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    14 Years of PID services at the German National Library of Science and Technology (TIB): Connected frameworks, research data and lessons learned from a National Research Library perspective
    (Paris : CODATA, 2017) Kraft, Angelina; Dreyer, Britta; Löwe, Peter; Ziedorn, Frauke
    In an ideal research world, any scientific content should be citable and the coherent content, as well as the citation itself, should be persistent. However, today’s scientists do not only produce traditional research papers – they produce comprehensive digital resources and collections. TIB’s mission is to develop a supportive framework for a sustainable access to such digital content – focusing on areas of engineering as well as architecture, chemistry, information technology, mathematics and physics. The term digital content comprises all digitally available resources such as audiovisual media, databases, texts, images, spreadsheets, digital lab journals, multimedia, 3D objects, statistics and software code. In executing this mission, TIB provides services for the management of digital content during ongoing and for finished research. This includes: • a technical and administrative infrastructure for indexing, cataloguing, DOI registration and licensing for text and digital objects, namely the TIB DOI registration which is active since 2005, • the administration of the ORCID DE consortium, an institutional network fostering the adoption of ORCID across academic institutions in Germany, • training and consultancy for data management, complemented with a digital repository for the deposition and provision of accessible, traceable and citable research data (RADAR), • a Research and Development Department where innovative projects focus on the visualization and the sustainable access to digital information, and • the development of a supportive framework within the German research data community which accompanies the life cycle of scientific knowledge generation and transfer. Its goal is to harmonize (meta)data display and exchange primarily on a national level (LEIBNIZ DATA project).
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    The SciQA Scientific Question Answering Benchmark for Scholarly Knowledge
    (London : Nature Publishing Group, 2023) Auer, Sören; Barone, Dante A.C.; Bartz, Cassiano; Cortes, Eduardo G.; Jaradeh, Mohamad Yaser; Karras, Oliver; Koubarakis, Manolis; Mouromtsev, Dmitry; Pliukhin, Dmitrii; Radyush, Daniil; Shilin, Ivan; Stocker, Markus; Tsalapati, Eleni
    Knowledge graphs have gained increasing popularity in the last decade in science and technology. However, knowledge graphs are currently relatively simple to moderate semantic structures that are mainly a collection of factual statements. Question answering (QA) benchmarks and systems were so far mainly geared towards encyclopedic knowledge graphs such as DBpedia and Wikidata. We present SciQA a scientific QA benchmark for scholarly knowledge. The benchmark leverages the Open Research Knowledge Graph (ORKG) which includes almost 170,000 resources describing research contributions of almost 15,000 scholarly articles from 709 research fields. Following a bottom-up methodology, we first manually developed a set of 100 complex questions that can be answered using this knowledge graph. Furthermore, we devised eight question templates with which we automatically generated further 2465 questions, that can also be answered with the ORKG. The questions cover a range of research fields and question types and are translated into corresponding SPARQL queries over the ORKG. Based on two preliminary evaluations, we show that the resulting SciQA benchmark represents a challenging task for next-generation QA systems. This task is part of the open competitions at the 22nd International Semantic Web Conference 2023 as the Scholarly Question Answering over Linked Data (QALD) Challenge.