Skip to main content
Log in

Capturing data quality requirements for web applications by means of DQ_WebRE

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

The number of Web applications which are part of Business Intelligence (BI) applications has grown exponentially in recent years, as has their complexity. Consequently, the amount of data used by these applications has also increased. The larger the number of data used, the greater the chance to make errors is. That being the case, managing data with an acceptable level of quality is paramount to success in any organizational business process. In order to raise and maintain adequate levels of Data Quality (DQ), it is indispensable for Web applications to be able to satisfy specific DQ requirements. To do so, DQ requirements should be captured and introduced into the development process of the Web Application, together with the other software requirements needed in the applications. In the field of Web application development, however, there appears to us to exist a lack of proposals aimed at managing specific DQ software requirements. This paper considers the MDA (Model Driven Architecture) approach and, principally, the benefits provided by Model Driven Web Engineering (MDWE), putting forward a proposal for two artifacts. These consist of a metamodel and a UML profile for the management of Data Quality Software Requirements for Web Applications (DQ_WebRE).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Ballou, D. P., & Pazer, H. L. (2003). Modeling completeness versus consistency tradeoffs in information decision contexts. IEEE Transactions on Knowledge and Data Engineering, 15(1), 240–243.

    Article  Google Scholar 

  • Batini, C., Barone, D., Mastrella, M., Maurino, A., & Ruffini, C. (2007). A Framework and a Methodology for Data Quality Assessment and Monitoring. In 12th International Conference on Information Quality, MIT, Cambridge, MA, November, 10–11.

  • Batini, C., Cappiello, C., Francalanci, C., & Maurino, A. (2009). Methodologies for data quality assessment and improvement. ACM Computing Surveys, 41(3).

  • Becker, D., McMullen, W., & Hetherington-Young, K. (2007). a flexible and generic data quality metamodel. In International Conference on Information Quality.

  • Becker, D., Jaster, J., & Kuperman, J. (2009). Flexible and generic data quality metadata exchange. In International Conference on Information Quality, ICIQ09.

  • Bertino, E., Maurino, A., & Scannapieco, M. (2010). Guest editors’ introduction: data quality in the internet Era. pp. 11–13.

  • Bézivin, J. (2004). In search of a basic principle for model driven engineering. UPGRADE, Novática, 2(2), 21–24.

    Google Scholar 

  • Caballero, I., Verbo, E. M., Calero, C., & Piattini, M. (2007). A data quality measurement information model based on ISO/IEC 15939. In 12th International Conference on Information Quality, MIT, Cambridge, MA, November, 10–11

  • Caro, A., Calero, C., Caballero, I., & Piattini, M. (2008). A proposal for a set of attributes relevant for Web Portal Data Quality. Software Quality Journal.

  • Ceri, S., Fraternali, P., & Bongio, A. (2000). Web Modeling Language (WebML): a modeling language for designing Web sites. Computer Networks, 33(1–6), 137–157.

    Article  Google Scholar 

  • De Castro, V., & Marcos, E. (2009). Towards a service-oriented MDA-based approach to the alignment of business process with IT Systems: from the business model to a web service composition model. International Journal of Cooperative Information Systems, 18(2), 225–260.

    Article  Google Scholar 

  • EasyChair EasyChair Conference System. http://www.easychair.org/. Accessed 14 December 2012.

  • Eppler, M., & Helfert, M. (2004). A classification and analysis of data quality costs. In International Conference on Information Quality, MIT, Cambridge, MA, USA. (pp. 311–325).

  • Escalona, M. J., & Aragón, G. (2008). NDT. A model-driven approach for web requirements. IEEE Transactions on Software Engineering, 34(3), 377–390. doi:10.1109/TSE.2008.27.

    Article  Google Scholar 

  • Escalona, M. J., & Koch, N. (2004). Requirements engineering for web applications: a comparative study. Journal on Web Engineering, 2, 193–212.

    Google Scholar 

  • Escalona, M. J., & Koch, N. (2006). Metamodeling the Requirements of Web Systems. In S. B. Heidelberg (Ed.), Web Information Systems and Technologies (Vol. Volume 1, pp. 267–280, Lecture Notes in Business Information Processing).

  • Fang, X., & Holsapple, C. W. (2011). Impacts of navigation structure, task complexity, and users’ domain knowledge on Web site usability-an empirical study. Information Systems Frontiers, 13(4), 453–469.

    Article  Google Scholar 

  • Guerra-García, C., Caballero, I., & Piattini, M. (2009). DQ-VORD: A methodology for managing and integrating data quality requirements into software requirement specification. In IADIS International Conference on WWW/INTERNET 2009, Rome, Italy, 19–22 November, 2009. (pp. 392–399).

  • Guerra-García, C., Caballero, I., & Piattini, M. (2010). A systematic literature review of how to introduce data quality requirements into a software product development. In 5th. International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE, Athens, Greece, 22–24 July, 2010. (pp. 12–19)

  • Guerra-García, C., Caballero, I., & Piattini, M. (2011). A survey on how to manage specific data quality requirements during information system development. Lecture Notes in Computer Science(Evaluation of Novel Approaches to Software Engineering), To be published.

  • ISO-25012 (2008). ISO/IEC 25012: Software Engineering-Software product Quality Requirements and Evaluation (SQuaRE)-Data Quality Model.

  • Jacobson, I., Booch, G., & Rumbaugh, J. (1999). The unified software development process. Reading: Addison-Wesley.

    Google Scholar 

  • Janjua, N. K., Hussain, F. K., & Hussain, O. K. (2012). Semantic information and knowledge integration through argumentative reasoning to support intelligent decision making. Information Systems Frontiers, 1–26.

  • Kahn, B. K., Strong, D. M., & Wang, R. Y. (2002). Information quality benchmarks: product and service performance. Communications of the ACM, 45(4ve), 184–192.

    Article  Google Scholar 

  • Karel, R., Moore, C., & Coit, C. (2009). Forrester’s report for Business Process and Application Professionals on Trends 2009: Master Data Management. Forrester.

  • Koch, N., & Kraus, A. (2002). The expressive power of UML-based web engineering. Paper presented at the Second Int. Workshop on Web-oriented Software Technology (IWWOST ‘02), Málaga, Spain., June 2002.

  • Laudon, K. C. (1986). Data quality and due process in large interorganizational record system. Communications of the ACM, 29(1), 4–11.

    Article  Google Scholar 

  • Lee, Y. W., Pipino, L. L., Funk, J. D., & Wang, R. Y. (2006). Journey to data quality. Cambridge: Massachussets Institute of Technology.

    Google Scholar 

  • Lucas, A. (2010). Corporate data quality management in context. In 15th International Conference on Information Quality, ICIQ 2010, Little Rock, Arkansas.

  • Meliá, S., & Gómez, J. (2005). Applying Transformations to Model Driven Development of Web applications. In S. B. Heidelberg (Ed.), Perspectives in Conceptual Modeling (Vol. Volume 3770/2005, pp. 63–73, Lecture Notes in Computer Science).

  • OMG (2001). Model Driven Architecture (MDA)- document number ormsc/2001-07-01.

  • OMG (2005a). OCL 2.0 Specification. Version 2.0. (pp. 185): Object Management Group (OMG).

  • OMG (2005b). Unified Modeling Language: Superstructure. Versión 2.0. <http://www.omg.org/docs/formal/05-07-04.pdf>.

  • OMG (2008). MOF QVT Final Adopted Specification. http://www.omg.org/spec/QVT/1.0/ [Accessed in January, 2012].

  • Phan, D. D., & Vogel, D. R. (2010). A model of customer relationship management and business intelligence systems for catalogue and online retailers. Information Management, 47(2), 69–77. doi:10.1016/j.im.2009.09.001.

    Article  Google Scholar 

  • Pipino, L., Lee, Y., & Wang, R. (2002). Data quality assessment. Communications of the ACM, 45(4), 211–218.

    Article  Google Scholar 

  • Sarsfield, S. (2009). The data governance imperative: IT Governance Publishing.

  • Scannapieco, M., & Berti-Équille, L. (2006). Report from the First and Second International Workshops on Information Quality in Information Systems- IQIS 2004 and IQIS 2005 in Conjunction with ACM SIGMOD/PODS Conferences. SIGMOD RECORD, 35(2), 50–52.

    Article  Google Scholar 

  • Shankaranayanan, G., & Cai, Y. (2005). A web services application for the data quality management in the B2B networked environment. In 38th Hawaii International Conference on System Sciences (HICSS-38 2005), Big Island, HI, USA, 3–6 January 2005: IEEE Computer Society.

  • Strong, D., Lee, Y., & Wang, R. (1997). Ten potholes in the road to information quality. IEEE Computer, 38–46.

  • Strong, D. M., Lee, Y. W., & Wang, R. Y. (1997b). Data quality in context. Communications of the ACM, 40(5), 103–110.

    Article  Google Scholar 

  • Wang, R., Storey, V., & Firth, C. (1995). A framework for analysis of data quality research. IEEE Transactions on Knowledge and Data Engineering, 7(4).

Download references

Acknowledgments

This work has been funded by the following projects: PEGASO/MAGO project (MICINN and FEDER, TIN2009-13718-C02-01), IQMNet (TIN2010-09809-E) project which are supported by the Spanish Ministerio de Educación y Ciencia. ENGLOBAS (PII2I09-0147-8235) and ARMONIAS (PII2I09-0223-7948) projects, both of which are supported by the Consejería de Educación y Ciencia of Junta de Comunidades de Castilla-La Mancha.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to César Guerra-García.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Guerra-García, C., Caballero, I. & Piattini, M. Capturing data quality requirements for web applications by means of DQ_WebRE. Inf Syst Front 15, 433–445 (2013). https://doi.org/10.1007/s10796-012-9401-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-012-9401-x

Keywords

Navigation