Challenges for Value-driven Semantic Data Quality Management

Rob Brennan

2017

Abstract

This paper reflects on six years developing semantic data quality tools and curation systems for both large-scale social sciences data collection and a major web of data hub. This experience has led the author to believe in using organisational value as a mechanism for automation of data quality management to deal with Big Data volumes and variety. However there are many challenges in developing these automated systems and this discussion paper sets out a set of challenges with respect to the current state of the art and identifies a number of potential avenues for researchers to tackle these challenges.

References

  1. Ahituv, N., 1989, Assessing the value of information: problems and approaches. In: DeGross, J.I.,Henderson, J.C., Konsynski, B.R. (eds.) International Conference on Information Systems (ICIS 1989). pp. 315-325. Boston, Massachusetts.
  2. Aiken, P., 2016, EXPERIENCE: Succeeding at Data Management-BigCo Attempts to Leverage Data, Journal of Data and Information Quality (JDIQ), Volume 7 Issue 1.
  3. Bertossi, L. and Bravo, L., 2013, Generic and Declarative Approaches to Data Cleaning: Some Recent Developments, Handbook of Data Quality: Research and Practice, Shazia Sadiq (Ed), Spriner, ISBN 978-3- 642-36256-9, 2013.
  4. Brennan, R. , Feeney, K. Mendel-Gleason, G. Bozic, B. Turchin, P. Whitehouse, H. Francois, P. Currie, T. E. Grohmann, S., 2011, Building the Seshat Ontology for a Global History Databank, LNCS , Extended Semantic Web Conference, Heraklion, 29th May - 2nd June, edited by Harald Sack - Eva Blomqvist - Mathieu d'Aquin - Chiara Ghidini - Simone Paolo Ponzetto - Christoph Lange , (9678), Springer, 2016, pp693 - 708.
  5. Calvanese, D., Cogrel, B. , Komla-Ebri, S. Kontchakov, R. Lanti, D. Rezk, M. Rodriguez-Muro, M. Xiao, G., 2016, Ontop: Answering SPARQL Queries over Relational Databases, (Accepted), Semantic Web Journal, Available at: http://www.semantic-webjournal.net/content/ontop-answering-sparql-queriesover-relational-databases-1 [Accessed 09 March 2017]
  6. Chen, Y., 2005, Information valuation for Information Lifecycle Management, Proc IEEE International Conference on Autonomic Computing pp: 135-146, DOI 10.1109/ICAC.2005.35.
  7. Console, M. and Lenzerini, M., 2014, Data Quality in Ontology-Based Data Access:The Case of Consistency, Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence.
  8. Debruyne, C., Walshe, B., O'Sullivan, D., 2015, Towards a Project Centric Metadata Model and Lifecycle for Ontology Mapping Governance, 17th International Conference on Information Integration and Web-based Applications & Services, Brussels, Belgium, 11-13 December , edited by Maria Indrawan-Santiago, Matthias Steinbauer, A Min Tjoa, Ismail Khalil, Gabriele Anderst-Kotsis , ACM, pp356 - 365.
  9. Vander Sande, M., Colpaert, P., Verborgh, R., Mannens, E., and Van De Walle, R., 2014 , RML?: A Generic Language for Integrated RDF Mappings of Heterogeneous Data.
  10. Even, A., and Shankaranarayanan, G., 2005, Value-Driven Data Quality Assessment, in Proceedings of the 10th International Conference on Information Quality, Cambridge, MA, USA.
  11. Evan, A., 2010, Evaluating a model for cost-effective data quality management in a real-world CRM setting, Decision Support Systems 50(1):152-163, DOI: 10.1016/j.dss.2010.07.011.
  12. Feeney, K., O'Sullivan, D., Tai, W. and Brennan, R. 2014, Improving curated web-data quality with structured harvesting and assessment, International Journal on Semantic Web and Information Systems 10(2).
  13. Feeney, K. Mendel-Gleason G. and Brennan, R., 2017, Linked data schemata: fixing unsound foundations, Semantic Web Journal, Accepted, Available at: http://www.semantic-web-journal.net/content/linkeddata-schemata-fixing-unsound-foundations-0 [Accessed 09 March 2017]
  14. Foley, S., and Fitzgerald, W., 2011, Management of security policy configuration using a Semantic Threat Graph approach, Journal of Computer Security, vol. 19, no. 3, pp. 567-605.
  15. Helfert, M., and Herrmann, C., 2002, Proactive Data Quality Management for Data Warehouse Systems - A Metadata based Data Quality System. In: 4th International Workshop on Design and Management of Data Warehouses (DMDW), Toronto, Canada.
  16. ISO/IEC JTC 1, 2014, Information Technology, Big Data, Preliminary Report 2014. Available at: http://www.iso.org/iso/big_data_report-jtc1.pdf [Accessed 09 March 2017]
  17. Janssen, M. and Vilminko-Heikkinen, R., 2016, Coordinating Decision-Making in Data Management Activities: A Systematic Review of Data Governance Principles, EGOV 2016, LNCS 9820, pp. 115- 125.DOI: 10.1007/978-3-319-44421-5_9.
  18. Khatri, V., Brown, C.V., 2010, Designing data governance. Communications of the ACM 53(1), 148- 152.
  19. Kontokostas, D. , Westphal, P. , Auer, S., Hellmann, S., Lehmann, J. , Cornelissen, r., Zaveri, a., 2014, Testdriven Evaluation of Linked Data Quality, Proceedings of the 23rd International Conference on World Wide Web, pp747-758.
  20. Logan, D. 2016, Ten Steps to Information Governance, Gartner Report G00296492. Available at: https://www.edq.com/resources/analystreports/gartner-10-steps-to-data-governance/ [Accessed 09 March 2017]
  21. Maali, F., Erickson, J., (Eds.), 2014, Data Catalog Vocabulary (DCAT), W3C Recommendation, Available at https://www.w3.org/TR/vocab-dcat/
  22. Meehan, A. Kontokostas, D. Freudenberg, M. Brennan, R. O'Sullivan, D., 2016, Validating Interlinks between Linked Data Datasets with the SUMMR Methodology, ODBASE 2016 - The 15th International Conference on Ontologies, DataBases, and Applications of Semantics, Rhodes, Greece, , Springer Verlag.
  23. Mendel-Gleason, G. Feeney K. and Brennan, R., 2015, Ontology Consistency and Instance Checking for Real World Linked Data, 2nd Workshop on Linked Data Quality, Slovenia.
  24. Moody, D. and Walsh, P., 1999, Measuring The Value Of Information: An Asset Valuation Approach, Proc. Seventh European Conference on Information Systems (ECIS'99).
  25. Mosley, M., Brackett, M.,, Earley, S., and Henderson, D., (Eds), 2010, The DMA Guide to the Data Management Body of Knowledge (1st Ed.), Technics Publications LLC, 2010, ISBN 978-9355040-2-3.
  26. Neumaier, S., Umbrich, J., Polleres, A., 2016, Automated Quality Assessment of Metadata across Open Data Portals, Journal of Data and Information Quality (JDIQ), Vol. 8 Issue 1, DOI:10.1145/2964909.
Download


Paper Citation


in Harvard Style

Brennan R. (2017). Challenges for Value-driven Semantic Data Quality Management . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 385-392. DOI: 10.5220/0006387803850392


in Bibtex Style

@conference{iceis17,
author={Rob Brennan},
title={Challenges for Value-driven Semantic Data Quality Management},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={385-392},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006387803850392},
isbn={978-989-758-247-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Challenges for Value-driven Semantic Data Quality Management
SN - 978-989-758-247-9
AU - Brennan R.
PY - 2017
SP - 385
EP - 392
DO - 10.5220/0006387803850392