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- ItemTowards an Open Research Knowledge Graph(Zenodo, 2018) Auer, Sören; Blümel, Ina; Ewerth, Ralph; Garatzogianni, Alexandra; Heller,, Lambert; Hoppe, Anett; Kasprzik, Anna; Koepler, Oliver; Nejdl, Wolfgang; Plank, Margret; Sens, Irina; Stocker, Markus; Tullney, Marco; Vidal, Maria-Esther; van Wezenbeek, WilmaThe document-oriented workflows in science have reached (or already exceeded) the limits of adequacy as highlighted for example by recent discussions on the increasing proliferation of scientific literature and the reproducibility crisis. Despite an improved and digital access to scientific publications in the last decades, the exchange of scholarly knowledge continues to be primarily document-based: Researchers produce essays and articles that are made available in online and offline publication media as roughly granular text documents. With current developments in areas such as knowledge representation, semantic search, human-machine interaction, natural language processing, and artificial intelligence, it is possible to completely rethink this dominant paradigm of document-centered knowledge exchange and transform it into knowledge-based information flows by representing and expressing knowledge through semantically rich, interlinked knowledge graphs. The core of the establishment of knowledge-based information flows is the distributed, decentralized, collaborative creation and evolution of information models, vocabularies, ontologies, and knowledge graphs for the establishment of a common understanding of data and information between the various stakeholders as well as the integration of these technologies into the infrastructure and processes of search and knowledge exchange in the research library of the future. By integrating these information models into existing and new research infrastructure services, the information structures that are currently still implicit and deeply hidden in documents can be made explicit and directly usable. This revolutionizes scientific work because information and research results can be seamlessly interlinked with each other and better mapped to complex information needs. As a result, scientific work becomes more effective and efficient, since results become directly comparable and easier to reuse. In order to realize the vision of knowledge-based information flows in scholarly communication, comprehensive long-term technological infrastructure development and accompanying research are required. To secure information sovereignty, it is also of paramount importance to science – and urgency to science policymakers – that scientific infrastructures establish an open counterweight to emerging commercial developments in this area. The aim of this position paper is to facilitate the discussion on requirements, design decisions and a minimum viable product for an Open Research Knowledge Graph infrastructure. TIB aims to start developing this infrastructure in an open collaboration with interested partner organizations and individuals.
- ItemVoraussetzungen und Anwendungspotentiale einer präzisen Sacherschließung aus Sicht der Wissenschaft(Zenodo, 2018) Kasprzik, AnnaThesen: Intellektuelle und automatisierte Sacherschließung müssen ineinandergreifen – tief erschlossene Kerne, die für eine Skalierung durch automatisierte Methoden optimiert sind. Die Qualität der Sacherschließung in Titeldaten lässt sich durch hochqualitative Normdaten verbessern. Automatisierung: Nachhaltige Mischung von statistischen/heuristischen und semantischen/logischen Methoden. Eine Transformation hin zu interoperablen Semantic-Web-Formaten öffnet Möglichkeiten zur Qualitätssteigerung durch erleichterte Nachnutzung in den Fachcommunities.
- ItemLost in translation – challenges of tailoring VIVO to the needs of the German scholarly landscape(Hannover : Technische Informationsbibliothek, 2017) Hauschke, Christian; Barber, Martin; Kasprzik, Anna; Walther, TatianaEvery time a research information system is implemented in an academic institution there is a need to adjust the software to local needs. If a system has its roots in a different country, the adjustments can be more comprehensive. In this case, the VIVO ontology and a lot of the underlying assumptions, which are based on the realities of the US scholarly landscape, must be “tailored” to be able to depict “German” academic reality. The differences concern both the meaning of the translated terms and the usage of the terms in the common parlance. The prominent examples for such kind of terms are grants and faculties. ‘Grant’ is an essential concept to describe the funding of research projects. Universities are divided into colleges and schools. The concepts for the description of research funding in Germany are completely different, and universities are usually divided into ‘Fakultäten’ and ‘Lehrstühle’. Furthermore, terms like ‘faculty’, or ‘grant’ are not being used consistently in German academic institutions. On the other hand some concepts which are important for representing the German academic landscape are missing in the VIVO Ontology. There are ongoing efforts to add missing classes and properties. The extension of the VIVO ontology with concepts as universal and interoperable as possible, and which are typical for Germany also requires broad agreement between German VIVO applicants. Due to the above mentioned issues, it was necessary, that, actors from different German institutions build a network to collaborate on these problems. This collaboration takes place in a number of working groups, calls and on GitHub. It has been resulted in a general ontology extension (VIVO-DE) and several drafts of the translation of the VIVO Ontology. Another common task is the translation of the VIVO application files into German and the constant updating of this translation with every new VIVO version. The 'Kerndatensatz Forschung' (The Research Core Dataset - a data model for research reporting) as an extension of the VIVO Ontology is one of the current tasks, which is collaborated on as well. This talk concerns the challenges, efforts and tools of the German VIVO community to address the described issues.
- ItemLinked Data & Ontologien – Teil 2: Ontologien(Zenodo, 2018) Kasprzik, AnnaEinführung in die wichtigsten Begrifflichkeiten rund um die Themen Linked Data und Ontologien inklusive Übung in Ontologie-Erstellung.
- ItemVIVO-DE-Extension und VIVO-KDSF – Ontologien für den deutschsprachigen Raum(Zenodo, 2017) Kasprzik, AnnaDer Aufbau einer deutschsprachigen Version der Fachinformationssystem-Software VIVO ist nicht so einfach, da sich auf allen Ebenen des Systems sprachspezifische Elemente finden -- von der Anzeige bis hin zu den enthaltenen Ontologien -- und da eine direkte Übersetzung aufgrund kultureller Unterschiede in den Wissenschaftslandschaften oft nicht möglich ist. In dieser Präsentation werden die entsprechenden Aktivitäten der deutschsprachigen VIVO-Community vorgestellt und es wird zur Beteiligung aufgerufen.
- ItemProjektvorhaben TEASER - Entwicklung einer Plattform für die kollaborative Thesauruspflege und -verknüpfung am Beispiel „Industrie 4.0“(Hannover : Technische Informationsbibliothek, 2017) Kasprzik, Anna[no abstract available]
- ItemMethoden und Denkweisen aus der Theoretischen Informatik in Bibliotheken(Zenodo, 2017) Kasprzik, AnnaPraxisbericht einer Formalsprachlerin aus dem Arbeitsalltag in der Forschungs- und Entwicklungsabteilung einer Bibliothek.
- ItemKnowledge organization systems in mathematics and in libraries(Zenodo, 2017) Kasprzik, AnnaBased on the project activities planned in the context of the Specialized Information Service for Mathematics (TIB Hannover, FAU Erlangen, L3S, SUB Göttingen) we give an overview over the history and interplay of subject cataloguing in libraries, the development of computerized methods for metadata processing and the rise of the Semantic Web. We survey various knowledge organization systems such as the Mathematics Subject Classification, the German Authority File, the clustering International Authority File VIAF, and lexical databases such as WordNet and their potential use for mathematics in education and research. We briefly address the difference between thesauri and ontologies and the relations they typically contain from a linguistic perspective. We will then discuss with the audience how the current efforts to represent and handle mathematical theories as semantic objects can help deflect the decline of semantic resource annotation in libraries that has been predicted by some due to the existence of highly performant retrieval algorithms (based on statistical, neuronal, or other big data methods). We will also explore the potential characteristics of a fruitful symbiosis between carefully cultivated kernels of semantic structure and automated methods in order to scale those structures up to the level that is necessary in order to cope with the amounts of digital data found in libraries and in (mathematical) research (e.g., in simulations) today.