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Now showing 1 - 10 of 41
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    Wie FAIR sind unsere Metadaten? : Eine Analyse der Metadaten in den Repositorien des TIB-DOI-Services
    (Marburg : Philipps-Universität, 2021) Burger, Marleen; Cordts, Anette; Habermann, Ted
    Im vorliegenden Erfahrungsbericht stellen wir eine Metadatenanalyse vor, welche die Metadatenqualität von 144 Repositorien des TIB-DOI-Service im Hinblick auf die Erfüllung der FAIR Data Principles, Konsistenz und Vollständigkeit untersucht. Im Ergebnis zeigt sich, dass der Fokus der untersuchten Repositorien schwerpunktmäßig auf der Auffindbarkeit der mit Metadaten beschriebenen Ressourcen liegt und im Gesamtdurchschnitt über die Metadaten-Pflichtfelder hinaus nur wenige weitere Metadaten angegeben werden. Insbesondere mit Blick auf eine angestrebte bessere Nachnutzbarkeit sowie eine stärkere Verknüpfung mit anderen in Beziehung stehenden persistenten Identifikatoren wie ORCID, ROR ID oder DOI-zu-DOI-Beziehungen mit zitierten oder zitierenden Ressourcen, bestehen noch ungenutzte Potenziale, die im Sinne einer offenen, zukunftsweisenden Wissenschaft erschlossen werden sollten. Dahingegen zeigt unsere Analyse auch einzelne Repositorien mit umfangreichen Metadaten als Best-Practice-Beispiele auf, an denen sich andere Repositorien orientieren können. Insgesamt ermöglicht die durchgeführte Metadatenanalyse die Ableitung von Handlungsempfehlungen zur passgenauen Beratung von Repositorien, die ihre Metadatenqualität verbessern möchten.
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    Anne Baillot: From Handwriting to Footprinting: Text and Heritage in the Age of Climate Crisis. Cambridge: Open Book Publishers, 2023, 179 Seiten, ISBN 978-1-80511-089-7, https://doi.org/10.11647/OBP.0355
    (Berlin : Walter de Gruyter, 2024-05-04) Schmeja, Stefan
    Reviewed Publication: Baillot Anne From Handwriting to Footprinting: Text and Heritage in the Age of Climate Crisis Cambridge Open Book Publishers 2023 179 Seiten ISBN 978-1-80511-089-7, https://doi.org/10.11647/OBP.0355
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    Zertifizierung von Forschungsdatenrepositorien: Wege, Praxiserfahrungen und Perspektiven : 10. Workshop der DINI/nestor-AG Forschungsdaten
    (Marburg : Philipps-Universität, 2020) Recker, Jonas; Helbig, Kerstin; Neumann, Janna
    Die DINI/nestor-AG Forschungsdaten führte am 5. März 2020 einen Workshop zum Thema Zertifizierung von Forschungsdatenrepositorien[1] an der Universitätsbibliothek Leipzig durch. Motiviert war die Veranstaltung durch den Wunsch, Teilnehmer*innen einen Überblick über relevante Zertifizierungsverfahren zu geben und Vorteile einer Zertifizierung herauszustellen. Gleichzeitig diente die Veranstaltung dem Austausch über Anforderungen und Unterstützungsbedarfe seitens der Repositorien. Trotz einer Reihe von Corona-bedingten Absagen und Vortragsausfällen verfolgten insgesamt 50 Teilnehmende die Vorträge und nahmen an der lebhaften Breakoutsession teil. Dieser Beitrag bereitet die Informationen und Anregungen aus den Diskussionen auf und skizziert erste Lösungsansätze zum Abbau identifizierter Hürden.
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    Persistent identification of instruments
    (London : Ubiquity Press, 2020) Stocker, M.; Darroch, L.; Krahl, R.; Habermann, T.; Devaraju, A.; Schwardmann, U.; D’onofrio, C.; Häggström, I.
    Instruments play an essential role in creating research data. Given the importance of instruments and associated metadata to the assessment of data quality and data reuse, globally unique, persistent and resolvable identification of instruments is crucial. The Research Data Alliance Working Group Persistent Identification of Instruments (PIDINST) developed a community-driven solution for persistent identification of instruments which we present and discuss in this paper. Based on an analysis of 10 use cases, PIDINST developed a metadata schema and prototyped schema implementation with DataCite and ePIC as representative persistent identifier infrastructures and with HZB (Helmholtz-Zentrum Berlin für Materialien und Energie) and BODC (British Oceanographic Data Centre) as representative institutional instrument providers. These implementations demonstrate the viability of the proposed solution in practice. Moving forward, PIDINST will further catalyse adoption and consolidate the schema by addressing new stakeholder requirements.
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    FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources
    (Cambridge, MA : MIT Press, 2020) Sustkova, Hana Pergl; Hettne, Kristina Maria; Wittenburg, Peter; Jacobsen, Annika; Kuhn, Tobias; Pergl, Robert; Slifka, Jan; McQuilton, Peter; Magagna, Barbara; Sansone, Susanna-Assunta; Stocker, Markus; Imming, Melanie; Lannom, Larry; Musen, Mark; Schultes, Erik
    The FAIR principles articulate the behaviors expected from digital artifacts that are Findable, Accessible, Interoperable and Reusable by machines and by people. Although by now widely accepted, the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR behaviors. As different communities have their own, often well-established implementation preferences and priorities for data reuse, coordinating a broadly accepted, widely used FAIR implementation approach remains a global challenge. In an effort to accelerate broad community convergence on FAIR implementation options, the GO FAIR community has launched the development of the FAIR Convergence Matrix. The Matrix is a platform that compiles for any community of practice, an inventory of their self-declared FAIR implementation choices and challenges. The Convergence Matrix is itself a FAIR resource, openly available, and encourages voluntary participation by any self-identified community of practice (not only the GO FAIR Implementation Networks). Based on patterns of use and reuse of existing resources, the Convergence Matrix supports the transparent derivation of strategies that optimally coordinate convergence on standards and technologies in the emerging Internet of FAIR Data and Services.
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    Open Access im Blick! Mehr Sichtbarkeit von Open-Access-Publikationen in der Bibliothek – Projekt visOA
    (Berlin : De Gruyter, 2020) Geith, Uwe; Kraß, Thomas
    In order to bring Open Access publications more into the perception of library users, it is necessary to make them more visible. In the visOA project, carried out by the NTNM library of the INM, Open Access publications were clearly highlighted in the OPAC as well as in the Discovery System and in the publication lists of the INM. A self-programmed virtual journal display (VIDIJO) also offers a subject-specific selection of Open Access journals. The effectiveness of the measures taken in the project was verified by accompanying research.
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    Graf, Dorothee; Fadeeva, Yuliya; Falkenstein-Feldhoff, Katrin (Hrsg.): Bücher im Open Access: ein Zukunftsmodell für die Geistes- und Sozialwissenschaften? Opladen: Verlag Barbara Budrich, 2020. ISBN: 978-3-8474-2460-4, Paperback, 39,90 €. Auch Open Access: https://doi.org/10.17185/duepublico/72237
    (Berlin ; New York : de Gruyter, 2021) Schmeja, Stefan
    Rezension zu Graf, Dorothee; Fadeeva, Yuliya; Falkenstein-Feldhoff, Katrin (Hrsg.): Bücher im Open Access: ein Zukunftsmodell für die Geistes- und Sozialwissenschaften? Opladen: Verlag Barbara Budrich, 2020. ISBN: 978-3-8474-2460-4
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    Compacting frequent star patterns in RDF graphs
    (Dordrecht : Springer Science + Business Media B.V, 2020) Karim, Farah; Vidal, Maria-Esther; Auer, Sören
    Knowledge graphs have become a popular formalism for representing entities and their properties using a graph data model, e.g., the Resource Description Framework (RDF). An RDF graph comprises entities of the same type connected to objects or other entities using labeled edges annotated with properties. RDF graphs usually contain entities that share the same objects in a certain group of properties, i.e., they match star patterns composed of these properties and objects. In case the number of these entities or properties in these star patterns is large, the size of the RDF graph and query processing are negatively impacted; we refer these star patterns as frequent star patterns. We address the problem of identifying frequent star patterns in RDF graphs and devise the concept of factorized RDF graphs, which denote compact representations of RDF graphs where the number of frequent star patterns is minimized. We also develop computational methods to identify frequent star patterns and generate a factorized RDF graph, where compact RDF molecules replace frequent star patterns. A compact RDF molecule of a frequent star pattern denotes an RDF subgraph that instantiates the corresponding star pattern. Instead of having all the entities matching the original frequent star pattern, a surrogate entity is added and related to the properties of the frequent star pattern; it is linked to the entities that originally match the frequent star pattern. Since the edges between the entities and the objects in the frequent star pattern are replaced by edges between these entities and the surrogate entity of the compact RDF molecule, the size of the RDF graph is reduced. We evaluate the performance of our factorization techniques on several RDF graph benchmarks and compare with a baseline built on top gSpan, a state-of-the-art algorithm to detect frequent patterns. The outcomes evidence the efficiency of proposed approach and show that our techniques are able to reduce execution time of the baseline approach in at least three orders of magnitude. Additionally, RDF graph size can be reduced by up to 66.56% while data represented in the original RDF graph is preserved.
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    Scientific publishing sanctions in response to the Russo-Ukrainian war
    (Chichester : Wiley, 2022) Nazarovets, Maryna; Teixeira da Silva, Jaime A.
    The Russian invasion of Ukraine is negatively affecting the development of the Ukrainian academy, now and in the foreseeable future. Different academic stakeholders around the world have reacted differently to this war, some imposing sanctions against Russia and/or providing aid to Ukraine. Some scientific publishers have partially or temporarily suspended sales and marketing of products and services to research organizations in Russia and Belarus. The issue of banning publication in international journals by authors from Russian institutions remains controversial and needs to be carefully considered by various stakeholders. © 2022 The Authors. Learned Publishing published by John Wiley & Sons Ltd on behalf of ALPSP
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    Sentence, Phrase, and Triple Annotations to Build a Knowledge Graph of Natural Language Processing Contributions - A Trial Dataset
    (Beijing : National Science Library, Chinese Academy of Sciences, 2021) D’Souza, Jennifer; Auer, Sören
    This work aims to normalize the NlpContributions scheme (henceforward, NlpContributionGraph) to structure, directly from article sentences, the contributions information in Natural Language Processing (NLP) scholarly articles via a two-stage annotation methodology: 1) pilot stage—to define the scheme (described in prior work); and 2) adjudication stage—to normalize the graphing model (the focus of this paper). We re-annotate, a second time, the contributions-pertinent information across 50 prior-annotated NLP scholarly articles in terms of a data pipeline comprising: contribution-centered sentences, phrases, and triple statements. To this end, specifically, care was taken in the adjudication annotation stage to reduce annotation noise while formulating the guidelines for our proposed novel NLP contributions structuring and graphing scheme. The application of NlpContributionGraph on the 50 articles resulted finally in a dataset of 900 contribution-focused sentences, 4,702 contribution-information-centered phrases, and 2,980 surface-structured triples. The intra-annotation agreement between the first and second stages, in terms of F1-score, was 67.92% for sentences, 41.82% for phrases, and 22.31% for triple statements indicating that with increased granularity of the information, the annotation decision variance is greater. NlpContributionGraph has limited scope for structuring scholarly contributions compared with STEM (Science, Technology, Engineering, and Medicine) scholarly knowledge at large. Further, the annotation scheme in this work is designed by only an intra-annotator consensus—a single annotator first annotated the data to propose the initial scheme, following which, the same annotator reannotated the data to normalize the annotations in an adjudication stage. However, the expected goal of this work is to achieve a standardized retrospective model of capturing NLP contributions from scholarly articles. This would entail a larger initiative of enlisting multiple annotators to accommodate different worldviews into a “single” set of structures and relationships as the final scheme. Given that the initial scheme is first proposed and the complexity of the annotation task in the realistic timeframe, our intra-annotation procedure is well-suited. Nevertheless, the model proposed in this work is presently limited since it does not incorporate multiple annotator worldviews. This is planned as future work to produce a robust model. We demonstrate NlpContributionGraph data integrated into the Open Research Knowledge Graph (ORKG), a next-generation KG-based digital library with intelligent computations enabled over structured scholarly knowledge, as a viable aid to assist researchers in their day-to-day tasks. NlpContributionGraph is a novel scheme to annotate research contributions from NLP articles and integrate them in a knowledge graph, which to the best of our knowledge does not exist in the community. Furthermore, our quantitative evaluations over the two-stage annotation tasks offer insights into task difficulty.