Value for users
For end-users it makes a big difference: rather than depending mostly on skills and jobs information and data collected months before, it is now possible to self-navigate in an platform (interface) with wide (holistic) coverage of occupational and skills data, visualised according to the user’s selected parameters (fine-grained, geo-localised, interlinked with other datasets), and based on frequent data updates from various sources (real time).
Labour market intelligence using Big Data analytics make a difference for end-users. The power of new visualization tools and the interactive online information platforms for end-users are changing the way people get and use information on skills, qualifications, occupations and jobs.
This transformation of LMI is happening now, and its potentialities as well as open challenges are yet to be fully comprehended.
Online tools and services such as EURES, Europass, the EU Skills Panorama, public and private job boards collect such data. One of the prominent Big Data projects in the context of LMI is the ongoing project Real-time labour market information and skill requirements of the European Centre for the Development of Vocational Training (Cedefop). Results for 18 EU Member States are already available on the new platform: Skills-OVATE.
Skills-OVATE: Online Vacancy Analysis Tool for Europe
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Cedefop works on a vast database and visualisation tool based on analysis of millions of online job vacancies (OJVs) of European Union (EU) Member States - OVATE: see here. The tool presents data collected from July 2018 until March 2019 in Austria, Belgium, Czech Republic, Denmark, Germany, Hungary, Spain, Finland, France, Italy, Ireland, Luxembourg, the Netherlands, Poland, Portugal, Sweden, Slovakia and the United Kingdom. Other EU MS will be included in 2019. |
For more information on the visualization of results of Skills-OVATE – go to section “EU specific experiences” of this station.
WollyBi – navigating the platform!
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WollyBI Firstly, the user has to select the occupations group from the first ISCO level down to the third one and some other parameters, such as the geographical area and the time horizon of the analysis. The larger the size of the bullets, the greater the number of occupations in the particular group. A first report showing the results for the chosen occupations group is returned. Once the user selects an occupation for deep exploration, a range of information is returned, including the name of the occupation, its ISCO code, its definition according to the ISCO taxonomy, the experience required, the contract typology, the top five sub-sectors and a list of top five skills (both hard and soft). A demo video of WollyBI in action on the occupation dimension is available below:
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