Big data and the complexity of labour market policies: new approaches in regional and local labour market monitoring for reducing skills mismatches (Munich, 2015)
"The experience of regional and lo cal labour market observatorie s shows that information on some as- pects of the labour market – such as the demand for skilled lab our in certain sectors or spatial units – is difficult to obtain. In the rec ent years, ICT-related innovatio ns have created new forms and types of data that can be used for enhancing the efficiency in several areas of economic activity. So far, the vast amount of unstructured data cont ained in the World Wide Web – B ig Data – has been largely unexploit- ed. However, as the available te chnology provides increasingly cost-effective solutions, it has become possible to provide services t hat have formerly been too expens ive. Therefore, applying Big Data in la- bour market monitoring can provide innovative insights into the functioning of labour markets. Also the process data of Public Employment Services or Statistical Offic es constitute a promising source of large amounts of data. The results of the analyses based on the diffe rent sources of data can be used to im- prove the efficiency of the l abour market at large and the prov ision of services by governments and pri- vate enterprises. However, the attempts to use Bi g Data in the context of labour market monitoring have been relatively rare so far, even though a growing interest can be observed amo ng researchers and practitioners alike. Against this background, the iss ues of collecting, elaborating, analysing and disseminating the infor- mation available on the Web urgently needed to be addressed – a s did the associated ethical and legal issues concerned with data ownersh ip and protection. This year’ s Anthology of the EN RLMM covers these issues from the viewpoint of labour market researchers an d practitioners in labour market observa- tories from different European r egions and localities. The cont ributions provide first insights into new models and tools of labour marke t monitoring based on the usage of Big Data. "