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End date: 2024 × Start date: 2020 × DDC: 020 × WGL Institute: FIZ KA ×

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Now showing 1 - 10 of 35
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    Harmonising, Harvesting, and Searching Metadata Across a Repository Federation
    (Hannover : TIB Open Publishing, 2023) Neumann, Steffen; Bach, Felix; Castro, Leyla Jael; Fischer, Tillmann; Hofmann, Stefan; Huang, Pei-Chi; Jung, Nicole; Katabathuni, Bhavin; Mauz, Fabian; Meier, René; Nainala, Venkata Chandra Sekhar; Rayya, Noura; Steinbeck, Christoph; Koepler, Oliver
    The collection of metadata for research data is an important aspect in the FAIR principles. The schema.org and Bioschemas initiatives created a vocabulary to embed markup for many different types, including BioChemEntity, ChemicalSubstance, Gene, MolecularEntity, Protein, and others relevant in the Natural and Life Sciences with immediate benefits for findability of data packages. To bridge the gap between the worlds of semantic-web-driven JSON+LD metadata on the one hand, and established but separately developed interface services in libraries, we have designed an architecture for harmonising, federating and harvesting metadata from several resources. Our approach is to serve JSON+LD embedded in an XML container through a central OAI-Provider. Several resources in NFDI4Chem provide such domain-specific metadata. The CKAN-based NFDI4Chem search service can harvest this metadata using an OAI-PMH harvester extension that can extract the XML-encapsulated JSON+LD metadata, and has search capabilities relevant in the chemistry domain. We invite the community to collaborate and reach a critical mass of providers and consumers in the NFDI.
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    Discussion on Existing Standards and Quality Criteria in Nanosafety Research : Summary of the NanoS-QM Expert Workshop
    (Zenodo, 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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    Analyzing social media for measuring public attitudes toward controversies and their driving factors: a case study of migration
    (Wien : Springer, 2022) Chen, Yiyi; Sack, Harald; Alam, Mehwish
    Among other ways of expressing opinions on media such as blogs, and forums, social media (such as Twitter) has become one of the most widely used channels by populations for expressing their opinions. With an increasing interest in the topic of migration in Europe, it is important to process and analyze these opinions. To this end, this study aims at measuring the public attitudes toward migration in terms of sentiments and hate speech from a large number of tweets crawled on the decisive topic of migration. This study introduces a knowledge base (KB) of anonymized migration-related annotated tweets termed as MigrationsKB (MGKB). The tweets from 2013 to July 2021 in the European countries that are hosts of immigrants are collected, pre-processed, and filtered using advanced topic modeling techniques. BERT-based entity linking and sentiment analysis, complemented by attention-based hate speech detection, are performed to annotate the curated tweets. Moreover, external databases are used to identify the potential social and economic factors causing negative public attitudes toward migration. The analysis aligns with the hypothesis that the countries with more migrants have fewer negative and hateful tweets. To further promote research in the interdisciplinary fields of social sciences and computer science, the outcomes are integrated into MGKB, which significantly extends the existing ontology to consider the public attitudes toward migrations and economic indicators. This study further discusses the use-cases and exploitation of MGKB. Finally, MGKB is made publicly available, fully supporting the FAIR principles.
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    The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI
    (Hannover : TIB Open Publishing, 2023) Rossenova, Lozana; Schubotz, Moritz; Shigapov, Renat
    The Strategic Research and Innovation Agenda (SRIA) of the European Commission identifies Knowledge Graphs (KGs) as one of the most important technologies for building an interoperability framework and enabling data exchange among users across countries, sectors, and disciplines [1]. KG is a graph-structured knowledge base containing a terminology (vocabulary or ontology) and data entities interrelated via the terminology [2]. KGs are based on semantic web technologies (RDF, SPARQL, etc.) and often used for agile data integration. KGs also play an essential role within Germany as a vehicle to connect research data and research-related entities and make those accessible – examples include the GESIS Knowledge Graph Infrastructure, TIB Open Research Knowledge Graph, and GND.network. Furthermore, the Wikidata knowledge graph, maintained by Wikimedia Germany, contains a large number of research-related entities and is widely used in scientific knowledge management in addition to being an important advocacy tool for open data [3]. Extending domain-specific ontology-supported KGs with the multidisciplinary, crowdsourced knowledge in Wikidata KG would enable significant applications. The linking between expert knowledge systems and world knowledge empowers lay persons to benefit from high-quality research data and ultimately contributes to increasing confidence in scientific research in society.
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    RADAR: Building a FAIR and Community Tailored Research Data Repository
    (Hannover : TIB Open Publishing, 2023) Bach, Felix; Soltau, Kerstin; Göller, Sandra; Bonatto Minella, Christian; Hofmann, Stefan
    The research data repository RADAR is designed to support the secure management, archiving, publication and dissemination of digital research data from completed scientific studies and projects. Developed as a collaborative project funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (2013-2016), the system is operated by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure - and currently serves as a generic cloud service for about 20 universities and non-university research institutions. Since its launch, RADAR has witnessed significant changes in the landscape of research data repositories and the evolving needs of researchers, research communities and institutions. In our presentation within the “Enabling RDM” Track, we will show how RADAR is responding to these dynamic changes. In order to create a sufficiently large user base for the sustainable operation of the system, we have moved RADAR away from its previous single focus on a discipline-agnostic cloud service and towards a demand-driven functional optimisation. In 2021, we introduced an additional operating model for institutions (RADAR Local), where we operate a separate RADAR instance locally at the institution site exclusively using the institutional IT-infrastructure. In 2022 we opened up RADAR to new target groups with community-specific service offerings, in particular in the context of the National Research Data Infrastructure (NFDI). Beside the expansion of the functional scope, our ongoing development work focuses also on strengthening the system's support for the FAIR principles [1] and the concepts of FAIR Digital Objects (FDO) [2] and Schema.org. Our presentation will outline recent RADAR developments and achievements as well as future plans thus providing solutions and synergy potential for the scientific community and for other service providers.
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    Gesamtkonzept für die Informationsinfrastruktur in Deutschland
    (Kommission Zukunft der Informationsinfrastruktur, 2011) Kommission Zukunft der Informationsinfrastruktur
    Was haben digitalisierte Objektträger aus der Krebsforschung, Magnetbandaufzeichnungen des ersten bemannten Mondfluges und das Tierstimmenarchiv der Berliner Humboldt- Universität miteinander zu tun? In allen Fällen enthalten sie wertvolle wissenschaftliche Informationen. Ihre Verfügbarkeit jedoch ist nicht immer gegeben: Wenige Klicks am Rechner genügen, um übers Internet beispielsweise den Teichfrosch (Rana esculenta) quaken zu hören. Doch wer Originalaufzeichnungen der ersten Mondmission sucht, hat Pech gehabt: Seit Jahren stöbern Mitarbeiter der US-Weltraumagentur NASA erfolglos in ihren Archiven und suchen die Spulen. Es wird immer mehr zur Gewissheit: Die drei Zentimeter breiten Magnetbänder wurden irgendwann schlicht gelöscht und mit anderen Daten überspielt. Ein Gutes hatte aber die Suche der NASA: Sie förderte in Australien andere alte Datenbänder zutage, auf denen Informationen über Mondstaub gespeichert sind. Doch darauf folgte gleich das nächste Problem – die Daten waren nicht lesbar. Man fand glücklicherweise einen historischen Rekorder, mit dem die Informationen entziffert werden konnten. Das Gerät von der Größe eines Kühlschranks kommt aus einem Museum. Diese Beispiele illustrieren die zunehmend wichtige Frage, wie Forscherinnen und Forscher künftig mit wissenschaftlichen Informationen und Daten künftig umgehen müssen, um sie für weitere Forschungsprozesse zu sichern und zugänglich zu machen. Mit diesem Themenkomplex hat sich die „Kommission Zukunft der Informationsinfrastruktur“ befasst. Diese hochrangig besetzte Expertengruppe hat unter der Federführung der Leibniz-Gemeinschaft das vorliegende Gesamtkonzept erarbeitet. Der Auftrag dazu kam von der Gemeinsamen Wissenschaftskonferenz des Bundes und der Länder (GWK). In der bemerkenswert kurzen Zeit von nur 15 Monaten ist es den Experten – es waren knapp 135 Personen aus 54 Institutionen – gelungen, eine umfassende Sachdarstellung sowie detaillierte Empfehlungen zu erarbeiten. Die Zusammensetzung der Kommission stellt ein Novum dar. Sie repräsentiert die maßgeblichen Akteure der Informationsinfrastruktur in Deutschland, und zwar sowohl die Dienstleister selbst als auch die Förderorganisationen ebenso wie die wissenschaftlichen Nutzer. Allen Mitgliedern der Kommission gebührt großer Dank für die erfolgreiche Arbeit. Mein ganz besonderer Dank gilt dem Engagement der Präsidiumsbeauftragten der Leibniz-Gemeinschaft für Informationsinfrastruktur, Sabine Brünger-Weilandt, die den Vorsitz der Kommission innehatte. Sie ist die Geschäftsführerin des Leibniz-Instituts für Informationsinfrastruktur – FIZ Karlsruhe, das sie zeitgleich zur Leitung der Kommission durch seine turnusgemäße Evaluierung geführt hat. Das vorliegende Konzept zeigt das enorme Potenzial für den Wissenschaftsstandort Deutschland, das in der strategischen Weiterentwicklung der Informationsinfrastruktur steckt. Und es weist den Weg in die Zukunft der Informationsinfrastruktur. Jetzt gilt es, die Umsetzung voranzutreiben.
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    Knowledge Graphs - Working Group Charter (NFDI section-metadata) (1.2)
    (Genève : CERN, 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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    Handreichung Urheberrecht und Datenschutz
    (Genève : CERN, 2023) Blumtritt, Ute; Euler, Ellen; Fadeevy, Yuliya; Pohle, Jörg; Rack, Fabian; Wrzesinski, Marcel
    Die vorliegende Handreichung adressiert wissenschaftsgeleitete Zeitschriften sowie herausgebende Einrichtungen. Sie sollen in die Lage versetzt werden, erste urheberrechtliche wie datenschutzrechtliche Fragen zu beantworten und dabei Qualitätsstandards einzuhalten. Dieser Text ersetzt keine Rechtsberatung, sondern bietet grundsätzliche Informationen, gibt Empfehlungen zum Weiterlesen für klassische Fragestellungen und verweist auf gelungene Beispiele im weiteren Feld des wissenschaftsgeleiteten Publizierens.
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    Modelling Archival Hierarchies in Practice: Key Aspects and Lessons Learned
    (Aachen, Germany : RWTH Aachen, 2021) Vafaie, Mahsa; Bruns, Oleksandra; Pilz, Nastasja; Dessì, Danilo; Sack, Harald; Sumikawa, Yasunobu; Ikejiri, Ryohei; Doucet, Antoine; Pfanzelter, Eva; Hasanuzzaman, Mohammed; Dias, Gaël; Milligan, Ian; Jatowt, Adam
    An increasing number of archival institutions aim to provide public access to historical documents. Ontologies have been designed, developed and utilised to model the archival description of historical documents and to enable interoperability between different information sources. However, due to the heterogeneous nature of archives and archival systems, current ontologies for the representation of archival content do not always cover all existing structural organisation forms equallywell. After briefly contextualising the heterogeneity in the hierarchical structure of German archives, this paper describes and evaluates differences between two archival ontologies, ArDO and RiC-O, and their approaches to modelling hierarchy levels and archive dynamics.
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    DDB-KG: The German Bibliographic Heritage in a Knowledge Graph
    (Aachen, Germany : RWTH Aachen, 2021) Tan, Mary Ann; Tietz, Tabea; Bruns, Oleksandra; Oppenlaender, Jonas; Dessì, Danilo; Harald, Sack; Sumikawa, Yasunobu; Ikejiri, Ryohei; Doucet, Antoine; Pfanzelter, Eva; Hasanuzzaman, Mohammed; Dias, Gaël; Milligan, Ian; Jatowt, Adam
    Under the German government’s initiative “NEUSTART Kultur”, the German Digital Library or Deutsche Digitale Bibliothek (DDB) is undergoing improvements to enhance user-experience. As an initial step, emphasis is placed on creating a knowledge graph from the bibliographic record collection of the DDB. This paper discusses the challenges facing the DDB in terms of retrieval and the solutions in addressing them. In particular, limitations of the current data model or ontology to represent bibliographic metadata is analyzed through concrete examples. This study presents the complete ontological mapping from DDB-Europeana Data Model (DDB-EDM) to FaBiO, and a prototype of the DDB-KG made available as a SPARQL endpoint. The suitabiliy of the target ontology is demonstrated with SPARQL queries formulated from competency questions.