use of controlled vocabularies, persistent identifiers and structured relationships among records. Metadata are exposed in machine-readable formats, and records are linked to external resources such as identifier schemes, organisations and related standards, databases and policies. These relationships allow both users and software to navigate the wider research data ecosystem. *Subjects:* [*GitHub repository*](https://github.com/FAIRsharing/subject-ontology)*,* [*FAIRsharing subject browser*](https://fairsharing.org/browse/subject)*,*[ *OLS browser*](https://www.ebi.ac.uk/ols/ontologies/srao)*.*\ *Domains:* [*GitHub repository*](https://github.com/FAIRsharing/domain-ontology)\ *Object types:* [*FAIRsharing documentation*](/fairsharing/record-sections-and-fields/general-information/object-types.md)*,* [*GitHub repository*](https://github.com/OSTrails/digital-object-commons)\ *Taxonomy: based on NCBI Taxonomy, work is ongoing to align fully with their hierarchy.* *Our links to ROR and ORCID could also be considered relevant to this item as well as to F1.* {% endcolumn %} {% column %} **How FAIRsharing enables FAIR** FAIRsharing encourages resource providers to document the standards, terminologies, identifier schemes and other resources that support interoperability. Recording these relationships provides context for understanding how resources exchange information, adopt community practices and fit within the broader research landscape. *The current* [***FAIR-enabling databases***](/fairsharing/fair-assistance/fair-enabling-databases.md) *guidance provides detailed characteristics describing how database records capture interoperability through standards implementation, terminology use, identifier schemes and relationships with other resources.* {% endcolumn %} {% endcolumns %} ### Reusable {% columns %} {% column %} **How FAIRsharing implements FAIR** FAIRsharing supports reuse through rich contextual metadata describing each resource, including licensing, provenance, governance, community adoption and relationships with other resources. Every change made to a FAIRsharing record is preserved in a publicly accessible history, providing transparent provenance for the metadata describing each resource. FAIRsharing also aligns its metadata model with community recommendations and collaborates with initiatives such as the [RDA](https://www.rd-alliance.org/) to promote good practice. *FAIRsharing content is released under a* [*CC BY-SA 4.0*](http://creativecommons.org/licenses/by-sa/4.0/) *licence. Other licences may be used for source code.* {% endcolumn %} {% column %} **How FAIRsharing enables FAIR** FAIRsharing encourages resource providers to supply the contextual information needed for others to determine whether a resource is appropriate for reuse. This includes information relating to licences, provenance, governance, documentation, community adoption, support and sustainability, together with relationships to standards, databases and policies that provide additional context for the resource. *The current* [***FAIR-enabling databases***](/fairsharing/fair-assistance/fair-enabling-databases.md) *guidance describes the detailed characteristics currently used for database records.* {% endcolumn %} {% endcolumns %} ## How FAIRsharing aligns with TRUST This section provides a summary of how FAIRsharing itself, as a registry of standards, databases and policies, attributes align with the [TRUST Principles](https://doi.org/10.1038/s41597-020-0486-7), developed in collaboration with the [RDA/WDS Certification of Digital Repositories IG](https://www.rd-alliance.org/groups/rdawds-certification-digital-repositories-ig/activity/). Work on this alignment is ongoing, with iterative feedback from the [RDA/WDS TRUST Principles Outreach and Adoption WG](https://www.rd-alliance.org/groups/rdawds-trust-principles-outreach-and-adoption-working-group/activity/). For more information on TRUST: Lin, D., Crabtree, J., Dillo, I. *et al.* The TRUST Principles for digital repositories. *Sci Data* 7, 144 (2020). **Transparency**: *mission statement, scope, terms of use, and minimum digital preservation timeframe.* FAIRsharing's mission statement is available from its front page, and is the first thing a user sees when visiting the site. {% hint style="info" %} ## FAIRsharing is a curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies. Guides consumers to discover, select and use these resources with confidence.\ Helps producers to make their resources more visible, more widely adopted and cited.\ Provides humans and tools with access to trustworthy content to enable data management tasks. {% endhint %} **Responsibility**: *community-defined metadata and curation standards, including persistence and other stewardship provisions; data services including download and machine interfaces; and IP management and sensitive data security.* Our application ontologies, used to build our tagging systems and hierarchical searches, are drawn from 50+ community ontologies. We implement schema.org and provide JSON and JSON-LD metadata, and our records are given DOIs. Our [Community Champions Programme](/fairsharing/community-champions/thinking-of-joining-us.md) was initially modelled on the best practices for community development as outlined at [CSCCE](https://www.cscce.org/). We have a variety of [computational endpoints](https://fairsharing.org/licence) available. There is no sensitive data stored at FAIRsharing, so those considerations are not applicable. **Usability**: *Implementing and publishing relevant data metrics, providing community catalogues, and monitoring community expectations*. We have a variety of [statistics](https://fairsharing.org/summary-statistics) relating to the registry, and our stakeholders regularly use our content for landscape analyses, e.g. of the attributes of databases or policies across a region or resource type. We are very active within the research data community to ensure that our content always reflects the need of the community. Our [Community Champions ](/fairsharing/community-champions/thinking-of-joining-us.md)are also key to ensuring that our community of stakeholders have access to FAIRsharing and can easily influence and comment on updates to the registry.
**Sustainability**: *risk mitigation, continuity, funding, governance and long-term preservation*. FAIRsharing [Governance](https://fairsharing.org/communities#governance) involves the engagement of a Stakeholder Advisory Board from a variety of roles, geographical locations, and subject areas. Our [Sustainability and Preservation](https://fairsharing.org/sustainability_and_preservation) plans provide a robust plan for longevity and availability of our content. Our funding is ongoing from a variety of sources including OSTrails and TIER2. **Technology**: *standards and tools for data management and curation, and mechanisms for responding to cyber or physical security threats*. Our software and technical infrastructure is kept up to date by our technical team and through the support of University of Oxford. We utilise open source tools such as [Zulip](https://zulip.com/) for team discussions and development. ## Alignment with other community efforts ### Database Attributes A number of efforts are ongoing to provide a minimal set of database attributes for describing such resources, to aid database discovery and comparison. FAIRsharing strives to integrate with any such community effort, and details of any alignments between them and FAIRsharing database metadata are integrated into the descriptions of those fields throughout this documentation. In short, FAIRsharing metadata is aligned with both RDA and NIH repository attribution efforts. To keep it all in a single documented location, please visit our [Database Conditions](/fairsharing/additional-information/database-conditions.md) 'Alignment with Existing Efforts' subsection for full details of alignment with the output of this group. ### Policies and Data Management Plans {% hint style="success" %} The alignment file for the four resources (FAIRsharing, FAIR-enabling Data Policy Checklist, RDA Data policy IG output, and Concordat on Open Research Data) is available at: Lister, A., & Davidson, J. (2024). Alignment of FAIRsharing Policy Attributes with Community Efforts (1.0.0). Zenodo. {% endhint %} There are two recent efforts that have drawn upon the research community to produce a set of common metadata attributes for data policies with the goal of standardising what metadata is most relevant to the research community when evaluating and comparing data policies. * FAIRsFAIR: [FAIR-enabling Data Policy Checklist](https://doi.org/10.5281/zenodo.6225774) * RDA's Data policy standardisation and implementation Interest Group (IG): [Developing a Research Data Policy Framework for All Journals and Publishers](http://doi.org/10.5334/dsj-2020-005) Additionally, the a third community effort in the UK has created a concordat that ensures that the research data gathered and generated by members of the UK research community is made openly available for use by others wherever possible. * [Concordat on Open Research Data ](https://www.ukri.org/wp-content/uploads/2020/10/UKRI-020920-ConcordatonOpenResearchData.pdf) These three efforts are related, although they do not completely overlap in scope. In a collaboration with the UKRN and the DCC ([2024 news item](https://blog.fairsharing.org/?p=691), [2022 news item](https://dcc.ac.uk/blog/fairsharing-and-dcc-collaborate-align-policy-metadata)), we have ensured our policy metadata fields allow you to create machine-actionable data policy descriptions within FAIRsharing that align with these three outputs. More details of this are available within our [Policy Content and Scope](/fairsharing/additional-information/policy-content-and-scope.md) documentation. ### Tools utilising FAIRsharing A number of tools providing a wide range of services link to FAIRsharing's API, and a selection of these are listed in our [Adopters](https://fairsharing.org/communities#tools) page. If you would like your tool listed with us, please follow the instructions on that page. ### EOSC #### Identifier schemas Our identifier schema records are marked as globally unique, persistent and/or resolvable (GUPRIs); our definition is aligned with, but not identical to, the EOSC PID policy (A Persistent Identifier (PID) policy for the European Open Science Cloud (EOSC), Publications Office, 2020, ). More information is available in our [GUPRI information page](/fairsharing/record-sections-and-fields/general-information/globally-unique-persistent-and-resolvable-identifier-schemas.md). When manually curating our identifier schema records, we use both our curation expertise and the information provided by identifiers.org () and bioregistry (). to populate our regular expressions fields. The community can then use our API to identify which id schema(s) a particular identifier string belongs to. #### Terminology Artifacts Corcho et al have published paper describing '[A maturity model for catalogues of semantic artefacts](https://doi.org/10.1038/s41597-024-03185-4)'\[1], written by a group within the [EOSC Task Force on Semantic Interoperability](https://eosc.eu/advisory-groups/semantic-interoperability) and aimed at identifying those dimensions and features that might be used to assess the maturity of catalogues of semantic artefacts. This paper: > presents a *maturity model* for assessing catalogues of semantic artefacts, one of the keystones that permit semantic interoperability of systems. We defined the dimensions and related features to include in the maturity model by analysing the current literature and existing catalogues of semantic artefacts provided by experts. In addition, we assessed 26 different catalogues to demonstrate the effectiveness of the maturity model, which includes 12 different dimensions (Metadata, Openness, Quality, Availability, Statistics, PID, Governance, Community, Sustainability, Technology, Transparency, and Assessment) and 43 related features (or sub-criteria) associated with these dimensions. \[1] FAIRsharing is one of the 26 resources assessed, and has scored very highly according to the set of attributes of such catalogues that the authors deem important for maturity. Incorporating those modifications to the assessment as described below, and ignoring those features/attributes that are lower/equivalent in stringency (5/43) or out of scope for a registry like FAIRsharing (4/43), we **implement 31/34 maturity features as defined by the EOSC TF on Semantic Interoperability**. Details of our alignment with this EOSC TF maturity model are below available in a [google spreadsheet](https://docs.google.com/spreadsheets/d/1UGLseCK485-FcLKgorLSH4gneHHi6zt-wDzHbz8qn1Q/edit?usp=sharing).

A partial screenshot of the update on the assessment of FAIRsharing in the context of semantic artifacts by Corcho et al[1]. Full details at this spreadsheet.

FAIRsharing provides not only manually-curated records for standards, databases and policies, but also a rich graph of the connectivity among these resources, placing each record within the broader context of the research data landscape. When you visit FAIRsharing to register, compare or help discover resources such as terminologies, you are able to discover and describe both their features and their interconnectedness.

A graph of the standards, databases and policies that are related to the Gene Ontology record at https://doi.org/10.25504/FAIRsharing.6xq0ee.

Find out more at our [blog post](https://blog.fairsharing.org/?p=806) on this alignment work. \[1] Corcho, O., Ekaputra, F.J., Heibi, I. *et al.* A maturity model for catalogues of semantic artefacts. *Sci Data* 11, 479 (2024).