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Towards data quality runtime verification

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Konferencja
Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
Języki publikacji
EN
Abstrakty
EN
This paper discusses data quality checking during business process execution by using runtime verification. While runtime verification verifies the correctness of business process execution, data quality checks assure that particular process did not negatively impact the stored data. Both, runtime verification and data quality checks run in parallel with the base processes affecting them insignificantly. The proposed idea allows verifying (a) if the process was ended correctly as well as (b) whether the results of the correct process did not negatively impact the stored data in result of its modification caused by the specific process. The desired result will be achieved by use of domain specific languages that would describe runtime verification and data quality checks at every stage of business process execution.
Rocznik
Tom
Strony
639--643
Opis fizyczny
Bibliogr. 13 poz., rys.
Twórcy
  • Faculty of Computing University of Latvia, Latvia
  • DIVI Grupa Ltd, Latvia
  • Faculty of Computing University of Latvia, Latvia
autor
  • DIVI Grupa Ltd, Latvia
Bibliografia
  • 1. El Hadji Bassirou Toure, I. Fall, A. Bah, M. S. Camara, Megamodel-based Management of Dynamic Tool Integration in Complex Software Systems. In FedCSIS Position Papers, 2016, pp. 211-218, http://dx.doi.org/10.15439/2016F585.
  • 2. I. Oditis, J. Bicevskis, Asynchronous Runtime Verification of Business Processes: Proof of Concept. International Journal of Simulation-Systems, Science & Technology, 2015, 16(6), 1-11, http://dx.doi.org/10.5013/IJSSST.a.16.06.06.
  • 3. J. Bicevskis, Z. Bicevska, A. Nikiforova, I. Oditis, An Approach to Data Quality Evaluation. In 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS), IEEE, 2018, pp. 196-201, http://dx.doi.org/10.1109/SNAMS.2018.8554915.
  • 4. J. Bicevskis, Z. Bicevska, A. Nikiforova, I. Oditis, Data quality evaluation: a comparative analysis of company registers’ open data in four European countries. In Communication Papers of the Federated Conference on Computer Science and Information Systems (FedCSIS), 2018, pp. 197-204, http://dx.doi.org/10.15439/2018F92.
  • 5. A. Coronato, A. Testa, Approaches of Wireless sensor network dependability assessment. In 2013 Federated Conference on Computer Science and Information Systems, IEEE, 2013, pp. 881-888.
  • 6. A. Nikiforova, Open Data Quality Evaluation: A Comparative Analysis of Open Data in Latvia. Baltic Journal of Modern Computing, 2018, 6(4), 363-386, https://doi.org/10.22364/bjmc.2018.6.4.04.
  • 7. A. Nikiforova, J. Bicevskis, An Extended Data Object-driven Approach to Data Quality Evaluation: Contextual Data Quality Analysis. In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, 274-281, 2019, http://dx.doi.org/10.5220/0007838602740281.
  • 8. A. Nikiforova, Analysis of Open Health Data Quality Using Data Object-Driven Approach to Data Quality Evaluation: Insights from a Latvian Context. In IADIS International Conference e-Health 2019, Part of the IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2019, IADIS
  • 9. G. C. Deka, NoSQL: database for storage and retrieval of data in cloud, Ed. CRC Press, 2017, https://doi.org/10.1201/9781315155579.
  • 10. C. Gröger, F. Niedermann, B. Mitschang. Data mining-driven manufacturing process optimization. In Proceedings of the world congress on engineering, 2012, Vol. 3, pp. 4-6.
  • 11. S. Khurshid, C. S. Păsăreanu, W. Visser, Generalized symbolic execution for model checking and testing. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Springer, Berlin, Heidelberg, 2003, pp. 553-568, https://doi.org/10.1007/3-540-36577-X_40.
  • 12. E. Ziemba, T. Papaj, D. Descours, Assessing the quality of e-government portals-the Polish experience. In 2014 Federated Conference on Computer Science and Information Systems, IEEE, 2014, pp. 1259-1267, http://dx.doi.org/10.15439/2014F121.
  • 13. A. Karabegovic, M. Ponjavic, Geoportal as decision support system with spatial data warehouse. In 2012 Federated Conference on Computer Science and Information Systems (FedCSIS), IEEE, 2012, pp. 915-918, http://dx.doi.org/10.13140/RG.2.2.26385.68963.
Uwagi
1. Track 4: Information Systems and Technology
2. Technical Session: 14th Conference on Information Systems Management
3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f85ffcbf-75cb-4526-89cd-5ecb61a40812
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