Abstract

Abstract Providing data for data analysis projects is one core task of automation technology, however, it still has to be done with a lot of manual effort. One challenge is to keep the meaning of data remain interpretable within or across multiple software environments so that provider and user of data share a common understanding of the transferred data. It is acknowledged that machine interpretable metadata is one crucial building block for reaching this goal. However, in industrial automation and information systems today, exporting and utilizing data coupled with metadata is still not a common practice. Therefore, we propose a general concept for extracting metadata and utilizing it in data analytics applications, which may help with system design in the future. The concept is prototypically implemented regarding the structural metadata for tabular data.

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