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    Global Community Guidelines for Documenting, Sharing, and Reusing Quality Information of Individual Digital Datasets
    (Paris : CODATA, 2022) Peng, Ge; Lacagnina, Carlo; Downs, Robert R.; Ganske, Anette; Ramapriyan, Hampapuram K.; Ivánová, Ivana; Wyborn, Lesley; Jones, Dave; Bastin, Lucy; Shie, Chung-lin; Moroni, David F.
    Open-source science builds on open and free resources that include data, metadata, software, and workflows. Informed decisions on whether and how to (re)use digital datasets are dependent on an understanding about the quality of the underpinning data and relevant information. However, quality information, being difficult to curate and often context specific, is currently not readily available for sharing within and across disciplines. To help address this challenge and promote the creation and (re)use of freely and openly shared information about the quality of individual datasets, members of several groups around the world have undertaken an effort to develop international community guidelines with practical recommendations for the Earth science community, collaborating with international domain experts. The guidelines were inspired by the guiding principles of being findable, accessible, interoperable, and reusable (FAIR). Use of the FAIR dataset quality information guidelines is intended to help stakeholders, such as scientific data centers, digital data repositories, and producers, publishers, stewards and managers of data, to: i) capture, describe, and represent quality information of their datasets in a manner that is consistent with the FAIR Guiding Principles; ii) allow for the maximum discovery, trust, sharing, and reuse of their datasets; and iii) enable international access to and integration of dataset quality information. This article describes the processes that developed the guidelines that are aligned with the FAIR principles, presents a generic quality assessment workflow, describes the guidelines for preparing and disseminating dataset quality information, and outlines a path forward to improve their disciplinary diversity.
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    Publikationsmonitoring
    (Bielefeld : Transcript, 2020) Schmeja, Stefan; Tullney, Marco; Lackner, Karin; Schilhan, Lisa; Kaier, Christian
    Die systematische Erfassung und Dokumentation des Publikationsoutputs einer Einrichtung spielt in Zeiten einer vorwiegend quantitativ erfolgenden Bewertung von Forschungsleistungen eine immer wichtigere Rolle für viele Universitäten und Forschungseinrichtungen. Zusammen mit weiteren Parametern wie eingeworbenen Drittmitteln dienen Publikationsdaten nicht nur der Außendarstellung, sondern auch der internen Auswertung und Steuerung bis hin zur leistungsorientierten Mittelvergabe. Hochschulverwaltungen dienen die Daten zur Identifizierung von Handlungsbedarfen bei der Entwicklung von Fachbereichen und Instituten. Systematisch erfasste Publikationsdaten geben Aufschluss über Trends in der Forschung und, insbesondere im Zusammenhang mit Zitationsdaten, über Verbindungen zwischen unterschiedlichen Forschungsgebieten oder Einrichtungen.
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    Towards Fair Principles for Research Information: Report on a Series of Workshops
    (Kyiv : Kyiv National University of Culture and Arts, 2021) Kaliuzhna, Nataliia; Altemeier, Franziska
    This is a summary report of the series of workshops on FAIR research information in open infrastructures that was jointly organised by the State Scientific and Technical Library of Ukraine (SSTL) and Leibniz Information Centre for Science and Technology (TIB) which have been collaborating under the framework of Joint German-Ukrainian project supported by the Federal Ministry of Education and Research of Germany and the Ministry of Science and Education of Ukraine. The workshops successfully harnessed the enthusiasm and experience of librarians, researchers, software providers, public funding body representatives, content providers, scientometricians and information specialists in an attempt to shed light and define criteria which assist discovery and reuse of research information by third-parties and make it FAIR. The series of workshops consisted of four separate workshops which addressed single aspects of FAIR– findability, accessibility, interoperability and reuse concerning research information. Due to Covid-19 travel restrictions workshops were held online between September 2020 and January 2021.
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    Plasma-MDS, a metadata schema for plasma science with examples from plasma technology
    (London : Nature Publ. Group, 2020) Franke, Steffen; Paulet, Lucian; Schäfer, Jan; O'Connell, Deborah; Becker, Markus M.
    A metadata schema, named Plasma-MDS, is introduced to support research data management in plasma science. Plasma-MDS is suitable to facilitate the publication of research data following the FAIR principles in domain-specific repositories and with this the reuse of research data for data driven plasma science. In accordance with common features in plasma science and technology, the metadata schema bases on the concept to separately describe the source generating the plasma, the medium in which the plasma is operated in, the target the plasma is acting on, and the diagnostics used for investigation of the process under consideration. These four basic schema elements are supplemented by a schema element with various attributes for description of the resources, i.e. the digital data obtained by the applied diagnostic procedures. The metadata schema is first applied for the annotation of datasets published in INPTDAT—the interdisciplinary data platform for plasma technology. © 2020, The Author(s).
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    Freie Versionen paywall-geschützter Artikel finden
    (Zenodo, 2017) Tullney, Marco
    Präsentation zum Hobsy-Workshop 2017, 15. Dezember 2017, Gottfried Wilhelm Leibniz Bibliothek