Abstract
(Big) Data analysis techniques are able to mine hidden correlations in data sets and/or data streams. Based on identified correlations, a causality analysis can generate new knowledge about happenings in a digitalised environment such as in smart manufacturing systems. Such knowledge can be suitable for further exploitation e.g. in system observation, diagnosis or optimization. However — in general, (Big) Data analysis of complex systems needs highly trained data scientists and application domain experts to define objectives and to perform the analysis of the data (streams). One research objective in smart manufacturing is the unification and provision of semantical meta data which describe structures, abilities, specifications, life-cycle information, etc. of a cyber-physical system (CPS), enrichable with dynamic context information (as the current location of a mobile CPS). This work describes an approach to use such meta-data and (dynamic) context data to support the data preparation phase (search, filter, select and prepare data (streams)) through a semantical supported CPS Data Marketplace.
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