Abstract
In this paper we discuss how knowledge management can contribute to the analysis of big data by joining enterprise modeling methods with data analyses. The goal of this approach is to enable the seamless interaction and exchange of information between knowledge-oriented representations as provided by enterprise modeling on the one hand and methods for analyzing data on the other hand. For the ...
Abstract
In this paper we discuss how knowledge management can contribute to the analysis of big data by joining enterprise modeling methods with data analyses. The goal of this approach is to enable the seamless interaction and exchange of information between knowledge-oriented representations as provided by enterprise modeling on the one hand and methods for analyzing data on the other hand. For the realization of the approach we revert to techniques of metamodeling. These permit to describe the necessary extensions of enterprise modeling methods and implement them as IT-based tools using metamodeling platforms. For evaluating the feasibility of our approach we describe a generic implementation using the ADOxx metamodeling platform and the R toolkit. In addition, we discuss the application to a use case from the area of business process improvement and the according implementation within the ADOxx-based RUPERT tool.
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