Meta-model based knowledge discovery

Abstract

Data acquisition and data mining are often seen as two independent processes in research. We introduce a meta-information based, highly generic data acquisition system which is able to store data of almost arbitrary structure. Based on the meta-information we plan to apply data mining algorithms for knowledge retrieval. Furthermore, the results from the data mining algorithms will be used to apply plausibility checks for the subsequent data acquisition, in order to maintain the quality of the collected data. So, the gap between data acquisition and data mining shall be decreased.