There is a wide variety of archives, databases, and repositories currently available that pro-vide access to research data. However, basic information about these systems is often diffi-cult to gather, such as whether there are limits to the size of data sets that can be published or whether there is any publication fee that applies. In addition to that, there are plenty of re-search groups publishing their research data sets independently of these infrastructures, making it difficult for scientists to find them since they are not centrally registered. Research data must be easily discoverable and accessible for scientists to use it effectively. The Data Collections Explorer, developed within the national research data infrastructure for the engineering sciences NFDI4Ing, is an easy-to-use information system addressing these needs. It is a low threshold information system that provides an overview of research data repositories, archives, databases as well as individually published data sets. Similar systems exist in other subject areas, for example the Data Repository Finder focusing on the medi-cal, life and social sciences. Contrary to the Data Collections Explorer, the Data Repository Finder only lists repositories.
This is the slide set for the talk as part of the "Engineering Sciences" track at the 1st Conference on Research Data Infrastructures.
NFDI4Ing Community Meeting CC-42 2022: Überblick zu NFDI & NFDI4IngEine kurze Einführung in die Nationale Forschungsdateninfrastruktur (NFDI)und die Nationale Forschungsdateninfrastruktur für Ingenieure (NFDI4Ing). A short introduction to the (German) National Research Data Infrastructure (NFDI) and the National Research Data Infrastructure for Engineers (NFDI4Ing).
Long Term Interoperability of Distributed Research Data InfrastructuresResearch institutions have established a variety of research data infrastructures that orient towards discipline or methodology specific needs of their respective research community. Technically, these infrastructures ultimately are based on "off-the-shelf" hardware and software building blocks – both commercial and open-source. While such "enterprise ready" infrastructures can scale well, they apt to data silos and typically do not adhere to scientific standards like the FAIR (Findability, Accessibility, Interoperability, Reusability) principles out of the box. Using common architecture concepts such as the FAIR Digital Object (FAIR DO) allows interconnection of these silos by adding a long term interoperability layer on top of the existing infrastructure components.
The presented approach provides a practical solution for interconnecting distributed research data infrastructures to national (like NFDI) and international (like EOSC and Gaia-X) infrastructures and preventing the creation of data silos. By allowing existing data infrastructures to make data FAIR, we enable researchers to access and reuse data from different domains, facilitating cross-disciplinary research and advancing new methods for scientific discoveries.
