Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

A Approach to Clinical Proteomics Data Quality Control and Import

  • Conference paper
Information Technology in Bio- and Medical Informatics (ITBAM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6865))

  • 563 Accesses

Abstract

Biomedical domain and proteomics in particular are faced with an increasing volume of data. The heterogeneity of data sources implies heterogeneity in the representation and in the content of data. Data may also be incorrect, implicate errors and can compromise the analysis of experiments results. Our approach aims to ensure the initial quality of data during import into an information system dedicated to proteomics. It is based on the joint use of models, which represent the system sources, and ontologies, which are use as mediators between them. The controls, we propose, ensure the validity of values, semantics and data consistency during import process.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.: Gene ontology: tool for the unification of biology. the gene ontology consortium. Nature genetics 25(1), 25–29 (2000)

    Article  Google Scholar 

  2. Ashenhurst, R.L.: Ontological aspects of information modeling. Minds and Machines 6, 287–394 (1996)

    Article  Google Scholar 

  3. Berti-Équille, L.: Quality Awareness for Data Managing and Mining. Habilitation à diriger les recherches, Université de Rennes 1, France (June 2007)

    Google Scholar 

  4. Brusa, G., Caliusco, M. L., Chiotti, O.: A process for building a domain ontology: an experience in developing a government budgetary ontology. In: Proceedings of the Second Australasian Workshop on Advances in Ontologies AOW 2006, Darlinghurst, Australia, Australia, vol. 72, pp. 7–15. Australian Computer Society, Inc. (2006)

    Google Scholar 

  5. Chen, J.Y., Carlis, J.V.: Genomic data modeling. Inf. Syst. 28, 287–310 (2003)

    Article  MATH  Google Scholar 

  6. Dasu, T., Johnson, T.: Exploratory Data Mining and Data Cleaning. John Wiley, Chichester (2003)

    Book  MATH  Google Scholar 

  7. Davidson, S., Overton, C., Buneman, P.: Challenges in Integrating Biological Data Sources. Journal of Computational Biology 2(4), 557–572 (1995)

    Article  Google Scholar 

  8. Degoulet, P., Fieschi, M., Attali, C.: Les enjeux de l’interopérabilité sémantique dans les systèmes d’information de santé. Informatique et gestion médicalisée 9, 203–212 (1997)

    Google Scholar 

  9. Fowler, M.: UML Distilled: A Brief Guide to the Standard Object Modeling Language, 3rd edn. Addison-Wesley Longman Publishing Co., Inc., Boston (2003)

    Google Scholar 

  10. Goh, C.H.: Representing and reasoning about semantic conflicts in heterogeneous information systems. PhD thesis (1997)

    Google Scholar 

  11. Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies 43(5-6), 907–928 (1995)

    Article  Google Scholar 

  12. Hall, J., Healy, K., Ross, R.: Defining Business Rules: What Are They Really? Rapport (2000)

    Google Scholar 

  13. Han, J., Kamber, M.: Data mining: concepts and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2006)

    MATH  Google Scholar 

  14. Horrocks, I., Patel-Schneider, P.F.: A proposal for an owl rules language. In: Proceedings of the 13th International World Wide Web Conference (WWW 2004), pp. 723–731. ACM Press, New York (2004)

    Google Scholar 

  15. Kim, W., Seo, J.: Classifying schematic and data heterogeneity in multidatabase systems. Computer 24, 12–18 (1991)

    Article  Google Scholar 

  16. Linster, M.: Viewing knowledge engineering as a symbiosis of modeling to make sense and modeling to implement systems. In: Ohlbach, H.J. (ed.) GWAI 1992. LNCS, vol. 671, pp. 87–99. Springer, Heidelberg (1993)

    Chapter  Google Scholar 

  17. Motik, B., Rosati, R.: Reconciling description logics and rules. J. ACM 57, 1–30 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  18. Motik, B., Sattler, U., Studer, R.: Query Answering for OWL DL with rules. Web Semantics 3(1), 41–60 (2005)

    Article  Google Scholar 

  19. Naiman, C.F., Ouksel, A.M.: A classification of semantic conflicts in heterogeneous database systems. J. Organ. Comput. 5, 167–193 (1995)

    Google Scholar 

  20. Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. The VLDB Journal 10, 334–350 (2001)

    Article  MATH  Google Scholar 

  21. Redman, T.C.: Data quality: the field guide. Digital Press, Newton (2001)

    Google Scholar 

  22. Ross, R.G.: Principles of the Business Rule Approach. Addison-Wesley Longman Publishing Co., Inc., Boston (2003)

    Google Scholar 

  23. Safar, B., Reynaud, C., Calvier, F.-E.: Techniques d’alignement d’ontologies basées sur la structure d’une ressource complémentaire. In: 1ères Journées Francophones sur les Ontologies (JFO 2007), pp. 21–35 (2007)

    Google Scholar 

  24. Salem, S., AbdelRahman, S.: A multiple-domain ontology builder. In: Proceedings of the 23rd International Conference on Computational Linguistics, COLING 2010, Stroudsburg, PA, USA, pp. 967–975. Association for Computational Linguistics (2010)

    Google Scholar 

  25. Shvaiko, P.: Ten challenges for ontology matching. In: Chung, S. (ed.) OTM 2008, Part II. LNCS, vol. 5332, pp. 1164–1182. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  26. Siegel, M., Madnick, S.E.: A metadata approach to resolving semantic conflicts. In: Proceedings of the 17th International Conference on Very Large Data Bases, VLDB 1991, pp. 133–145. Morgan Kaufmann Publishers Inc, San Francisco (1991)

    Google Scholar 

  27. Spear, A.D.: Ontology for the twenty first century: An introduction with recommendations. Institute for Formal Ontology and Medical Information Science, Saarbrücken, Germany (2006)

    Google Scholar 

  28. Sugumaran, V., Storey, V.C.: Ontologies for conceptual modeling: their creation, use, and management. Data Knowl. Eng. 42, 251–271 (2002)

    Article  MATH  Google Scholar 

  29. Van Heijst, G., Schreiber, A.T., Wielinga, B.J.: Using explicit ontologies in KBS development. Int. J. Hum.-Comput. Stud. 46, 183–292 (1997)

    Article  MATH  Google Scholar 

  30. Wiederhold, G.: Interoperation, mediation, and ontologies. In: Proceedings International Symposium on Fifth Generation Computer Systems (FGCS94), Workshop on Heterogeneous Cooperative Knowledge-Bases, vol. 3, pp. 33–48 (1994)

    Google Scholar 

  31. Willson, S.J.: Measuring inconsistency in phylogenetic trees. J. Theor. Biol. 190, 15–36 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Naubourg, P., Savonnet, M., Leclercq, É., Yétongnon, K. (2011). A Approach to Clinical Proteomics Data Quality Control and Import. In: Böhm, C., Khuri, S., Lhotská, L., Pisanti, N. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2011. Lecture Notes in Computer Science, vol 6865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23208-4_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23208-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23207-7

  • Online ISBN: 978-3-642-23208-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics