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ATMODAT Standard v3.0

2020, Gasnke, Anette, Kraft, Angelina, Kaiser, Amandine, Heydebreck, Daniel, Lammert, Andrea, Höck, Heinke, Thiemann, Hannes, Voss, Vivien, Grawe, David, Leitl, Bernd, Schlünzen, K. Heinke, Kretzschmar, Jan, Quaas, Johannes

Within the AtMoDat project (Atmospheric Model Data), a standard has been developed which is meant for improving the FAIRness of atmospheric model data published in repositories. The ATMODAT standard includes concrete recommendations related to the maturity, publication and enhanced FAIRness of atmospheric model data. The suggestions include requirements for rich metadata with controlled vocabularies, structured landing pages, file formats (netCDF) and the structure within files. Human- and machine readable landing pages are a core element of this standard, and should hold and present discipline-specific metadata on simulation and variable level. This standard is an updated and translated version of "Bericht über initialen Kernstandard und Kurationskriterien des AtMoDat Projektes (v2.4)

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A tale of two 'opens': intersections between Free and Open Source Software and Open Scholarship

2020, Tennant, Jonathan P., Agrawal, Ritwik, Baždarić, Ksenija, Brassard, David, Crick, Tom, Dunleavy, Daniel J., Evans, Thomas Rhys, Gardner, Nicholas, Gonzalez-Marquez, Monica, Graziotin, Daniel, Greshake Tzovaras, Bastian, Gunnarson, Daniel, Havemann, Johanna, Hosseini, Mohammad, Katz, Daniel S., Knöchelmann, Marcel, Lahti, Leo, Madan, Christopher R., Manghi, Paolo, Marocchino, Alberto, Masuzzo, Paola, Murray-Rust, Peter, Narayanaswamy, Sanjay, Nilsonne, Gustav, Pacheco-Mendoza, Josmel, Penders, Bart, Pourret, Olivier, Rera, Michael, Samuel, John, Steiner, Tobias, Stojanovski, Jadranka, Uribe Tirado, Alejandro, Vos, Rutger, Worthington, Simon, Yarkoni, Tal

There is no clear-cut boundary between Free and Open Source Software and Open Scholarship, and the histories, practices, and fundamental principles between the two remain complex. In this study, we critically appraise the intersections and differences between the two movements. Based on our thematic comparison here, we conclude several key things. First, there is substantial scope for new communities of practice to form within scholarly communities that place sharing and collaboration/open participation at their focus. Second, Both the principles and practices of FOSS can be more deeply ingrained within scholarship, asserting a balance between pragmatism and social ideology. Third, at the present, Open Scholarship risks being subverted and compromised by commercial players. Fourth, the shift and acceleration towards a system of Open Scholarship will be greatly enhanced by a concurrent shift in recognising a broader range of practices and outputs beyond traditional peer review and research articles. In order to achieve this, we propose the formulation of a new type of institutional mandate. We believe that there is substantial need for research funders to invest in sustainable open scholarly infrastructure, and the communities that support them, to avoid the capture and enclosure of key research services that would prevent optimal researcher behaviours. Such a shift could ultimately lead to a healthier scientific culture, and a system where competition is replaced by collaboration, resources (including time and people) are shared and acknowledged more efficiently, and the research becomes inherently more rigorous, verified, and reproducible.

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Knowledge Graphs - Working Group Charter (NFDI section-metadata) (1.2)

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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Concept for Setting up the Persistent Identifier Services Working Group in the NFDI Section "Common Infrastructures"

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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Advancing Research Data Management in Universities of Science and Technology

2020-02-13, Björnemalm, Matthias, Cappellutti, Federica, Dunning, Alastair, Gheorghe, Dana, Goraczek, Malgorzata Zofia, Hausen, Daniela, Hermann, Sibylle, Kraft, Angelina, Martinez Lavanchy, Paula, Prisecaru, Tudor, Sànchez, Barbara, Strötgen, Robert

The white paper ‘Advancing Research Data Management in Universities of Science and Technology’ shares insights on the state-of-the-art in research data management, and recommendations for advancement. A core part of the paper are the results of a survey, which was distributed to our member institutions in 2019 and addressed the following aspects of research data management (RDM): (i) the establishment of a RDM policy at the university; (ii) the provision of suitable RDM infrastructure and tools; and (iii) the establishment of RDM support services and trainings tailored to the requirements of science and technology disciplines. The paper reveals that while substantial progress has been made, there is still a long way to go when it comes to establishing “advanced-degree programmes at our major universities for the emerging field of data scientist”, as recommended in the seminal 2010 report ‘Riding the Wave’, and our white paper offers concrete recommendations and best practices for university leaders, researchers, operational staff, and policy makers. The topic of RDM has become a focal point in many scientific disciplines, in Europe and globally. The management and full utilisation of research data are now also at the top of the European agenda, as exemplified by Ursula von der Leyen addressat this year’s World Economic Forum.However, the implementation of RDM remains divergent across Europe. The white paper was written by a diverse team of RDM specialists, including data scientists and data stewards, with the work led by the RDM subgroup of our Task Force Open Science. The writing team included Angelina Kraft (Head of Lab Research Data Services at TIB, Leibniz University Hannover) who said: “The launch of RDM courses and teaching materials at universities of science and technology is a first important step to motivate people to manage their data. Furthermore, professors and PIs of all disciplines should actively support data management and motivate PhD students to publish their data in recognised digital repositories.” Another part of the writing team was Barbara Sanchez (Head of Centre for Research Data Management, TU Wien) and Malgorzata Goraczek (International Research Support / Data Management Support, TU Wien) who added:“A reliable research data infrastructure is a central component of any RDM service. In addition to the infrastructure, proper RDM is all about communication and cooperation. This includes bringing tools, infrastructures, staff and units together.” Alastair Dunning (Head of 4TU.ResearchData, Delft University of Technology), also one of the writers, added: “There is a popular misconception that better research data management only means faster and more efficient computers. In this white paper, we emphasise the role that training and a culture of good research data management must play.”

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Discussion on Existing Standards and Quality Criteria in Nanosafety Research : Summary of the NanoS-QM Expert Workshop

2021, Binder, Kunigunde, Bonatto Minella, Christian, Elberskirchen, Linda, Kraegeloh, Annette, Liebing, Julia, Petzold, Christiane, Razum, Matthias, Riefler, Norbert, Schins, Roel, Sofranko, Adriana, van Thriel, Christoph, Unfried, Klaus

The partners of the research project NanoS-QM (Quality- and Description Standards for Nanosafety Research Data) identified and invited relevant experts from research institutions, federal agencies, and industry to evaluate the traceability of the results generated with the existing standards and quality criteria. During the discussion it emerged that numerous studies seem to be of insufficient quality for regulatory purposes or exhibit weaknesses with regard to data completeness. Deficiencies in study design could be avoided by more comprehensive use of appropriate standards, many of which already exist. The use of Electronic Laboratory Notebooks (ELNs) that allow for early collection of metadata and enrichment of datasets could be one solution to enable data re-use and simplify quality control. Generally, earlier provision and curation of data and metadata indicating their quality and completeness (e.g. guidelines, standards, standard operating procedures (SOPs) that were used) would improve their findability, accessibility, interoperability, and reusability (FAIR) in the nanosafety research field.

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PID Network Deutschland: Netzwerk für die Förderung von persistenten Identifikatoren in Wissenschaft und Kultur

2023, Bertelmann, Roland, Buys, Matthew, Kett, Jürgen, Pampel, Heinz, Pieper, Dirk, Scholze, Frank, Sens, Irina, Burger, Felix, Dreyer, Britta, Glagla-Dietz, Stephanie, Hagemann- Wilholt, Stephanie, Hartmann, Sarah, Schrader, Antonia C., Schirrwagen, Jochen, Summann, Friedrich, Vierkant, Paul

[No abstract available]

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Metadatenschema für Schulungsmaterialien zum Thema Forschungsdatenmanagement

2020-04-27, Biernacka, Katarzyna, Danker, Sarah Ann, Engelhardt, Claudia, Helbig, Kerstin, Hendriks, Sonja, Jacob, Juliane, Jagusch, Gerald, Lanza, Giacomo, Leone, Claudio, Meier, Kristin, Neumann, Janna, Odebrecht, Carolin, Peters, Karsten, Rehwald, Stephanie, Rex, Jessica, Senft, Matthias, Strauch, Annette, Thiemann, Kathrin, Trautwein-Bruns, Ute, Wiljes, Cord, Wuttke, Ulrike, Ziedorn, Frauke

Das Dokument enthält ein Metadatenschema für Schulungsmaterialien zum Thema Forschungsdatenmanagement. Dieses Schema wurde von der UAG Schulungen/Fortbildungen der DINI/nestor AG Forschungsdaten erstellt und bei der Materialsammlung von FDM-Schulungsmaterialien unter https://rs.cms.hu-berlin.de/uag_fdm/ umgesetzt.

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Train-the-Trainer Konzept zum Thema Forschungsdatenmanagement - Version 3.1

2020-12-18, Biernacka, Katarzyna, Buchholz, Petra, Danker, Sarah Ann, Dolzycka, Dominika, Engelhardt, Claudia, Helbig, Kerstin, Jacob, Juliane, Neumann, Janna, Odebrecht, Carolin, Wiljes, Cord, Wuttke, Ulrike

Im Rahmen des BMBF-Projekts FDMentor wurde ein deutschsprachiges Train-the-Trainer Programm zum Thema Forschungsdatenmanagement (FDM) erstellt, das nach Projektende durch Mitglieder der UAG Schulungen/Fortbildungen der DINI/nestor-AG Forschungsdaten ergänzt und aktualisiert wurde. Die behandelten Themen umfassen sowohl die Aspekte des Forschungsdatenmanagements als auch didaktische Einheiten zu Lernkonzepten, Workshopgestaltung und eine Reihe von didaktischen Methoden. Die nun veröffentlichte dritte, überarbeitete und erweiterte Version des Train-the-Trainer-Konzepts enthält Einheiten zu Methoden und Materialien für Online-Veranstaltungen. Erste Erfahrungen aus bereits online durchgeführten Train-the-Trainer-Workshops sind zusätzlich in das Konzept eingeflossen. Die mit dieser Version eingeführten didaktischen Methoden für Online-Veranstaltungen sollen die geschulten Trainer*innen dabei unterstützen, ihre Schulungsangebote auch im virtuellen Raum lebendig und interaktiv zu gestalten und dient somit auch der weitergehenden Information der bereits geschulten Teilnehmer*innen. An English version of the "Train-the-Trainer Konzept zum Forschungsdatenmanagement" is available under https://doi.org/10.5281/zenodo.4071471

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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

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.