By Fayçal Hamdi, Chantal Reynaud, Brigitte Safar (auth.), Philipp Cimiano, H. Sofia Pinto (eds.)
Knowledge administration and information Engineering is an interesting ?eld of re- 1 seek nowadays. initially of EKAW , the modeling and acquisition of information used to be the privilege of – or particularly a burden for – a couple of wisdom engineers accustomed to wisdom engineering paradigms and data rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and make allowance for reusability, the data types produced in those early days have been quite often utilized in unmarried and extremely speci?c purposes and infrequently - replaced. additionally, those versions have been usually relatively advanced, and so they will be understood basically through a couple of professional wisdom engineers. this case has replaced notably within the previous few years as truly indicated by way of the next traits: – The production of (even formal) wisdom is now turning into a growing number of collaborative. Collaborative ontology engineering instruments and social software program structures express the capability to leverage the knowledge of the crowds (or at the least of “the many”) to steer to broader consensus and therefore produce shared types which qualify larger for reuse. – A pattern can be saw in the direction of constructing and publishing small yet 2 three four high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than advanced and big wisdom models.
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Additional resources for Knowledge Engineering and Management by the Masses: 17th International Conference, EKAW 2010, Lisbon, Portugal, October 11-15, 2010. Proceedings
Example text
But that identity should be weaker than numerical identity since the same person might gain weight at the next visit. On the other hand, the identity must be stronger than that used for just counting the number of things because counting needs no identification of what the counted objects are. The identity in the example (1) is similar to the one in (2), but is different in that your bike cannot change by replacing all the parts with new ones until becoming a totally different bike from your original one.
Safar which test the existence of mappings generated by alignment techniques. MRPL is defined as follows: Definition 1 (Vocabulary) The vocabulary of MRPL contains: – a set of predicate constants. We distinguish three categories of predicate constants: the predicate constants relating to the type of techniques applied in the identification of a mapping by TaxoMap, the predicate constants expressing structural relations between concepts of a same ontology, the predicate constants expressing terminological relations between labels of concepts.
Regarding our environment, another related work is PROMPT-Suite integrating the ontology merging tool IPROMPT [13], the alignment tool AnchorPROMPT, versioning, comparison, translation functionalities. All these tools are interactive and semi-automatic. For example, in the fusion process the system makes suggestions. The expert can hold one of them or specify an operation to perform. The system then executes the operation, calculates the resulting changes, makes other suggestions and detects any inconsistencies.