Using publications linked open data to define organizational policies

Using publications linked open data to define organizational policies

Автор: Muhammad Ahtisham Aslam

Журнал: International Journal of Information Engineering and Electronic Business @ijieeb

Статья в выпуске: 5 vol.10, 2018 года.

Бесплатный доступ

Researchers around the world are publishing their scientific research results in different forms such as books, journal articles, reference works and project reports. Publishers of these scientific documents usually describe them by using metadata for organizational purposes. This metadata provides a rich information about scientific documents that can be used for analysis purposes such as measuring the impact of researchers and research centers. It can also be used to find scientific documents published in domain of some ones interest, which ultimately can be used to raise the state of the art to the next level. Scientific publications metadata can also be used to analyze the quality and directions of common and highly cited individuals and organizations, and based on this analysis other individuals and organizations can define directions for their future work and research. However, the main limitation of this metadata is that it is available in different formats that might not facilitate the analysis of scientific documents. Therefore, in this paper we clarify that how our SPedia knowledge base (a semantic based knowledge base of scientific publications metadata which we extracted by using SpringerLink as information source) facilitates the analysis of scientific data for policy making. We discuss different kind of questions that can be answered through SPedia knowledge base and we show that how results of these questions can be used to analyze the performance of individuals as well as organizations. We also show that how results of such analysis can help in making organizational policies regarding future research directions.

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Linked open data, policy making, RDF, knowledge representation, data analysis, reasoning

Короткий адрес: https://sciup.org/15016145

IDR: 15016145   |   DOI: 10.5815/ijieeb.2018.05.02

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