A SYSTEMATIC LITERATURE REVIEW OF HOW TO INTRODUCE DATA QUALITY REQUIREMENTS INTO A SOFTWARE PRODUCT DEVELOPMENT

César Guerra-García, Ismael Caballero, Mario Piattini

2010

Abstract

In recent years many organizations have come to realize the importance of maintaining data with the most appropriate levels of data quality when using their information systems (IS). We therefore consider that it is essential to introduce and implement mechanisms into the organizational IS in order to ensure acceptable quality levels in its data. Only by means of these mechanisms, will users be able to trust in the data they are using for the task in hand. These mechanisms must be developed to satisfy their data quality requirements when using specific functionalities of the IS. From our point of view as software engineering researchers, both these data quality requirements and the remaining software requirements must be dealt with in an appropriate manner. Since the goal of our research is to establish means to develop those software mechanisms aimed at managing data quality in IS, we decided to begin by carrying out a survey on related methodological and technical issues to depict the current state of the field. We decided to use the systematic review technique to achieve this goal. This paper shows the principal results of the survey, along with the conclusions reached.

References

  1. Ballou, D. P., R. Y. Wang, et al. (1998). "Modelling Information Manufacturing Systems to Determine Information Product Quality." Management Science 44(4): 462-484.
  2. Becker, D., W. McMullen, et al. (2007). A Flexible and Generic Data Quality Metamodel. International Conference on Information Quality.
  3. Bernes-Lee, T., J. Hendler, et al. (2001). "The Semantic Web." Scientific American.
  4. Bertino, E., C. Dai, et al. (2009). The Challenge of Assuring Data Trustworthiness. Database Systems for Advanced Applications. Springer-Verlag. Volume 5463/2009: 22-33.
  5. Bézivin, J. (2004). "In Search of a Basic Principle for Model Driven Engineering." UPGRADE, Novática. Vol. 2(No.2): 21-24.
  6. Biolchini, J. C. d. A., P. G. Mian, et al. (2007). "Scientific research ontology to support systematic review in software engineering." Adv. Eng. Inform. 21(2): 133- 151.
  7. Caballero, I., A. Caro, et al. (2008). "IQM3: Information Quality Maturity Model." Journal of Universal Computer Science 14: 1-29.
  8. Caballero, I., E. M. Verbo, et al. (2008). DQRDFS:Towards a Semantic Web Enhanced with Data Quality. Web Information Systems and Technologies, Funchal, Madeira, Portugal.
  9. Eppler, M. and M. Helfert (2004). A Classification and Analysis of Data Quality Costs. International Conference on Information Quality, MIT, Cambridge, MA, USA.
  10. Gomes, P., J. Farinha, et al. (2007 ). A data quality metamodel extension to CWM Proceedings of the fourth Asia-Pacific conference on Comceptual modelling - Volume 67 Ballarat, Australia Australian Computer Society, Inc.: 17-26
  11. ISO-25012 (2008). "ISO/IEC 25012: Software Engineering-Software product Quality Requirements and Evaluation (SQuaRE)-Data Quality Model."
  12. Karel, R., C. Moore, et al. (2009). "Forrester?s report for Business Process and Application Professionals on Trends 2009: Master Data Management." Forrester.
  13. Laudon, K. C. (1986). "Data Quality and Due Process in Large Interorganizational Record System." Communications of the ACM 29(1): 4-11.
  14. Missier, P., S. Embury, et al. (2006). "Quality views: capturing and exploiting the user perspective on data quality." Proceedings of the 32nd international conference on Very large data bases-Volume 32.
  15. OMG. (2003). "Common Warehouse Metamodel (CWM) Specification v1.1." October, 2008, from http://www.omg.org/docs/formal/03-03-02.pdf [Consultado el: 29-09-2008].
  16. OMG (2003). MDA Guide Version 1.0.1., Object Management Group: 62.
  17. Scannapieco, M., B. Pernici, et al. (2002). IP-UML: Towards a Methodology for Quality Improvement Based on the IP-MAP Framework. International Conference on Information Quality, ICIQ-02.
  18. Shankaranarayan, G., R. Y. Wang, et al. (2000). IP-MAP: Representing the Manufacture of an Information Product. Fifth International Conference on Information Quality (ICIQ'2000), MIT, Cambridge, MA, USA.
  19. Strong, D. M., Y. W. Lee, et al. (1997). "Data Quality in Context." Communications of the ACM 40(5): 103- 110.
  20. Wang, R., V. Storey, et al. (1995). "A Framework for Analysis of Data Quality Research." IEEE Transactions on Knowledge and Data Engineering 7(4).
  21. Wang, R. Y. (1998). "A Product Perspective on Total Data Quality Management." Communications of the ACM 41(2): 58-65.
  22. Wang, R. Y. and S. Madnick (1993). Data Quality Requirements: Analysis and Modelling. Ninth International Conference on Data Engineering (ICDE'93), Vienna, Austria, IEEE Computer Society.
  23. Wang, R. Y., M. Reddy, et al. (1995). "Towards quality data: An attribute-based approach." Journal of Decision Support Systems 13(3-4): 349-372. Data Extraction of the Study
  24. Wang, Richard Y., Reddy, M., Kon, H.. March, 1995. Toward quality data: An attribute-based approach. In: Journal of
Download


Paper Citation


in Harvard Style

Guerra-García C., Caballero I. and Piattini M. (2010). A SYSTEMATIC LITERATURE REVIEW OF HOW TO INTRODUCE DATA QUALITY REQUIREMENTS INTO A SOFTWARE PRODUCT DEVELOPMENT . In Proceedings of the Fifth International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-8425-21-8, pages 12-19. DOI: 10.5220/0002926700120019


in Bibtex Style

@conference{enase10,
author={César Guerra-García and Ismael Caballero and Mario Piattini},
title={A SYSTEMATIC LITERATURE REVIEW OF HOW TO INTRODUCE DATA QUALITY REQUIREMENTS INTO A SOFTWARE PRODUCT DEVELOPMENT},
booktitle={Proceedings of the Fifth International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2010},
pages={12-19},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002926700120019},
isbn={978-989-8425-21-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - A SYSTEMATIC LITERATURE REVIEW OF HOW TO INTRODUCE DATA QUALITY REQUIREMENTS INTO A SOFTWARE PRODUCT DEVELOPMENT
SN - 978-989-8425-21-8
AU - Guerra-García C.
AU - Caballero I.
AU - Piattini M.
PY - 2010
SP - 12
EP - 19
DO - 10.5220/0002926700120019