Abstract
Access to multisource heterogeneous data is a fundamental research issue in a variety of contexts, including syndicated data retrieval, Web service selection and cooperative information systems. In these variable contexts, the brokering approach to multisource data access provides greater flexibility with respect to the more traditional data integration. The general brokering model assumes that the broker is submitted a query and has the responsibility to optimize the response along specified parameters such as time efficiency, completeness, and consistency. This paper takes a data quality perspective on data brokering and considers data accuracy. Furthermore, the data quality literature assumes that metadata are associated with data to describe their quality. Metadata support data selection without viewing and assessing data directly. On the contrary, previous brokering approaches view data. This paper compares previous results with those of a brokering approach based on metadata which assumes that actual data are transparent to the broker. Testing results comparing the delta between the data visibility and transparency approaches to data brokering are presented.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11914853_71.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ardagna, D., Cappiello, C., Comuzzi, M., Francalanci, C., Pernici, B.: A Broker For Selecting And Provisioning High Quality Syndicated Data. In: ICIQ 2005 Proc. (2005)
Avenali, A., Bertolazzi, P., Batini, C., Missier, P.: A formulation of the data quality optimization problem in cooperative information systems. In: CAiSE Workshops (2) (2004)
Braumandl, R.: Quality of service and optimization in data integration systems. In: BTW Proc. (2003)
English, L.P.: Improving data warehouse and business information quality: methods for reducing costs and increasing profits. John Wiley & Sons, Inc., Chichester (1999)
Hernández, M.A., Stolfo, S.J.: Real-world data is dirty: Data cleansing and the merge/purge problem. Data Min. Knowl. Discov. 2(1), 9–37 (1998)
Lenzerini, M.: Data integration: A theoretical perspective. In: PODS 2002 Proc. (2002)
Leser, U., Naumann, F.: Query Planning with Information Quality Bounds. In: FQAS 2000 Proc. (2000)
Manber, U.: Introduction to Algorithms. Addison-Wesley, Reading (1989)
Naumann, F., Freytag, J.C., Leser, U.: Completeness of integrated information sources. Inf. Syst. 29(7), 583–615 (2004)
Naumann, F., Leser, U., Freytag, J.C.: Quality-driven Integration of Heterogeneous Information Systems. In: VLDB Proc. (1999)
Olson, J.E.: Data Quality: The Accuracy Dimension. Morgan Kaufmann, San Francisco (2003)
Scannapieco, M., Virgillito, A., Marchetti, C., Mecella, M., Baldoni, R.: The daquincis architecture: a platform for exchanging and improving data quality in cooperative information systems. Inf. Syst. 29(7), 551–582 (2004)
Turner, M., Zhu, F., Kotsiopoulos, I.A., Russell, M., Budgen, D., Bennett, K.H., Brereton, P., Keane, J., Layzell, P.J., Rigby, M.: Using web service technologies to create an information broker: An experience report. In: ICSE 2004 Proc. (2004)
Wolsey, L.: Integer Programming. Wiley, Chichester (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ardagna, D., Cappiello, C., Francalanci, C., Groppi, A. (2006). Brokering Multisource Data with Quality Constraints. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE. OTM 2006. Lecture Notes in Computer Science, vol 4275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11914853_49
Download citation
DOI: https://doi.org/10.1007/11914853_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48287-1
Online ISBN: 978-3-540-48289-5
eBook Packages: Computer ScienceComputer Science (R0)