Publishing a scorecard for evaluating the use of open-access journals using linked data technologies

Abstract

Abstract-Open access journals collect, preserve and publish scientific information in digital form, but it is still difficult not only for users but also for digital libraries to evaluate the usage and impact of this kind of publications. This problem can be tackled by introducing Key Performance Indicators (KPIs), allowing us to objectively measure the performance of the journals related to the objectives pursued. In addition, Linked Data technologies constitute an opportunity to enrich the information provided by KPIs, connecting them to relevant datasets across the web. This paper describes a process to develop and publish a scorecard on the semantic web based on the ISO 2789:2013 standard using Linked Data technologies in such a way that it can be linked to related datasets. Furthermore, methodological guidelines are presented with activities. The proposed process was applied to the open journal system of a university, including the definition of the KPIs linked to the institutional strategies, the extraction, cleaning and loading of data from the data sources into a data mart, the transforming of data into RDF (Resource Description Framework), and the publication of data by means of a SPARQL endpoint using the OpenLink Virtuoso application. Additionally, the RDF data cube vocabulary has been used to publish the multidimensional data on the web. The visualization was made using CubeViz a faceted browser to present the KPIs in interactive charts.

Added Values of Linked Data in Education: A Survey and Roadmap

“…Ref. [55] shows a detailed roadmap, guideline, procedures and tools in the purpose of illustrating what open scientific journals should do to adopt LD technologies and make their open data part of the LOD cloud. It is worth mentioning that ACM, IEEE, and DBLP research publication repositories are part of LOD cloud according to [56].…”

“…The natural following step is extracting data from OER repositories or MOOC providers combined with any necessary cleaning process to generate RDF datasets according to the defined vocabulary-then making interlinking among datasets and enrichment with LOD cloud or other open LD repositories, publishing datasets and providing a SPARQL Endpoint to make data accessible, establishing applications and services to consume and exploit datasets, and providing any needed maintenance, optimization and quality procedures. More details could be found in [2,55] and other works mentioned in this track.…”

“…For cleaning and interlinking instances OpenLink Virtuoso 11 "is a database engine that combines the functionality of RDBMS, virtual databases, RDF triple stores, XML store, web application server and file servers" [55] Storing Pubby 12 Provides LD interface for SPARQL triple stores.…”

“…"is a database engine that combines the functionality of RDBMS, virtual databases, RDF triple stores, XML store, web application server and file servers" [55] platform that "collect information within universities, that can then be opened through LD to others, forming a network of resources from many different universities" [22]. Gnoss.com allows users to discover knowledge from both of Learning Analytics Knowledge (LAK) and Educational Data Mining (EDM) [96].…”