Data, Ontologies and Decision Making - An Inter-disciplinary Case Study

Stephen Dobson, Arun Sukumar, Tony O'Brien

2013

Abstract

Several studies have highlighted the need for information governance in organisations and the importance of quality data in decision making. Especially when considering the increasing need for collaboration, data-sharing, and interoperability. Organisations are not immune to importance of information governance and given the recent spate of information- related disasters and accidents, information risk management has become all the more important and its link to corporate governance explicitly noted and mapped. Data driven organisations typically lack the structure to associate ontologies tagged with data and are unable to offer the rich semantics that sometimes can enrich a decision maker's worldview. Data documents need not necessarily capture relationships and ontologically there are unable to offer the rich semantics that the data can sometimes show. The value of data is enriched by the associated semantics and modern enterprise systems are inadequate in their capacity to capture this rich source of knowledge and its representation. This research borrows approaches from urban sustainability to understand domain ontologies and their implications in system design and subsequent improvement in the value of organisational information. It uses case studies to highlight ontology modelling and how such an approach can add value in an organisational context specifically in the domains of system design and information value chain.

References

  1. Akkermans, H., Baida, Z., Gordijn, J., Peiia, N., Altuna, A., & Laresgoiti, I. (2004). 'Value webs:
  2. Using ontologies to bundle real-world services'. Intelligent Systems, IEEE, 19(4), pp. 57-66.
  3. Amaral MHR, Loch CH, Wilkinson D, Huberman BA (1996) Scaling behaviour in the growth of companies. Nature 379, pp. 831-848.
  4. Batty M, Longley P (1994) Fractal Cities: A Geometrybof Form and Function (Academic Press, San Diego, CA and London).
  5. Bhardwaj N, Yan K, Gerstein MB (2010) Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels. Proc Natl Acad Sci USA 107, pp 6841- 6846.
  6. Brüggemann, S. and d'Amato, C. (2012) Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources IGI Global
  7. Cimiano, P., Mädche, A., Staab, S., & Völker, J. (2009). Ontology learning. Handbook on Ontologies, pp. 245- 267.
  8. Connelly, S. (2007). 'Mapping sustainable development as a contested concept' Local Environment, 12(3), pp. 259-278.
  9. Dawson, R. J. (2011). 'Potential pitfalls on the transition to more sustainable cities and how they might be avoided' Carbon, 2(2), pp. 175-188.
  10. Dobson, S. (2012) 78 The Reflexive Practitioner: Knowledge Discovery through Action Research'
  11. in (eds) S. Brüggemann and C. d'Amato Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources IGI Global pp. 135-148.
  12. Erwin D. H., Davidson EH (2009) The evolution of hierarchical gene regulatory networks. Nat Rev Genet 10, pp. 141-148.
  13. Guimer R, Danon L, D ´aiaz-Guilera A, Giralt F, Arenas A (2003) Self-similar community structure in a network of human interactions. Phys Rev E Stat Nonlin Soft Matter Phys 68, 065103.
  14. Hall, J. W., Dawson, R. J., Walsh, C. L., Barker, T., Barr, S. L., Batty, M., & Zanni, A. M. (2009). Engineering Cities: How can cities grow whilst reducing emissions and vulnerability?78 Newcastle University: October.
  15. Hirata H., Ulanowicz R (1985) Information theoretical analysis of the aggregation and hierarchical structure of ecological networks. J. Theor. Biol. 116, pp. 321- 341
  16. Krugman PR (1996) Confronting the mystery of urban hierarchy. Journal of the Japanese and International Economies 10, pp. 399-418.
  17. Ma H., Buer J., Zeng A (2004) Hierarchical structure and modules in the escherichia coli transcriptional regulatory network revealed by a new top-down approach. BMC Bioinformatics 5, pp. 199
  18. Mihm J., Loch CH, Wilkinson DM, Huberman BA (2010) Hierarchical structure and search in complex organizations. Management Science 56, pp. 831-848.
  19. Mounce, S., Brewster, C., Ashley, R. and Hurley, L. (2010) 'Knowledge Management for More
  20. Action C21 - Future of Urban Ontologies Universite de Liege
  21. Rettinger, A., Lösch, U., Tresp, V., d'Amato, C., & Fanizzi, N. (2012). 'Mining the Semantic
  22. Web'. Data Mining and Knowledge Discovery, pp. 1-50.
  23. Rodriguez-Iturbe I, Rinaldo A (1996) Fractal River Basins: Chance and Self-Organization (Cambridge University press)
  24. Schauser, I., Otto, S., Schneiderbauer, S., Harvey, A., Hodgson, N., Robrecht, H., ... & McCallum, S. (2010). Urban Regions: Vulnerabilities, Vulnerability Assessments by Indicators and Adaptation Options for Climate Change Impacts. European Topic Centre on Air ad Climate Change (ETC/ACC): Bilthoven.
  25. Simon, H.A. (1960) The new science of management decision Englewood Cliffs, NJ; Prentice Hall
  26. Teller, J., Tweed, C. & Rabino, G. (2008) Conceptual Models for Urban Practitioners Società Editrice Esculapio, Bologna
  27. Yu H, Gerstein M (2006) Genomic analysis of the hierarchical structure of regulatory networks. Proc Natl Acad Sci USA 103, pp. 14724-14731.
  28. Valverde S, Sol ´ RV (2007) Self-organization versus hierarchy in open-source social networks. Phys Rev E StatbNonlin Soft Matter Phys 76, pp. 046118
  29. Wallas, G. (1926) The Art of Thought New York, Harcourt, Brace and Company
  30. West G., Brown J, Enquist B (1997) A general model for the origin of allometric scaling laws in biology. Science 276, pp. 122-126.
  31. Wickens J., Ulanowicz R (1988) On quantifying hierarchical connections in ecology. J. Social Biol. Struct. 11, pp. 369-378.
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Paper Citation


in Harvard Style

Dobson S., Sukumar A. and O'Brien T. (2013). Data, Ontologies and Decision Making - An Inter-disciplinary Case Study . In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: IVM, (ICEIS 2013) ISBN 978-989-8565-60-0, pages 563-568. DOI: 10.5220/0004616905630568


in Bibtex Style

@conference{ivm13,
author={Stephen Dobson and Arun Sukumar and Tony O'Brien},
title={Data, Ontologies and Decision Making - An Inter-disciplinary Case Study},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: IVM, (ICEIS 2013)},
year={2013},
pages={563-568},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004616905630568},
isbn={978-989-8565-60-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 2: IVM, (ICEIS 2013)
TI - Data, Ontologies and Decision Making - An Inter-disciplinary Case Study
SN - 978-989-8565-60-0
AU - Dobson S.
AU - Sukumar A.
AU - O'Brien T.
PY - 2013
SP - 563
EP - 568
DO - 10.5220/0004616905630568