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Abstract

Im Zuge der Vernetzung und Digitalisierung sind mittlerweile nahezu alle Arten von Information online verfügbar und der Informationsaustausch hat sich in zahlreichen Bereichen radikal gewandelt. Informationen, die früher über gedruckte Medien wie Telefon- und Adressbücher, Straßenkarten und -atlanten oder auch Katalogen für den Bestell-Einzelhandel zur Verfügung gestellt wurden, werden heute in der Regel online und komplett anders strukturiert dargeboten. In der Wissenschaft erfolgt die Kommunikation von Forschungsergebnissen jedoch nach wie vor auf der Basis statischer Text-Dokumente: Forscher erarbeiten Aufsätze und Artikel, die in Online- und Offline-Publikationsmedien als grobgranulare und wenig übergreifend strukturierte Dokumente verfügbar gemacht werden. Als Nutzer einer Bibliothek suchen sie dann ihrerseits nach Dokumenten und müssen zunächst in langen Trefferlisten die passenden Dokumente und in diesen wiederum die für sie relevanten Informationen identifizieren. Auch wenn der Anteil an Publikationen wächst, die im Open Access verfügbar sind, sind die Wissenschaftler weiterhin darauf angewiesen, dass die Bibliothek ihnen ein umfassendes Ressourcenangebot zur Verfügung stellt. Auf diese grundsätzliche Vorgehensweise ist die gesamte Bibliotheks-, Technologie-, Dienst- und Forschungslandschaft derzeit ausgerichtet. Während es früher ausreichte, nur wenige Zeitschriften für das eigene Fach im Blick zu haben, sind Information Overload und Transdisziplinarität nun allgegenwärtige Herausforderungen. Die TIB hat mit der Realisierung eines prototypischen ORKG-Dienstes begonnen.

Footnote

Vgl. auch den Abdruck in: Bredemeier, W. (Hrsg.): Zukunft der Informationswissenschaft: Hat die Infromationswissenschaft eine Zukunft? Grundlagen und Perspektiven - Angebote in der Lehre - An den Fronten der Informationswissenschaft. Berlin: Simon Verlag für Bibliothekswesen 2019. S.170-186.

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Abstract

Die TIB - Leibniz-Informationszentrum Technik und Naturwissenschaften hat ein Positionspapier zum Open Research Knowledge Graph veröffentlicht. 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, Wilma (2018): Towards an Open Research Knowledge Graph.

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Abstract

Wikis are established means for the collaborative authoring, versioning and publishing of textual articles. The Wikipedia project, for example, succeeded in creating the by far largest encyclopedia just on the basis of a wiki. Recently, several approaches have been proposed on how to extend wikis to allow the creation of structured and semantically enriched content. However, the means for creating semantically enriched structured content are already available and are, although unconsciously, even used by Wikipedia authors. In this article, we present a method for revealing this structured content by extracting information from template instances. We suggest ways to efficiently query the vast amount of extracted information (e.g. more than 8 million RDF statements for the English Wikipedia version alone), leading to astonishing query answering possibilities (such as for the title question). We analyze the quality of the extracted content, and propose strategies for quality improvements with just minor modifications of the wiki systems being currently used.

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Abstract

Over the past 3 years, the semantic web activity has gained momentum with the widespread publishing of structured data as RDF. The Linked Data paradigm has therefore evolved from a practical research idea into a very promising candidate for addressing one of the biggest challenges in the area of the Semantic Web vision: the exploitation of the Web as a platform for data and information integration. To translate this initial success into a world-scale reality, a number of research challenges need to be addressed: the performance gap between relational and RDF data management has to be closed, coherence and quality of data published on theWeb have to be improved, provenance and trust on the Linked Data Web must be established and generally the entrance barrier for data publishers and users has to be lowered. In this vision statement we discuss these challenges and argue, that research approaches tackling these challenges should be integrated into a mutual refinement cycle. We also present two crucial use-cases for the widespread adoption of linked data.

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Series

Lecture notes in computer science ; 4825