By Fayçal Hamdi, Chantal Reynaud, Brigitte Safar (auth.), Philipp Cimiano, H. Sofia Pinto (eds.)
Knowledge administration and data Engineering is an engaging ?eld of re- 1 seek nowadays. firstly of EKAW , the modeling and acquisition of information was once the privilege of – or really a burden for – a number of wisdom engineers accustomed to wisdom engineering paradigms and data rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and make allowance for reusability, the information versions produced in those early days have been more often than not utilized in unmarried and intensely speci?c purposes and infrequently - replaced. furthermore, those types have been generally relatively complicated, they usually should be understood in simple terms through a couple of professional wisdom engineers. this example has replaced considerably within the previous few years as basically indicated via the subsequent traits: – The production of (even formal) wisdom is now changing into an increasing number of collaborative. Collaborative ontology engineering instruments and social software program systems convey the aptitude to leverage the knowledge of the crowds (or a minimum of of “the many”) to guide to broader consensus and hence produce shared versions which qualify larger for reuse. – A development is also saw in the direction of constructing and publishing small yet 2 three four high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than advanced and massive wisdom models.
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