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| − | |Referiert= | + | |Referiert=Ja |
| − | |Title=Leveraging Mathematical Subject Information to Enhance Bibliometric | + | |Title=Leveraging Mathematical Subject Information to Enhance Bibliometric Data |
|Year=2017 | |Year=2017 | ||
|Month=Mai | |Month=Mai | ||
|Booktitle=Proc. of 1st Scientometrics Workshop 2017, co-located with 14th ESWC 2017 | |Booktitle=Proc. of 1st Scientometrics Workshop 2017, co-located with 14th ESWC 2017 | ||
| − | |Publisher= | + | |Publisher=CEUR Workshop Proceedings |
| + | |Volume=1878 | ||
}} | }} | ||
{{Publikation Details | {{Publikation Details | ||
|Abstract=The field of mathematics is known to be especially challenging from a bibliometric point of view. Its bibliographic metrics are especially sensitive to distortions and are heavily influenced by the subject and its popularity. Therefore, quantitative methods are prone to misrepresentations, and need to take subject information into account. In this paper we investigate how the mathematical bibliography of the abstracting and reviewing service Zentralblatt MATH (zbMATH) could further benefit from the inclusion of mathematical subject information MSC2010. Furthermore, the mappings of MSC2010 to Linked Open Data resources have been upgraded and extended to also benefit from semantic information provided by DBpedia. | |Abstract=The field of mathematics is known to be especially challenging from a bibliometric point of view. Its bibliographic metrics are especially sensitive to distortions and are heavily influenced by the subject and its popularity. Therefore, quantitative methods are prone to misrepresentations, and need to take subject information into account. In this paper we investigate how the mathematical bibliography of the abstracting and reviewing service Zentralblatt MATH (zbMATH) could further benefit from the inclusion of mathematical subject information MSC2010. Furthermore, the mappings of MSC2010 to Linked Open Data resources have been upgraded and extended to also benefit from semantic information provided by DBpedia. | ||
| + | |Download=article-04.pdf | ||
| + | |Link=https://ceur-ws.org/Vol-1878/article-04.pdf | ||
|Forschungsgruppe=Information Service Engineering | |Forschungsgruppe=Information Service Engineering | ||
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Aktuelle Version vom 17. November 2022, 17:06 Uhr
Leveraging Mathematical Subject Information to Enhance Bibliometric Data
Leveraging Mathematical Subject Information to Enhance Bibliometric Data
Published: 2017
Mai
Buchtitel: Proc. of 1st Scientometrics Workshop 2017, co-located with 14th ESWC 2017
Ausgabe: 1878
Verlag: CEUR Workshop Proceedings
Referierte Veröffentlichung
BibTeX
Kurzfassung
The field of mathematics is known to be especially challenging from a bibliometric point of view. Its bibliographic metrics are especially sensitive to distortions and are heavily influenced by the subject and its popularity. Therefore, quantitative methods are prone to misrepresentations, and need to take subject information into account. In this paper we investigate how the mathematical bibliography of the abstracting and reviewing service Zentralblatt MATH (zbMATH) could further benefit from the inclusion of mathematical subject information MSC2010. Furthermore, the mappings of MSC2010 to Linked Open Data resources have been upgraded and extended to also benefit from semantic information provided by DBpedia.
Download: Media:article-04.pdf
Weitere Informationen unter: Link
Information Service Engineering