Take it personally - A Python library for data enrichment for infometrical 
applications

Seidlmayer, Eva; Galke, Lukas; Melnychuk, Tatyana; Schultz, Carsten; Tochtermann, Klaus; Förstner, Konrad U.

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Take it personally - A Python library for data enrichment for infometrical applications

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Seidlmayer, E., Galke, L., Melnychuk, T., Schultz, C., Tochtermann, K., & Förstner, K. U. (2019). Take it personally - A Python library for data enrichment for infometrical applications. In M. Alam, R. Usbeck, T. Pellegrini, H. Sack, & Y. Sure-Vetter (Eds.), Proceedings of the Posters and Demo Track of the 15th International Conference on Semantic Systems co-located with 15th International Conference on Semantic Systems (SEMANTiCS 2019).

Cite as: https://hdl.handle.net/21.11116/0000-0009-FAA4-4

Abstract

Like every other social sphere, science is inﬂuenced by individual characteristics of researchers. However, for investigations on scientiﬁc networks, only little data about the social background of researchers, e.g. social origin, gender, aﬃliation etc., is available.
This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the
semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata.
The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientiﬁc knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientiﬁc publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities.