Summary
A core requirement for the usage of ontologies within enterprizes is the availability of proved and tested techniques which guarantee an efficient engineering of high-quality ontologies, be that by reuse, manual building or automatic knowledge acquisition. Besides feasible technological support this includes in equal measure integrating ontology engineering within the more general framework of enterprize information architectures, and taking into account the economics of ontology engineering projects, in particular issues of cost effectiveness and profitability. This chapter addresses these two aspects. We discuss the role of ontology engineering in the context of enterprize architectures, arguing for the importance of cost-related measures as decision support in planning and controlling. Then we analyze approaches for reliably assessing the costs of building ontologies, and the usage of cost-related information to quantifiably support decisions arising during the life cycle of an ontology and to optimize the operation of associated processes. We account for the similarities and differences between software and ontology engineering in order to establish the appropriateness of applying methods with a long-standing tradition in this adjacent engineering field to ontologies. Building upon the results of this analysis we introduce ONTOCOM as the first cost model for ontologies and discuss different methods to improve its accuracy for a wide range of ontology engineering projects at public and corporate level.
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Notes
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An exception from this statement is the IDEF integrated definition method. The IDEF approach defines a function modeling method (IDEF0), information modeling method (IDEF1), data modeling method (IDEF1X), process description capture method (IDEF3), object oriented design method (IDEF4), and finally the ontology description capture method (IDEF5), which can be mapped to the aforementioned architectural models foreseen by enterprize architecture development frameworks. More information about IDEF is available at http://www.idef.com/
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Linear regression is a mathematical method to calculate the parameters of a linear equation so that the squared differences between the predictions from the linear equation and the observations are minimal [19].
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Simperl, E., Tempich, C. (2009). Exploring the economical aspects of ontology engineering. In: Staab, S., Studer, R. (eds) Handbook on Ontologies. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92673-3_15
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