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An Extension of ToscanaJ for FCA-based Data Analysis over Triple Stores

Classical Business Intelligence (BI) solutions provide different means like OLAP, data mining or case based reasoning to explore structured data. The data is usually stored in dedicated repositories like data warehouses and then explored by standard BI means, which are usually based on mathematical statistics and provide a quantitative analysis of the data. In this paper, we complement this approach in two respects. First of all, FCA, as a qualitative approach for data analysis, is used for analyzing the data. Second, the analyzed data is not stored in a data warehouse, but in a triple store instead. To make this possible, the existing FCA-tool ToscanaJ has been extended in order to act on triple stores. The approach in this paper is exemplified on a dataset of documents crawled from the SAP community network.