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End date: 2024 × Start date: 2020 × DDC: 020 × Has files: Yes × Type: Text × Subject: NFDI × WGL Institute: TIB ×

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    Relevante Faktoren für eine gelungene Implementierung von FDM-Services vor Ort: Ergebnisse einer Interviewbefragung von FDM-Mitarbeiter*innen an hessischen Hochschulen
    (Marburg : Philipps-Universität, 2022) Dellmann, Sarah
    Eine Vielzahl von Initiativen und Förderprogrammen zielt darauf, die Etablierung von Forschungsdatenmanagement (FDM) an deutschen Wissenschaftseinrichtungen voranzutreiben. Die Initiativen und Programme unterscheiden sich in Bezug auf Zielgruppe und gewählte Implementierungsstrategie. Welche hochschulinternen und -übergreifenden Faktoren sind für die gelungene Implementierung von FDM-Angeboten vor Ort ausschlaggebend? Der vorliegende Beitrag präsentiert Ergebnisse einer Interviewbefragung unter FDM-Mitarbeiter*innen an hessischen Hochschulen (Universitäten und staatliche Hochschulen für Angewandte Wissenschaften) im November 2020, die mittels qualitativer Inhaltsanalyse ausgewertet wurden. Neben Auflagen von Forschungsförderern sowie der Möglichkeit, sich über FDM hochschulpolitisch zu positionieren, wurden die Verstetigung von Stellen, Engagement der Hochschulleitung und gute Kommunikation der beteiligten zentralen Einrichtungen untereinander, insbesondere mit der Drittmittelstelle, als relevant genannt. Eine besondere Bedeutung bei der Schaffung von FDM-Services maßen die Interviewteilnehmer*innen der Hessischen Forschungsdateninfrastruktur HeFDI bei.
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    Workshop on PIDs within NFDI: Report of the Working Group “Persistent Identifiers (PID)” of the Section Common Infrastructures of the NFDI
    (Zenodo, 2023) Arend, Daniel; Bach, Janete; Elger, Kirsten; Göller, Sandra; Hagemann-Wilholt, Stephanie; Krahl, Rolf; Lange, Matthias; Linke, David; Mayer, Desiree; Mutschke, Peter; Reimer, Lorenz; Scheidgen, Markus; Schrader, Antonia C.; Selzer, Michael; Wieder, Philipp
    In order to gain an overview of the current state of the discussion on PIDs and for the identification of use cases for the initiation phase of a PID service within the NFDI basic services, the working group Persistent Identifier of the Section Common Infrastructures of the NFDI hosted an online workshop in January 2023. In the course of the workshop, members of nine different NFDI consortia presented the current application of PIDs in their consortia.
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    Knowledge Graphs - Working Group Charter (NFDI section-metadata) (1.2)
    (Genève : CERN, 2023) Stocker, Markus; Rossenova, Lozana; Shigapov, Renat; Betancort, Noemi; Dietze, Stefan; Murphy, Bridget; Bölling, Christian; Schubotz, Moritz; Koepler, Oliver
    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" in Section "(Meta)data, Terminologies, Provenance" of the German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur (NFDI) e.V.) 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 transformation of structured and unstructured data into semantically reusable knowledge across different domains.
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    The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI
    (Hannover : TIB Open Publishing, 2023) Rossenova, Lozana; Schubotz, Moritz; Shigapov, Renat
    The Strategic Research and Innovation Agenda (SRIA) of the European Commission identifies Knowledge Graphs (KGs) as one of the most important technologies for building an interoperability framework and enabling data exchange among users across countries, sectors, and disciplines [1]. KG is a graph-structured knowledge base containing a terminology (vocabulary or ontology) and data entities interrelated via the terminology [2]. KGs are based on semantic web technologies (RDF, SPARQL, etc.) and often used for agile data integration. KGs also play an essential role within Germany as a vehicle to connect research data and research-related entities and make those accessible – examples include the GESIS Knowledge Graph Infrastructure, TIB Open Research Knowledge Graph, and GND.network. Furthermore, the Wikidata knowledge graph, maintained by Wikimedia Germany, contains a large number of research-related entities and is widely used in scientific knowledge management in addition to being an important advocacy tool for open data [3]. Extending domain-specific ontology-supported KGs with the multidisciplinary, crowdsourced knowledge in Wikidata KG would enable significant applications. The linking between expert knowledge systems and world knowledge empowers lay persons to benefit from high-quality research data and ultimately contributes to increasing confidence in scientific research in society.
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    Isn't a number and a URL enough? Why PIDs matter and technical solutions alone are not sufficient
    (Zenodo, 2023) Schrader, Antonia C.; Hagemann-Wilholt, Stephanie; Czerniak, Andreas
    In the presentation, we introduce the two projects PID4NFDI and PID Network Germany that deal with PIDs at the national level, present some initial findings and highlight their benefit for NFDI. PIDs are used and needed along the entire lifecycle of research data: from enabling to connecting. However, a particular focus for the presentation will be laid on harmonising and connecting.
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    Semantic annotation for 3D cultural artefacts: MVP
    (Zenodo, 2021) Blümel, Ina; Rossenova, Lozana; Sohmen, Lucia; Vock, Richard; Schubert, Zoe
    A suite of tools for semantic annotation of 3D cultural artefacts is being developed as part of the NFDI4Culture project across several partner organisations (led by the Open Science lab at TIB, Hannover). Operating within Task area 1: Data capture and enrichment, the proposed toolchain focuses on the annotation of 3D data within a knowledge graph environment, so that 3D objects’ geometry, attendant metadata, as well as annotations remain searchable, while data interconnections are not lost.
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    PID4NFDI: Survey on PID Practices. Main results
    (Zenodo, 2023) Hagemann-Wilholt, Stephanie
    In December 2022 and January 2023, the NFDI working group on Persistent Identifier Services conducted a survey among infrastructure managers of NFDI services to learn about current PID integrations and future plans on PID usage. The slides summarise the key results of the survey.
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    Concept for Setting up the Persistent Identifier Services Working Group in the NFDI Section "Common Infrastructures"
    (Zenodo, 2022) Bingert, Sven; Brase, Jan; Burger, Felix; Dreyer, Britta; Hagemann-Wilholt, Stephanie; Vierkant, Paul; Wieder, Philipp
    The aim of this NFDI working group is to develop a common strategy for the implementation and extension of PID services that is closely aligned with the needs of NFDI consortia. Resulting solutions should enable FAIR research workflows balancing out generic metadata requirements for PIDs that maximise resource discoverability on the one hand and subject-specific needs on the other. At the technical level, the partners want to realise interoperability between PID types and established systems and build on a high level of maturity here; jointly developed services should be able to be rolled out for the entire NFDI.
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    Leipzig-Berlin-Erklärung zu NFDI-Querschnittsthemen der Infrastrukturentwicklung
    (Meyrin : CERN, 2020-06-15) Bierwirth, Maik; Glöckner, Frank Oliver; Grimm, Christian; Schimmler, Sonja; Boehm, Franziska; Busse, Christian; Degkwitz, Andreas; Koepler, Oliver; Neuroth, Heike
    Für den wissenschaftsgeleiteten Aufbau der Nationalen Forschungsdaten-Infrastruktur (NFDI) muss sich die Infrastruktur gemeinsam mit der Forschung weiterentwickeln. Die dafür notwendigen, wechselseitigen Abstimmungen müssen auf Basis tragfähiger Prozesse und Strukturen sichergestellt werden. Themen, die für mehrere Fachkonsortien relevant sind, müssen im Sinne einer nachhaltigen Funktionalität kooperativ und über einzelne Konsortien hinweg bearbeitet werden. Dieses Dokument identifiziert solche Querschnittsthemen und Wege zu ihrer Bearbeitung in der NFDI. Um diese Herausforderung abgestimmt zu adressieren, hat sich die Mehrzahl der Fachkonsortien im Sommer 2019 auf die “Berlin Declaration on NFDI Cross-Cutting Topics” verständigt. Auf einer gemeinsamen Veranstaltung am 25. Februar 2020 in Berlin haben sich Vertreterinnen und Vertreter von Fachkonsortien und Querschnittsinitiativen erneut über die Handlungsfelder der NFDI-übergreifenden Infrastrukturentwicklung ausgetauscht. Dabei haben Fachkonsortien und Querschnittsinitiativen vier modellhafte Vorschläge erarbeitet, um diese Handlungsfelder zu erweitern und im Rahmen der NFDI belastbar und nachhaltig umzusetzen. Diese „Leipzig-Berlin-Erklärung zu NFDI-Querschnittsthemen der Infrastrukturentwicklung“ dient als Diskussionsimpuls und richtet sich an alle Konsortien und am Aufbau der NFDI Beteiligten, sowie diejenigen Fachgruppen, die näher mit Forschungsdatenmanagement befasst sind. Mit der Unterzeichnung dieser Erklärung bestätigen die 27 Konsortien, dass sie gemeinschaftlich und im Einklang mit dem Direktorat und den Gremien der NFDI die benannten Querschnittsthemen und Handlungsfelder weiterentwickeln und im Sinne einer NFDI bearbeiten werden.
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    NFDI4Ing - the National Research Data Infrastructure for Engineering Sciences
    (Meyrin : CERN, 2020-09-25) Schmitt, Robert H.; Anthofer, Verena; Auer, Sören; Başkaya, Sait; Bischof, Christian; Bronger, Torsten; Claus, Florian; Cordes, Florian; Demandt, Évariste; Eifert, Thomas; Flemisch, Bernd; Fuchs, Matthias; Fuhrmans, Marc; Gerike, Regine; Gerstner, Eva-Maria; Hanke, Vanessa; Heine, Ina; Huebser, Louis; Iglezakis, Dorothea; Jagusch, Gerald; Klinger, Axel; Krafczyk, Manfred; Kraft, Angelina; Kuckertz, Patrick; Küsters, Ulrike; Lachmayer, Roland; Langenbach, Christian; Mozgova, Iryna; Müller, Matthias S.; Nestler, Britta; Pelz, Peter; Politze, Marius; Preuß, Nils; Przybylski-Freund, Marie-Dominique; Rißler-Pipka, Nanette; Robinius, Martin; Schachtner, Joachim; Schlenz, Hartmut; Schwarz, Annett; Schwibs, Jürgen; Selzer, Michael; Sens, Irina; Stäcker, Thomas; Stemmer, Christian; Stille, Wolfgang; Stolten, Detlef; Stotzka, Rainer; Streit, Achim; Strötgen, Robert; Wang, Wei Min
    NFDI4Ing brings together the engineering communities and fosters the management of engineering research data. The consortium represents engineers from all walks of the profession. It offers a unique method-oriented and user-centred approach in order to make engineering research data FAIR – findable, accessible, interoperable, and re-usable. NFDI4Ing has been founded in 2017. The consortium has actively engaged engineers across all five engineering research areas of the DFG classification. Leading figures have teamed up with experienced infrastructure providers. As one important step, NFDI4Ing has taken on the task of structuring the wealth of concrete needs in research data management. A broad consensus on typical methods and workflows in engineering research has been established: The archetypes. So far, seven archetypes are harmonising the methodological needs: Alex: bespoke experiments with high variability of setups, Betty: engineering research software, Caden: provenance tracking of physical samples & data samples, Doris: high performance measurement & computation, Ellen: extensive and heterogeneous data requirements, Frank: many participants & simultaneous devices, Golo: field data & distributed systems. A survey of the entire engineering research landscape in Germany confirms that the concept of engineering archetypes has been very well received. 95% of the research groups identify themselves with at least one of the NFDI4Ing archetypes. NFDI4Ing plans to further coordinate its engagement along the gateways provided by the DFG classification of engineering research areas. Consequently, NFDI4Ing will support five community clusters. In addition, an overarching task area will provide seven base services to be accessed by both the community clusters and the archetype task areas. Base services address quality assurance & metrics, research software development, terminologies & metadata, repositories & storage, data security & sovereignty, training, and data & knowledge discovery. With the archetype approach, NFDI4Ing’s work programme is modular and distinctly method-oriented. With the community clusters and base services, NFDI4Ing’s work programme remains firmly user-centred and highly integrated. NFDI4Ing has set in place an internal organisational structure that ensures viability, operational efficiency, and openness to new partners during the course of the consortium’s development. NFDI4Ing’s management team brings in the experience from two applicant institutions and from two years of actively engaging with the engineering communities. Eleven applicant institutions and over fifty participants have committed to carrying out NFDI4Ing’s work programme. Moreover, NFDI4Ing’s connectedness with consortia from nearby disciplinary fields is strong. Collaboration on cross-cutting topics is well prepared and foreseen. As a result, NFDI4Ing is ready to join the National Research Data Infrastructure.