Evaluating open access journals using Semantic Web technologies and scorecards

Abstract

This paper describes a process to develop and publish a scorecard from an OAJ (Open Access Journal) on the semantic web using Linked Data technologies in such a way that it can be linked to related datasets. Furthermore, methodological guidelines are presented with activities related to each step of the process. The proposed process was applied to a university OAJ from a university, including the definition of the KPIs (Key Performance Indicators) linked to the institutional strategies, the extraction, cleaning and loading of data from the data sources into a data mart, the transformation of data into RDF (Resource Description Framework), and the publication of data by means of a SPARQL endpoint using the Virtuoso software. Additionally, the RDF data cube vocabulary has been used to publish the multi-dimensional data on the Web. The visualization was made using CubeViz, a faceted browser to present the KPIs in interactive charts.

Adding value to Linked Open Data using a multidimensional model approach based on the RDF Data Cube vocabulary

“…In the topic of LOD, multidimensional models are the combination of different datasets, which enable the application of evaluation techniques by means of statistics and indicators [40,41]. According to the W3C, a statistical data set comprises a collection of observations that can be organised into a set of dimensions, attributes and measures, known as components [37].…”

“…Literature also contains some examples of the use of multidimensional models and Linked Data [43,41]. In [44,45], a new vocabulary is proposed as an extension of RDF Data Cube vocabulary that supports advanced OLAP operations, such as rollup, slice, dice, and drill-across, using standard SPARQL queries.…”