To ensure that research data can be found and used efficiently, it must be associated with metadata. Metadata is information about the data, e.g., about the researchers who collected the data or about the license under which the data may be used. The section supports processes of the NFDI consortia in jointly developing and establishing common data and metadata standards as a foundation for effective reuse of research data in accordance with FAIR principles. In order to be able to link data from different sources in an interdisciplinary manner, semantic technologies (ontologies, knowledge graphs) are to be integrated in NFDI, which make it possible to generate knowledge and information in a machine-readable form. Uniform documentation procedures will make the creation and processing context (provenance) of data transparent. In the topic area of metadata and research data, the section addresses issues of (meta)data harmonization, discoverability of data, general data and metadata standards with a perspective on a possible NFDI core metadata format, as well as format conversions and persistent identifier systems. In the topic area of terminologies, the section will address cross-community and cross-disciplinary definitions of top-level ontologies and mappings of ontologies, as well as best practices for modeling terminologies, vocabularies, and ontologies, and data integration services based on them. In the area of provenance, the section will address legal, technical, and cultural aspects of the context of creation of (meta)data and design proposals for uniform and traceable documentation procedures to answer the questions of what, where, when, who, how, and why of data creation and data processing. The section will work in close cooperation with the sections “Common Infrastructures” and “Ethical, Social and Legal Aspects”, especially on the topics of terminologies and provenance.

Cookbooks, Guidance and Best Practice

Researchers need guidance in discovering and applying standards, and tools for (meta)data, terminologies, and provenance addressing their specific needs. In NFDI each consortium identifies, collects, and develops approaches that might be relevant for the broader research activities by and in the communities. The Working Group “Cookbooks, Guidance, and Best Practices” aims at identifying, collecting, exchanging and, where appropriate, harmonizing concepts, workflows, and best practices from consortia related to these topics and will develop support strategies to advance high-quality metadata production and provision. Contact: Susanne Arndt

Terminology Services

The core of FAIR metadata for research data management (RDM) are terminologies. Terminologies have various distinct characteristics: they describe domain knowledge (e.g. Chemistry, Biology or Information Science use their own set of terminologies), and they are constantly evolving over time and need to be accepted and agreed upon (mapped) within their knowledge domain and beyond. The overall goal of the Terminology Services Working Group is to drive common developments, share best practices, and reduce barriers to the use of terminologies. Contact: Roman Baum

Ontology Harmonization and Mapping

Consistent use of terminologies, and the organization of vocabulary items into structured ontologies are prerequisites of FAIR data, in particular regarding cross-community re-use and machine-actionability of research data. Each scientific discipline and each consortium in NFDI comes with pre-existing terminologies, shaped by respective needs. They are prone to have conceptual overlaps and – as in natural language – there are different ways of expressing the same concept. Harmonization refers to finding an agreement on a common terminology, whereas mapping refers to an “agreement to disagree”, while using a well-defined interface between terminologies. This working group is going to coordinate this essential work for the federation of data that are structured with domain ontologies. Contact: Philip Strömert 

Search and Harvesting

This working group focuses on how to extract, find, and use (meta)data, both for discovery and consumption of data by researchers (search/discovery) and for aggregation and indexing by discovery services (harvesting). The actors can be humans or machines. Contact: Brigitte Mathiak, Heinrich Widmann

Knowledge Graphs

Knowledge Graphs are a key technology for implementing the FAIR principles in data infrastructures by ensuring interoperability for both humans and machines. The Working Group “Knowledge Graphs” aims to promote the use of knowledge graphs in all NFDI consortia, to facilitate cross-domain data interlinking and federation following the FAIR principles, and to contribute to the joint development of tools and technologies that enable the transformation of data into semantically reusable knowledge across different domains.

Contact: Renat Shigapov, Lozana Rossenova, Moritz Schubotz

Research Software Metadata

Research software is commonly used in various disciplines to perform research and as a research object itself. Therefore, it is covered by multiple NFDI consortia. To fulfill the FAIR criteria for research software, it needs to be described with meaningful and interoperable metadata enhancing transparency, reproducibility, and reusability in research. While there exist some metadata schemes for research software, e.g., CodeMeta, they have some limitations, e.g., missing elements and missing semantic interoperability.

To address these issues, this working group aims to provide a comprehensive metadata vocabulary for research software, compatible with existing frameworks such as schema.org and CodeMeta. Also, the working group will support all NFDI consortia in applying the vocabulary as well as develop domain-specific extensions if needed.

Contakt: Stephan Ferenz, Leyla Jael Castro

Deputy speaker: Dr. Brigitte Mathiak 

(GESIS – Leibniz Institute for Social Sciences e.V.)