Bringing Mathematics to the Web of Data: The Case of the Mathematics Subject Classification

Lange, Christoph; Ion, Patrick; Dimou, Anastasia; Bratsas, Charalampos; Sperber, Wolfram; Kohlhase, Michael; Antoniou, Ioannis

doi:10.1007/978-3-642-30284-8_58

Cited by 16 publications

(15 citation statements)

References 7 publications

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“…We deliver the first implementation of the MSC that is easily comprehensible to machines. It does not only facilitate maintenance and development of novel services, but the rigorous conceptual modeling approach [6] also helped to uncover issues in the MSC conceptualization, which we have now fixed. We are now planning to do three things in parallel: (1) refining the dataset implementation by making the internal structures of the MSC even more explicit 10 and by adopting further best practices for modeling classification schemes in SKOS [9];…”

Section: Discussionmentioning

confidence: 99%

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Reimplementing the Mathematics Subject Classification (MSC) as a Linked Open Dataset

Lange

Ion

Dimou

et al. 2012

Lecture Notes in Computer Science

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Abstract. The Mathematics Subject Classification (MSC) is a widely used scheme for classifying documents in mathematics by subject. Its traditional, idiosyncratic conceptualization and representation makes the scheme hard to maintain and requires custom implementations of search, query and annotation support. This limits uptake e.g. in semantic web technologies in general and the creation and exploration of connections between mathematics and related domains (e.g. science) in particular. This paper presents the new official implementation of the MSC2010 as a Linked Open Dataset, building on SKOS (Simple Knowledge Organization System). We provide a brief overview of the dataset's structure, its available implementations, and first applications.

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Section: Discussionmentioning

confidence: 99%

“…For details about this and about most other aspects of this project presentation, we refer to a full paper published recently[6].…”

mentioning

confidence: 99%

Reimplementing the Mathematics Subject Classification (MSC) as a Linked Open Dataset

Lange

Ion

Dimou

et al. 2012

Lecture Notes in Computer Science

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“…В [9] классификаторы MSC2010 преобразованы в RDF Linked Data с использованием стандартизированного словаря Simple Knowledge Organization System (SKOS, https://www.w3.org/TR/skos-reference/). Это дает возможность присваивать классификаторы не только статьям, но и постам в блогах, рисункам и формулам.…”

Section: системы математической классификации и их приложенияunclassified

Method of automated selection of reviewers of scientific articles, implemented in the scientific journal information system

Махмутович

Константинович

Михайлович

2019

Scientific Conference “Scientific Services &Amp; Internet”

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“…Similarly, the MSC 2010 has been implemented as a Linked Dataset, using the SKOS ontology [33] (cf. [44,162]), an official release being expected in early 2012.…”

Section: Mathematical Metadata Vocabulariesmentioning

confidence: 99%

Ontologies and languages for representing mathematical knowledge on the Semantic Web

Lange

2013

Semantic Web

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Mathematics is a ubiquitous foundation of science, technology, and engineering. Specific areas of mathematics, such as numeric and symbolic computation or logics, enjoy considerable software support. Working mathematicians have recently started to adopt Web 2.0 environments, such as blogs and wikis, but these systems lack machine support for knowledge organization and reuse, and they are disconnected from tools such as computer algebra systems or interactive proof assistants. We argue that such scenarios will benefit from Semantic Web technology. Conversely, mathematics is still underrepresented on the Web of [Linked] Data. There are mathematics-related Linked Data, for example statistical government data or scientific publication databases, but their mathematical semantics has not yet been modeled. We argue that the services for the Web of Data will benefit from a deeper representation of mathematical knowledge. Mathematical knowledge comprises structures given in a logical language-formulae, statements (e.g. axioms), and theories-, a mixture of rigorous natural language and symbolic notation in documents, application-specific metadata, and discussions about conceptualizations, formalizations, proofs, and (counter-)examples. Our review of vocabularies for representing these structures covers ontologies for mathematical problems, proofs, interlinked scientific publications, scientific discourse, as well as mathematical meta-data vocabularies and domain knowledge from pure and applied mathematics. Many fields of mathematics have not yet been implemented as proper Semantic Web ontologies; however, we show that MathML and OpenMath, the standard XML-based exchange languages for mathematical knowledge, can be fully integrated with RDF representations in order to contribute existing mathematical knowledge to the Web of Data. We conclude with a roadmap for getting the mathematical Web of Data started: what datasets to publish, how to interlink them, and how to take advantage of these new connections.

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Bringing Mathematics to the Web of Data: The Case of the Mathematics Subject Classification

Cited by 16 publications

References 7 publications

Reimplementing the Mathematics Subject Classification (MSC) as a Linked Open Dataset

Reimplementing the Mathematics Subject Classification (MSC) as a Linked Open Dataset

Method of automated selection of reviewers of scientific articles, implemented in the scientific journal information system

Ontologies and languages for representing mathematical knowledge on the Semantic Web

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