What if Multiusers Wish to Reconcile Their Data?

Dayse Silveira de Almeida, Carmem Satie Hara, Cristina Dutra de Aguiar Ciferri

2015

Abstract

Reconciliation is the process of providing a consistent view of the data imported from different sources. Despite some efforts reported in the literature for providing data reconciliation solutions with asynchronous collaboration, the challenge of reconciling data when multiple users work asynchronously over local copies of the same imported data has received less attention. In this paper, we propose AcCORD, an asynchronous collaborative data reconciliation model based on data provenance. AcCORD is innovative because it supports applications in which all users are required to agree on the data integration in order to provide a single consistent view to all of them, as well as applications that allow users to disagree on the correct data value, but promote collaboration by sharing updates. We also introduce different policies based on provenance for solving conflicts among multiusers’ updates. An experimental study investigates the main characteristics of the policies, showing the efficacy of AcCORD.

References

  1. Bhattacharjee, A. and Jamil, H. (2012). A schema matching system for on-the-fly autonomous data integration. International Journal of Information and Decision Sciences, 4(2-3):167-181.
  2. Cao, Y., Fan, W., and Yu, W. (2013). Determining the relative accuracy of attributes. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 565-576.
  3. Cheney, J., Chiticariu, L., and Tan, W.-C. (2009). Provenance in databases: Why, how, and where. Foundations and Trends in Databases, 1(4):379-474.
  4. Edwards, W. K., Mynatt, E. D., Petersen, K., Spreitzer, M. J., Terry, D. B., and Theimer, M. M. (1997). Designing and implementing asynchronous collaborative applications with Bayou. In Proceedings of the 10th Annual ACM Symposium on User Interface Software and Technology, pages 119-128.
  5. Green, T. J., Karvounarakis, G., Ives, Z. G., and Tannen, V. (2007). Update exchange with mappings and provenance. In Proceedings of the 33rd International Conference on Very Large Data Bases, pages 675-686.
  6. Halevy, A. Y., Rajaraman, A., and Ordille, J. J. (2006). Data integration: The teenage years. In Proceedings of the 32nd International Conference on Very Large Data Bases, pages 9-16.
  7. Hossain, M. S., Masud, M., Muhammad, G., Rawashdeh, M., and Hassan, M. M. (2014). Automated and user involved data synchronization in collaborative ehealth environments. Computer in Human Behavior, 30:485-490.
  8. Ives, Z. G., Green, T. J., Karvounarakis, G., Taylor, N. E., Tannen, V., Talukdar, P. P., Jacob, M., and Pereira, F. (2008). The Orchestra collaborative data sharing system. SIGMOD Record, 37(3):26-32.
  9. Kermarrec, A.-M., Rowstron, A., Shapiro, M., and Druschel, P. (2001). The IceCube approach to the reconciliation of divergent replicas. In Proceedings of the 20th Annual ACM Symposium on Principles of Distributed Computing, pages 210-218.
  10. Köpcke, H., Thor, A., and Rahm, E. (2010). Evaluation of entity resolution approaches on real-world match problems. PVLDB, 3(1):484-493.
  11. Kot, L. and Koch, C. (2009). Cooperative update exchange in the Youtopia system. PVLDB, 2(1):193-204.
  12. Mahmood, T., Jami, S. I., Shaikh, Z. A., and Mughal, M. H. (2013). Toward the modeling of data provenance in scientific publications. Computer Standards & Interfaces, 35(1):6-29.
  13. Nguyen, H.-Q., Taniar, D., Rahayu, J., and Nguyen, K. (2011). Double-layered schema integration of heterogeneous XML sources. Journal of Systems and Software, 84(1):63-76.
  14. Pierce, B. C., Schmitt, A., and Greenwald, M. B. (2004). Bringing Harmony to optimism: A synchronization framework for heterogeneous tree-structured data. Technical Report MS-CIS-03-42, University of Pennsylvania.
  15. Saito, Y. and Shapiro, M. (2005). Optimistic replication. ACM Computing Surveys, 37(1):42-81.
  16. Taylor, N. E. and Ives, Z. G. (2006). Reconciling while tolerating disagreement in collaborative data sharing. In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pages 13-24.
  17. Tomazela, B., Hara, C. S., Ciferri, R. R., and Ciferri, C. D. A. (2013). Empowering integration processes with data provenance. Data & Knowledge Engineering, 86:102-123.
Download


Paper Citation


in Harvard Style

Silveira de Almeida D., Satie Hara C. and Dutra de Aguiar Ciferri C. (2015). What if Multiusers Wish to Reconcile Their Data? . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 184-195. DOI: 10.5220/0005384401840195


in Bibtex Style

@conference{iceis15,
author={Dayse Silveira de Almeida and Carmem Satie Hara and Cristina Dutra de Aguiar Ciferri},
title={What if Multiusers Wish to Reconcile Their Data?},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={184-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005384401840195},
isbn={978-989-758-096-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - What if Multiusers Wish to Reconcile Their Data?
SN - 978-989-758-096-3
AU - Silveira de Almeida D.
AU - Satie Hara C.
AU - Dutra de Aguiar Ciferri C.
PY - 2015
SP - 184
EP - 195
DO - 10.5220/0005384401840195