Abstract
The labor market is a system that is complex and difficult to manage. To overcome this challenge, the European Union has launched the ESCO project which is a language that aims to describe this labor market. In order to support the spread of this project, its dataset was presented as linked open data (LOD). Since LOD is usable and reusable, a set of conditions have to be met. First, LOD must be feasible and high quality. In addition, it must provide the user with the right answers, and it has to be built according to a clear and correct structure. This study investigates the LOD of ESCO, focusing on data quality and data structure. The former is evaluated through applying a set of SPARQL queries. This provides solutions to improve its quality via a set of rules built in first order logic. This process was conducted based on a new proposed ESCO ontology.
Highlights
Labor market governance is one of Europe’s top priorities
ESCO was born to help someone who studied in Germany, and lived in Greece to work in Italy by the linked open data that achieve semantic interoperability throughout Europe
In order to assess the capability of the current ESCO ontology to being exploited of retrieve valuable information from the related linked open data (LOD), according to [20] we identified a number of assessment queries
Summary
Labor market governance is one of Europe’s top priorities. Market governance is an important challenge because the job market is a complex network involving many diverse actors. To enhance its use and reuse, ESCO has published its dataset as Linked Open Data (LOD). ESCO was born to help someone who studied in Germany, and lived in Greece to work in Italy by the linked open data that achieve semantic interoperability throughout Europe. Several methodologies have been developed to enhance as well as to assess data quality [9]. For these reasons, any Linked Open Data (LOD) has to consider these aspects before being published. In order to solve these issues, this study seeks to make the ESCO LOD more structured and more accurate in providing search results.
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