ONTOLOGY-BASED KNOWLEDGE MANAGEMENT - Graphical Query Editor for OWL Ontologies

Markus Schwinn, Norbert Kuhn, Stefan Richter

Abstract

The OnToBau research project aims to provide a way to classify, archive and effectively use business knowledge with the assistance of an ontology-based knowledge archive for small and medium companies from construction industry. This archive is intended to pro-actively provide users with information to assist them in their daily business process handling. The system consists of four main parts. The document converters prepare the different resources (EMails, Paperdocuments, PDFs etc.) that should be stored in the knowledge archive for the enclosed inference system. The inference system is the core component and extracts the information from the preprocessed resources. Ontologies provide the necessary domain knowledge. In order to exploit the available knowledge, a personal agent monitors the current activities of the user and tries to infer the intention from his behaviors. At certain points it automatically offers the user helpful information. Again ontologies are used to represent information about the business processes. In addition, the user has the option to search for information in the archive through the graphical user interface. The importance of simple query systems has already been identified in the area of database systems. This paper gives an overview of the OnToBau research project presenting a first approach to visual query for information in the knowledge archive.

References

  1. Böder, J. (2003). Das Internet und seine Folgen - Was Luthers Reformation und unsere Zukunft gemeinsam haben. http://www.intelligenzia.de/Texte/Internet.pdf. 17. August 2009.
  2. Borsje, J. and Embregts, H. (2006). Graphical Query Composition and Natural Language Processing in an RDF Visualization Interface. Bachelor, Erasmus University Rotterdam.
  3. Castell, M. (2001). Das Informationszeitalter. Wirtschaft, Gesellschaft, Kultur, volume 1. Leske + Budrich Verlag.
  4. Catarci, T. (1997). Visual Query Systems for Databases: A Survey. Journal of Visual Languages & Computing, 8(2):215-260.
  5. Goasduff, L. (2002). Gartner Says 90 Percent of Businesses Suffer from Information Overload. http://www.gartner.com/5 about/press releases/2002 - 05/pr20020507c.jsp. 24. August 2009.
  6. Lyman and Varian (2003). How Much Information? http://www2.sims.berkeley.edu/research/projects/howmuch-info-2003/printable report.pdf. 19. August 2009.
  7. Makolm, J., Weiß, S., and Reisinger, D. (2007). Proactive knowledge management: the DYONIPOS research and use-case project. In Janowski, T. and Pardo, T. A., editors, Proceedings of the 1st international conference on Theory and practice of electronic governance (ICEGOV 7807), pages 85-88, New York, NY, USA. ACM.
  8. Radicati, S. and Khmartseva, M. (2009). Email Statistics Report, 2009-2013. http://www.radicati.com/wp/wpcontent/uploads/2009/05/email-stats-report-execsummary.pdf. 19. August 2009.
  9. Rasheed, N. (2005). The Impact Of Knowledge Management On Smes. Technical report, Knowledgeboard.
  10. Russell, A. and Smart, P. R. (2008). NITELIGHT: A Graphical Editor for SPARQL Queries. In International Semantic Web Conference (Posters & Demos).
  11. Schwinn, M. (2010). Automatic Information Extraction from Documents for Setting Up a Knowledge Archive as Basis for an Automated Tender Preparation. Masters thesis, University of Applied Sciences, Trier.
  12. Spira, J. B. (2008). Information Overload: Now $ 900 Billion - What is Your Organizations Exposure? http://www.basexblog.com/2008/12/19/informationoverload-now-900-billion-what-is-yourorganizations. 10. December 2010.
  13. Tochtermann, K., Reisinger, D., Granitzer, M., and Lindstaedt, S. (2006). Integrating Ad Hoc Processes and Standard Processes in Public Administrations. In Proceedings of the OCG eGovernment Conference, Linz (Austria),.
  14. Wong, K. and Aspinwall, E. (2004). Characterizing knowledge management in the small business environment. Journal of Knowledge Management, 8:44-61.
Download


Paper Citation


in Harvard Style

Schwinn M., Kuhn N. and Richter S. (2011). ONTOLOGY-BASED KNOWLEDGE MANAGEMENT - Graphical Query Editor for OWL Ontologies . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 978-989-8425-55-3, pages 235-240. DOI: 10.5220/0003491202350240


in Bibtex Style

@conference{iceis11,
author={Markus Schwinn and Norbert Kuhn and Stefan Richter},
title={ONTOLOGY-BASED KNOWLEDGE MANAGEMENT - Graphical Query Editor for OWL Ontologies},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2011},
pages={235-240},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003491202350240},
isbn={978-989-8425-55-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - ONTOLOGY-BASED KNOWLEDGE MANAGEMENT - Graphical Query Editor for OWL Ontologies
SN - 978-989-8425-55-3
AU - Schwinn M.
AU - Kuhn N.
AU - Richter S.
PY - 2011
SP - 235
EP - 240
DO - 10.5220/0003491202350240