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Auflistung nach Autor:in "Mutschke, Peter"

1 - 4 von 4
  • Zeitschriftenartikel
    Applying Linked Data Technologies in the Social Sciences
    (KI - Künstliche Intelligenz: Vol. 30, No. 2, 2016) Zapilko, Benjamin; Schaible, Johann; Wandhöfer, Timo; Mutschke, Peter
    In recent years, Linked Open Data (LOD) has matured and gained acceptance across various communities and domains. Large potential of Linked Data technologies is seen for an application in scientific disciplines. In this article, we present use cases and applications for an application of Linked Data in the social sciences. They focus on (a) interlinking domain-specific information, and (b) linking social science data to external LOD sources (e.g. authority data) from other domains. However, several technical and research challenges arise, when applying Linked Data technologies to a scientific domain with its specific data, information needs and use cases. We discuss these challenges and show how they can be addressed.
  • Konferenzbeitrag
    NFDI4DS Infrastructure and Services
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Schimmler, Sonja; Wentzel, Bianca; Bleier, Arnim; Dietze, Stefan; Karmakar, Saurav; Mutschke, Peter; Kraft, Angelie; Taffa, Tilahun A.; Usbeck, Ricardo; Boukhers, Zeyd; Auer, Sören; Castro, Leyla J.; Ackermann, Marcel R.; Neumuth, Thomas; Schneider, Daniel; Abedjan, Ziawasch; Latif, Atif; Limani, Fidan; Abu Ahmad, Raia; Rehm, Georg; Attar Khorasani, Sima; Lieber, Matthias
    NFDI4DataScience (NFDI4DS) is a consortium founded to support researchers in all stages of the research data lifecycle in order to conduct their research in line with the FAIR principles. The infrastructure developed targets researchers from a wide range of disciplines working in the field of data science and artificial intelligence. NFDI4DS contributes to systematically understanding the needs and challenges of researchers in various disciplines regarding data science and artificial intelligence, keeping in mind ethical, legal and social aspects. The identified needs will be addressed by support structures such as educational videos and challenges. Transparency, reproducibility and FAIRness will be improved by integrating existing and newly developed services into the NFDI4DS infrastructure, and by systematically adding all digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) to the NFDI4DS research knowledge graph. This paper presents the goals of NFDI4DS, and gives an overview on what the consortium is going to contribute to the data science and artificial intelligence communities. It focuses on existing and newly developed services and their integration.
  • Konferenzbeitrag
    Research Knowledge Graphs in NFDI4DS
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Karmakar, Saurav; Zloch, Matthäus; Limani, Fidan; Zapilko, Benjamin; Upadhyaya, Sharmila; D’Souza, Jennifer; Castro, Leyla J.; Rehm, Georg; Ackermann, Marcel R.; Sack, Harald; Boukhers, Zeyd; Schimmler, Sonja; Dessí, Danilo; Mutschke, Peter; Dietze, Stefan
    The ever-increasing amount of research output through scientific articles requires means to enable transparency and a better understanding of key entities of the research lifecycle, referred to as research artifacts, such as methods, software, datasets, etc. Research Knowledge Graphs (RKG) make research artifacts findable, accessible, interoperable, and reusable (FAIR) and facilitate their interpretability. In this article, we describe the role of RKGs, from their construction to the expected benefits, including an overview and a vision of their use within the German National Research Data Infrastructure (NFDI) consortium NFDI4DataScience (NFDI4DS). This paper includes insights about the existing RKGs, how to formally represent research artifacts, and how this supports better transparency and reproducibility in data science and artificial intelligence. We also discuss key challenges, such as RKG construction, and integration, and give an outlook on future work.
  • Workshopbeitrag
    Strategische Unterstützung in verteilten, agentengestützten Informationssystemen
    (Mensch & Computer 2002: Vom interaktiven Werkzeug zu kooperativen Arbeits- und Lernwelten, 2002) Schaefer, André; Klas, Claus-Peter; Mutschke, Peter
    Durch eine agentenbasierte Vermittlungsschicht und ein integrierende, anwenderfreundliche Benutzerschnittstelle sollen im Projekt Daffodil Lösungen für Probleme bei der Integration verschiedener digitaler Bibliotheken und internetbasierter Informationsdienste gefunden werden. Der gesamte wissenschaftliche informationelle Prozess soll dabei unterstützt werden. Ein Schlüsselbegriff ist die strategische Unterstützung durch höhere Suchdienste, welche auf den Basisdiensten zur Integration heterogener Quellen aufsetzen und spezielle Mehrwertfunktionen implementieren. Die Arbeitsteilung zwischen Mensch und Maschine soll dabei unter Berücksichtigung von Benutzerautonomie und Arbeitserleichterung optimiert werden.