Process aware Data Quality assessment

Data quality (DQ) has been recognized as an important issue for optimal business decisions [TDWI]. Considerable work has been done on improving defected data. However, less attention has been paid to preventing data to become defective at the first place.

On the other hand, business process management becomes more and more relevant in every day business. Currently, there are many standardized business process languages available (e.g., BPMN specification).


Our research addresses the issue of data quality given that data and resources are managed by business processes. In particular, the idea is to find causes of low data quality in the processes that generates the data. Based on the causes, the next goal is to find ways to improve data quality by changing those processes and preventing the data from becoming defective.


[DBLP profile, Google Scholar profile]

  1. O. Savković, E. Marengo, W. Nutt
    Query Stability in Monotonic Data-Aware Business Processes
    ICDT 2016
  2. O. Savković, E. Marengo, W. Nutt
    Query Stability in Monotonic Data-Aware Business Processes [Extended Version] 2016
  3. W. Nutt, S. Paramonov, O. Savković
    Implementing Query Completeness Reasoning
    CIKM 2015
  4. E. Marengo, W. Nutt, O. Savković
    Towards a Theory of Query Stability in Business Processes
    Proc. of the 8th Alberto Mendelzon Workshop on Foundations of Data Management (AMW 2014), 2014, (CEUR Workshop Proceedings)
  5. M. Kacimi, O. Savković, M Manfred
    Clinical-based Prediction of Side Effects in Colon Cancer Chemotherapy
    IEEE Int. Conf. on e-Health Networking, Applications & Services (HealthCom 2013), 2013, pp. 617 – 621
  6. S. Paramonov, N. Werner, O. Savković
    An ASP approach to query completeness reasoning
    Theory and Practice of Logic Programming 13 (4-5) (ICLP Techical Communications 2013), 2013, pp. 1-11
  7. O. Savković, P. Mirza, A. Tomasi, W. Nutt
    Complete approximations of incomplete queries
    Proc. of the VLDB Endowment 6 (12) (VLDB 2013), 2013, pp. 1378-1381
  8. O. Savković, M. Paramita, S. Paramonov, W. Nutt
    MAGIK: managing completeness of data
    Proc. of the 21st ACM Int. Conf. on Information and knowledge management (CIKM 2012), 2012, pp. 2725-2727, ACM
  9. O. Savković, D. Calvanese
    Introducing Datatypes in DL-Lite
    Proc. of the 20th European Conf. on Artificial Intelligence
    (ECAI 2012), 2012, pp. 720-725, IOS Press

  10. O. Savković
    Managing Data Types in Ontology-based Data Access
    Master’s thesis, KRDB Res. Centre, Free Univ. of Bozen-Bolzano, October 2011
    pdf | Abstract | BibTeX