Abstract
Instruments to predict the total costs associated with the development, deployment and ownership of ontology-based technologies are a must for their adoption by the industry. In previous work of ours we have introduced a series of models that analyzed and estimated the costs and benefits associated with the development of ontologies and related knowledge structures, and of the applications using them. This chapter can be seen as a continuation of this work as it provides guidelines – both scenario and tool-oriented – that assist project managers in utilizing these models throughout the ontology life cycle.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The survey did not cover reuse efforts related to the usage of ontologies in the context of the Linked Open Data (LOD) initiative, where a (relatively small) number of vocabularies is reused through so-called ’interlinking’. With LOD acting as a real game-changer in the semantic-technologies landscape, a new survey is required in order to fully understand the state-of-practice of ontology engineering in such data-driven scenarios.
- 2.
We use the cost-driver abbreviations defined in the ONTOCOM model [Popov et al. 2009]. A positive correlation means, that, if the value of one factor rises, the other rises as well; the opposite holds for negatively correlated factors. For instance, if OCAP decreases, the effort is expected to rise.
- 3.
FOLCOM calculates the time required to tag the entire collection.
- 4.
Dumb nodes are non-specialists which are information/data pushers. These roles may be incorporated into enterprise information systems.
- 5.
Active nodes are specialists that define the process dynamics and can only have an interface to enterprise knowledge portals.
- 6.
External nodes are specialists on a sub-process level. They should therefore be considered while designing enterprise information systems.
References
Berners-Lee T, Hendler J, Lassila O (2001) The semantic web. Sci Am 284(5):34–43
Bürger T, Simperl E (2008) Measuring the benefits of ontologies. In OTM ’08: proceedings of the OTM confederated international workshops and posters on on the move to meaningful internet systems, pp 584–594. Springer
Bürger T, Popov I, Simperl E, Hofer C, Imtiaz A, Krenge J (2010) Calibrated predictive model for costs and benefits. Deliverable D4.1.2, ACTIVE
Cooke N (1994) Varieties of knowledge elicitation techniques. Int J Hum Comput Stud 41:801–849
Davis J, Fensel D, van Harmelen F (eds) (2003) Towards the semantic web: ontology-driven knowledge management. Wiley, The Atrium, Southern Gate, Chichester, West Sussex
Ebert C, Dumke R (2007) Software measurement: establish – extract – evaluate – execute. Springer, Berlin
Ebert C, Dumke M, Schmietendorf A (2005) Best practices in software measurement. Springer, New York
Fensel D (2001) Ontologies: a silver bullet for knowledge management and electronic commerce. Springer Verlag, Berlin
Gomez-Perez A, Suarez-Figueroa M-C, Vigo M (2009) Gontt: a tool for scheduling ontology development projects. In Proceedings of the fifth international conference on knowledge capture, ACM, New York
Hepp M, De Leenheer P, de Moor A, Sure Y (eds) (2008) Ontology management: semantic web, semantic web services, and business applications (semantic web and beyond). Springer, New York.
Imtiaz A, Giernalczyk A, Davies J, Thurlow I (2008) Cost, benefit engineering for collaborative knowledge creation within knowledge workpspaces. In Proceedings of EChallenges 2008.
Imtiaz A, Giernalczyk A, Bürger T, Popov I (2009) A predictive framework for value engineering within collaborative knowledge workspaces. In Proceedings of EChallenges 2009.
McGuinness DL (2003) Ontologies come of age. In Fensel D, Hendler J, Lieberman H, Wahlster C, (eds) Spinning the semantic web: bringing the world wide web to its full potential. MIT Press, Cambridge
Paslaru Bontas Simperl E, Tempich C, Sure Y (2006) Ontocom: a cost estimation model for ontology engineering. In Proceedings of the 5th International Semantic Web Conference ISWC2006.
Paslaru Bontas E, Tempich C (2005) How much does it cost? Applying ONTOCOM to DILIGENT. Technical Report TR-B-05-20, Free University of Berlin
Popov I, Bürger T, Simperl E, Imtiaz A (2009) Preliminary predictive model for costs and benefits. Deliverable D4.1.1, ACTIVE.
Remenyi D, Money A, Sherwood-Smith M, Irani Z (2001) The effective measurement and management of IT costs and benefits
Simperl E, Bürger T (2010) H. Jin, Z. Lv (editors): data management in semantic web, chapter Ontology Reuse – Is it Feasible? Nova Science Publishers, Inc. (to be published)
Simperl E, Mochol M, Bürger T, Popov I (2009a) Achieving maturity: the state of practice in ontology engineering in 2009. In Proceedings of Ontologies, DataBases, and Applications of Semantics for Large Scale Information Systems (ODBASE’09).
Simperl E, Popov I, Bürger T (2009b) ONTOCOM Revisited: towards accurate cost predictions for ontology development projects. In Proceedings of the 6th European Semantic Web Conference (ESWC 2009), pp 248–262
Simperl EPB, Bürger T, Hofer C (2010) Folcom or the costs of tagging. In Proceedings of the 17th international conference on Knowledge Engineering and Management by the Masses (EKAW2010), pp 163–177
Suarez-Figueroa M, de Cea GA, Buil C, Caracciolo C, Dzbor M, Gomez-Perez A, Herrrero G, Lewen H, Montiel-Ponsoda E, Presutti V (2007) Neon development process and ontology life cycle. NeOn deliverable 5.3.1, NeOn
Acknowledgements
The research leading to this paper was partially supported by the European Commission under the contract FP7-215040 “ACTIVE”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bürger, T., Simperl, E., Wölger, S., Hangl, S. (2011). Using Cost-Benefit Information in Ontology Engineering Projects. In: Warren, P., Davies, J., Simperl, E. (eds) Context and Semantics for Knowledge Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19510-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-19510-5_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19509-9
Online ISBN: 978-3-642-19510-5
eBook Packages: Computer ScienceComputer Science (R0)