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- ItemConnecting Islands: Bridging zbMATH and DLMF with Scholix, a blueprint for connecting expert knowledge systems(Berlin : EMS Press, 2021) Cohl, Howard S.; Teschke, Olaf; Schubotz, MoritzThis paper reports on the recently launched zbMATH Links API. We discuss its potential based on the initial link partner, the National Institute of Standards and Technology Digital Library of Mathematical Functions. As the API provides machine readable data in the links, we show how one can use data from both sources for further analysis. To exemplify the simplicity, we also show how one can use zbMATH’s link data in Jupyter notebooks.
- ItemzbMATH Open: API Solutions and Research Challenges(Aachen, Germany : RWTH Aachen, 2021) Petrera, Matteo; Trautwein, Dennis; Beckenbach, Isabel; Ehsani, Dariush; Müller, Fabian; Teschke, Olaf; Gipp, Bela; Schubotz, Moritz; Balke, Wolf-Tilo; de Waard, Anita; Fu, Yuanxi; Hua, Bolin; Schneider, Jodi; Song, Ningyuan; Wang, XiaoguangWe present zbMATH Open, the most comprehensive collection of reviews and bibliographic metadata of scholarly literature in mathematics. Besides our website zbMATH.org which is openly accessible since the beginning of this year, we provide API endpoints to offer our data. APIs improve interoperability with others, i.e., digital libraries, and allow using our data for research purposes. In this article, we (1) illustrate the current and future overview of the services offered by zbMATH; (2) present the initial version of the zbMATH links API; (3) analyze potentials and limitations of the links API based on the example of the NIST Digital Library of Mathematical Functions; (4) and finally, present thezbMATHOpen dataset as a research resource and discuss connected open research problems.
- ItemMathematics in Wikidata(Aachen, Germany : RWTH Aachen, 2021) Scharpf, Philipp; Schubotz, Moritz; Gipp, Bela; Kaffee, Lucie-Aimée; Razniewski, Simon; Hogan, AidanDocuments from Science, Technology, Engineering, and Mathematics (STEM) disciplines usually contain a signicant amount of mathematical formulae alongside text. Some Mathematical Information Retrieval (MathIR) systems, e.g., Mathematical Question Answering (MathQA), exploit knowledge from Wikidata. Therefore, the mathematical information needs to be stored in items. In the last years, there have been efforts to define several properties and seed formulae together with their constituting identifiers into Wikidata. This paper summarizes the current state, challenges, and discussions related to this endeavor. Furthermore, some data mining methods (supervised formula annotation and concept retrieval) and applications (question answering and classification explainability) of the mathematical information are outlined. Finally, we discuss community feedback and issues related to integrating Mathematical Entity Linking (MathEL) into Wikidata and Wikipedia, which was rejected in 33% and 12% of the test cases, for Wikidata and Wikipedia respectively. Our long-term goal is to populate Wikidata, such that it can serve a variety of automated math reasoning tasks and AI systems.