The amount of information and data generated by scientists is constantly growing. These data have to be managed, structured and aggregated, and new knowledge is generated by analyzing and interpreting them. Transparency, traceability and reproducibility as part of good scientific practice require new tools, processes and services. This raises completely new legal questions and places high demands on security and trustworthiness. Collaboration beyond the boundaries of institutions and disciplines, in virtual research environments, is gaining in importance. And education also takes place in virtual spaces, independent of time and place.
For FIZ Karlsruhe as a Leibniz institute for information infrastructure, these challenges have great potential for the future: We research into these issues in order to further develop our products and services according to our customers’ needs and to promote the state of the art. This enables us to fulfil our main task, i.e., to provide researchers and scientists with information and the related services, at a high level.
The research department Information Service Engineering investigates models and methods for efficient semantic indexing, aggregation, linking, and retrieval of comprehensive heterogeneous and distributed data sources.
The NFDI aims to systematically index, preserve, and make available data from science and research. FIZ Karlsruhe’s various research units contribute to the NFDI consortia. All research areas are included.
Alam, Mehwish; Biswas, Russa; Chen,Yiyi; Dessi, Danilo; Gesese, Genet Asefa; Hoppe, Fabian; Sack, Harald:HierClasSArt: Knowledge-Aware Hierarchical Classification of Scholarly Articles. In Proc. of 1st International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K 2021), Co-located with The Web Conf 2021. [local copy (PDF)]
Dimitrova, Diana; Quintel, Teresa: Technological Experimentation Without Adequate Safeguards? Interoperable EU Databases and Access to the Multiple Identity Detector by SIRENE Bureaux; In: Data Protection and Privacy. Data Protection and Artificial Intelligence / Hallinan, Dara; Leenes, Ronald; Hert, Paul de (Hrsg.); Oxford: Hart Publishing, 2021; 280 S.; ISBN: 978-1-50994175-9; Computers Privacy and Data Protection Vol. 13
Hallinan, Dara; Leenes, Ronald; Hert, Paul de: Data Protection and Privacy, Data Protection and Artificial Intelligence; ISBN: 9781509941759
Hoppe, Fabian; Dessi, Danilo; Sack, Harald:Deep Learning meets Knowledge Graphs for Scholarly DataClassification. In Proc. of 1st International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K 2021), Co-located with The Web Conf 2021. [local copy (PDF)]
Jung, Nicole; Neumann, Steffen; Koepler, Oliver; Bach, Felix; Popp, Christian; Herres-Pawlis, Sonja; Liermann, Johannes; Razum, Matthias; Steinbeck, Christoph: "NFDI4Chem – Infrastruktur für den digitalen Wandel in der Chemischen Forschung" (Anhang); In: Bunsen-Magazin 23 (2), März 2021 (DOI: 10.26125/r978-6f93)
Tietz, Tabea; Bruns, Oleksandra; Göller, Sandra; Razum, Matthias; Dessì, Danilo; Sack, Harald: Knowledge Graph enabled Curation and Exploration of Nuremberg's City Heritage; In Proc. of the Conference on Digital Curation Technologies 2021 (Qurator 2021) (To be published)
Vsesviatska, Oleksandra; Tietz, Tabea; Hoppe, Fabian; Sprau, Mirjam; Meyer, Nils; Dessi, Danilo; Harald Sack: ArDO: An Ontology to Describe the Dynamics of Multimedia Archival Records; In: Proceedings of the 36th ACM/SIGAPP Symposium On Applied Computing (ACM SAC 2021) (To be published)