Discovering job Knowledge through Web Analytics towards facilitating the mobility of European Professionals and Refugees Career Integration (DISKOW)

Improving job knowledge, competencies, and skills of job seekers is essential to increase their employability and reduce the risk of poverty and social exclusion. According to the European Commission (EC), proper development and use of job knowledge, competencies and skills are key factors for success in finding the job and keeping it. In this regard, low and weak job knowledge and skills are identified to be the main obstacles to employability in the EU.

According to Eurostat, the average unemployment rate in the EU has continuously been increased from 29.7% in 2008 to 31.5% in 2013. In Horizon 2020, the EC plans to reverse this trend and increase the employment rate to 75% (on average, maximum of 25% unemployment) and in this regard, the most affected groups with low qualifications are of special interest. In fact, 75 million people in Europe have low or no qualifications and the situation is even worse with big waves of refugees who seriously face the risk of poverty and social exclusion.

In the last few years, substantial efforts have been invested by governments, international organizations, and other institutes to improve our understanding of the dynamics of the labor market. These efforts have resulted in a series of applications, tools, and sources that cover labor demands, supply, or matching and that shed more light on skill gaps and mismatches. ESCO (European skills, competencies, qualifications, and occupations tool developed by the EC), Cedefop’s skills panorama and EURES (EU’s job portal) as well as European Qualifications Framework (EQF) are a few examples of such efforts.

Traditionally, to get more insight into labor demands or supply, researchers and policymakers have relied on interviews, trade publications, surveys, and vacancies. While these traditional data sources have some clear advantages, they are also characterized by limitations that can be addressed by using web-based data instead. The web is a gold mine for job knowledge discovery. Linked open data, job announcements, social media, job search engines, forums, wikis, data streams, and interlinked information are a few examples of such valuable job-related sources on the net.

The main problem in this regard is not in the availability of data and how to retrieve them, but in how to clean, explore, visualize and interpret such a huge volume of various web data. With an aim to streamline this process and make such data suitable for further exploitation (e.g. consument by specialized mobile apps) an open Job Knowledge Base (JKB) is proposed within the scope of the DISKOW project, that can be used by employers, employees, job seekers, labor market experts, and policymakers. Such a JKB contains different types of information such as responsibilities and roles, required competencies (described using existing standards, such as ECF, EQF, etc.), that could be used to develop training and identify priorities, wage information, geographical and demographic trends, cultural issues, demands of the job markets in different domains, job announcement information and rates, job popularity and other useful statistics. The project DISKOW aims at creating a JKB prototype, based on an existing open-source Business Intelligence platform in order to cover the most important factors in this regard such as required job knowledge for a specific job.

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