Ontology-Based Data Access for Extracting Event Logs from Legacy Data: The onprom Tool and Methodology

  • Diego Calvanese
  • Tahir Emre Kalayci
  • Marco Montali
  • Stefano Tinella
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 288)

Abstract

Process mining aims at discovering, monitoring, and improving business processes by extracting knowledge from event logs. In this respect, process mining can be applied only if there are proper event logs that are compatible with accepted standards, such as extensible event stream (XES). Unfortunately, in many real world set-ups, such event logs are not explicitly given, but instead are implicitly represented in legacy information systems. In this work, we exploit a framework and associated methodology for the extraction of XES event logs from relational data sources that we have recently introduced. Our approach is based on describing logs by means of suitable annotations of a conceptual model of the available data, and builds on the ontology-based data access (OBDA) paradigm for the actual log extraction. Making use of a real-world case study in the services domain, we compare our novel approach with a more traditional extract-transform-load based one, and are able to illustrate its added value. We also present a set of tools that we have developed and that support the OBDA-based log extraction framework. The tools are integrated as plugins of the ProM process mining suite.

Keywords

Process mining Ontology-based data access Event log extraction Relational database management systems 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Diego Calvanese
    • 1
  • Tahir Emre Kalayci
    • 1
  • Marco Montali
    • 1
  • Stefano Tinella
    • 2
  1. 1.KRDB Research Centre for Knowledge and DataFree University of Bozen-BolzanoBolzanoItaly
  2. 2.EBITmax srlBolzanoItaly

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