Abstract
To succeed in their tasks, users need to manage data with the most adequate quality levels possible according to specific data quality models. Typically, data quality assessment consists of calculating a synthesizing value by means of a weighted average of values and weights associated with each data quality dimension of the data quality model. We shall study not only the overall perception of the level of importance for the set of users carrying out similar tasks, but also the different issues that can influence the selection of the data quality dimensions for the model. The core contribution of this paper is a framework for representing and managing data quality models using social networks. The framework includes a proposal for a data model for social networks centered on data quality (DQSN), and an extensible set of operators based on soft-computing theories for corresponding operations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wang, R.Y.: A Product Perspective on Total Data Quality Management. Communications of the ACM 41(2), 58–65 (1998)
Cappiello, C., Francalanci, C., Pernici, B.: Data quality assessment from the user’s perspective. In: International Workshop on Information Quality in Information Systems (IQIS 2004), Paris, Francia, pp. 68–73. ACM, New York (2004)
Wang, R., Strong, D.: Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems 12(4), 5–33 (1996)
Zadeh, L.: From Computing with Numbers to Computing with Words-From Manipulation of Measurements to Manipulation of Perceptions. Fuzzy Control: Theory and Practice (2000)
Ding, L., Zhou, L., Finin, T., Joshi, A.: How the Semantic Web is Being Used: An Analysis of FOAF Documents. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS 2005) - Track 4, vol. 04, p. 113. IEEE Computer Society, Los Alamitos (2005)
Caballero, I., Verbo, E.M., Calero, C., Piattini, M.: A Data Quality Measurement Information Model based on ISO/IEC 15939. In: 12th International Conference on Information Quality. MIT, Cambridge (2007)
Batini, C., Scannapieco, M.: Data Quality: Concepts, Methodologies and Techniques. In: Data-Centric Systems and Applications. Springer, Heidelberg (2006)
Even, A., Shankaranarayanan, G.: Utility-driven assessment of data quality. SIGMIS Database 38(2), 75–93 (2007)
Caballero, I., Verbo, E.M., Calero, C., Piattini, M.: DQRDFS:Towards a Semantic Web Enhanced with Data Quality. In: Web Information Systems and Technologies, Funchal, Madeira, Portugal, pp. 178–183 (2008)
Cappiello, C., Francalanci, C., Pernici, B., Martini, F.: Representation and Certification of Data Quality on the Web. In: 9th International Conference on Information Quality, pp. 402–417. MIT, Cambridge (2004)
Lassila, O., Hendler, J.: Embracing “Web 3.0”. IEEE Internet Computing 11(3), 90–93 (2007)
DCMI, Dublin Core Metadata Element Set, Version 1.1 (2008), http://dublincore.org/documents/dces/#DCTERMS
Brickley, D., Miller, L.: FOAF Vocabulary Specification 0.91 (2007), http://xmlns.com/foaf/spec
García, F., Bertoa, M.F., Calero, C., Vallecillo, A., Ruiz, F., Genero, M.: Towards a consistent terminology for software measurement. Information and Software Technology 48(8), 631–644 (2006)
Strong, D.M., Lee, Y.W., Wang, R.Y.: Data Quality in Context. Communications of the ACM 40(5), 103–110 (1997)
Zhang, D., Lowry, P.B., Zhou, L., Fu, X.: The impact of Individualism-Collectivism, Social Presence, and Group Diversity on Group Decision Making under majority influence. Journal on Management Information System 23(4), 53–80 (2007)
Pipino, L., Lee, Y., Wang, R.: Data Quality Assessment. Communications of the ACM 45(4), 211–218 (2002)
Pasi, G., Yager, R.: Modeling the concept of majority opinion in group decision making. Information Sciences 176(4), 390–414 (2006)
Yager, R., Filev, D.: Induced ordered weighted averaging operators. Part B, IEEE Transactions on Systems, Man and Cybernetics 29(2), 141–150 (1999)
Herrera-Viedma, E., Herrera, F., Martinez, L., Herrera, J.C., Lopez, A.G.: Incorporating filtering techniques in a fuzzy linguistic multi-agent model for information gathering on the web. Fuzzy Sets and Systems. Web Mining Using Soft Computing 148(1), 61–83 (2004)
Chiclana, F., Herrera-Viedma, E., Herrera, F., Alonso, S.: Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations. European Journal of Operational Research 182(1), 383–399 (2007)
Jamali, M., Abolhassani, H.: Different Aspects of Social Network Analysis. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, pp. 66–72. IEEE Computer Society, Los Alamitos (2006)
Stivilia, B.: A Model for Information Quality Change. In: 12th International Conference on Information Quality, pp. 39–49. MIT, Cambridge (2007)
DeAmicis, F., Barone, D., Batini, C.: An Analytical Framework to analyze Dependencies among data Quality Dimensions. In: ICIQ 2006. MIT, Cambridge (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Caballero, I., Verbo, E., Serrano, M., Calero, C., Piattini, M. (2009). Tailoring Data Quality Models Using Social Network Preferences. In: Chen, L., Liu, C., Liu, Q., Deng, K. (eds) Database Systems for Advanced Applications. DASFAA 2009. Lecture Notes in Computer Science, vol 5667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04205-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-04205-8_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04204-1
Online ISBN: 978-3-642-04205-8
eBook Packages: Computer ScienceComputer Science (R0)