Fair by Design

Since 2016, the scientific data management principles — Findable, Accessibility, Interoperability, and Reusability (FAIR)—have been addressed at various scientific forums and have become a guideline for managing research data with machine actionability. The need to manage scientific data with minimal human intervention and rely on computational systems has become increasingly urgent. This underscores the importance of containerizing and centralizing research data objects and related artifacts. To this end, FAIR guiding principles as well as the five recommendations for FAIR software have become essential to improving the infrastructure that supports FAIR principles in designing research data and software magnet objects.

The FAIR principles serve as both a guide and a compass for the work within NFDIxCS. The RDMC architecture is designed to provide research data and software infrastructure and services, embedding FAIR principles as general requirements throughout the process.

Achieving and Realizing FAIR Principles through RDMC Components and Features

Findable

This principle addresses the role and properties of identifiers and metadata, which are part of a search infrastructure that identifies data and its related context. In the RDMC prototype version, metadata and data are structured to be findable for both humans and computers through unique and persistent identifiers. Data are described with rich metadata, and metadata explicitly include the identifiers of the data they describe. (Meta)data are indexed in a searchable resource.

Accessible

This principle focuses on how research data is stored and accessed through metadata and identifiers via a search infrastructure with well-defined authorization and authentication. In the RDMC prototype version, once users find the required data and artifacts, access may include authentication and authorization. Data are retrievable by their identifiers using standardized communication protocols. These protocols are open, free, and universally implementable, with authentication and authorization procedures where necessary.

Interoperable

This principle ensures that data and artifacts can be integrated with other related data and artifacts, and can interoperate with applications or workflows for analysis, storage, and processing. In the RDMC prototype version, interoperability is realized at all levels of the research data management architecture, which is open and shared among the broader community and is planned to be integrated into the general infrastructure of NFDI.

Reusable

This principle ensures that metadata and data are well-described to allow replication and combination in different settings. It focuses on how research data can be reused easily and openly. Attributes such as access licenses, provenance, and community standards are key considerations. In the RDMC prototype version, (meta)data are richly described with a plurality of accurate and relevant attributes. Data and artifacts are released with clear and accessible usage licenses, associated with detailed provenance, and aligned with domain-relevant community standards.