Supporting Scientometric Studies with Linked Open Data

ABSTRACT

In Scientometric Studies, measuring scientific indicators is a complex task due to the challenges associated with data collection, organization and linking, especially in the web, where data is distributed in various sources and incompatible formats. These problems can be tackled with the technological and methodological techniques based on the Linked Open Data principles. These principles cover a set of the best practices from the fields of Semantic Web and Open Data to organize, publish and interlink the data on the Web. With the use of those best practices, the data can be accessed and consumed without restrictions, in many applications. This paper addresses the availability of a Qualis historical dataset, according to the mentioned principles. In Scientometric studies, this effort is important for data reuse, taking into the account: measuring an evolution of scientific journals; assisting production of qualitative and quantitative measures of scientific publications; or obtaining relevant information by interlinking and exploring other scientific indicators. The availability of the Qualis dataset is verified by the three use cases. As a result, the Qualis index (historical series 2005-2013) is shared by a web interface for: (i) furthering the data reuse and integration; and (ii) supporting the interoperability and computational processability of the available resources.

Keywords:
Linked Open Data; Scientometrics; Qualis Index; Scientometric Studies; Semantic Web.