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FAIR and CARE Principles

FAIR and CARE Principles

FAIR and CARE principles are frameworks designed to enhance data management and sharing. FAIR focuses on technical standards, while CARE addresses ethical considerations. Both should be considered from the beginning of data collection.

See also the FORS-DaSCH Webinar on FAIR and CARE: Video, Slides.

FAIR Principles

FAIR stands for Findable, Accessible, Interoperable, and Reusable. These principles aim to improve interoperability and the ability to find, access, and use data effectively. Read more about FAIR here.

How DaSCH Supports FAIR Principles

  • Findable: DaSCH provides descriptive metadata and persistent identifiers (ARKs) at resource level. Researchers receive support in providing high-quality metadata including descriptive information, keywords, and tags to improve dataset findability.
  • Accessible: DaSCH offers a web application and a public API (DSP-API), making data accessible to both humans and machines. Guidance on open file format selection is provided.
  • Interoperable: DaSCH references ontologies and controlled vocabularies. The API is based on open standards to ensure data can be integrated and reused across different systems. Researchers receive support in using existing controlled vocabularies and mapping data models to relevant ontologies (e.g., CIDOC-CRM, dcterms) to ensure consistency and interoperability. Several thesauri are available, including those at the Getty Research Institute.
  • Reusable: DaSCH provides clear licensing information to ensure data can be reused and cited appropriately. Researchers receive guidance in choosing open licenses and providing clear documentation and provenance information, including how datasets were created, processed, and transformed.

CARE Principles

CARE stands for Collective Benefit, Authority to Control, Responsibility, and Ethics. These principles focus on ensuring data is managed in ways that respect the rights and interests of indigenous peoples and communities. The CARE principles can be applied more broadly to ensure ethical data practices. They serve as a source of inspiration, prompting reflection on ensuring the inclusion of individuals within data analysis and management contexts. Read more about CARE here.

Applying CARE Principles in Research

  • Identify the people behind the data: Who is directly concerned? Who may be affected? Who financed the project?
  • Address the geographical context: Where was the data collected? Where is the research project based?
  • Assess the potential benefits and harms: Could the data benefit a community or individuals? Could the data harm or shock individuals or communities, their beliefs, and their culture?
  • Record data provenance in the metadata.