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Abstract

Product family design is one of the prevailing approaches in realizing mass customization. With the increasing number of product offerings targeted at different market segments, the issue of information management in product family design, that is related to an efficient and effective storage, sharing and timely retrieval of design information, has become more complicated and challenging. Product family modelling schema reported in the literature generally stress the component aspects of a product family and its analysis, with a limited capability to model complex inter-relations between physical components and other required information in different semantic orientations, such as manufacturing, material and marketing wise. To tackle this problem, ontology-based representation has been identified as a promising solution to redesign product platforms especially in a semantically rich environment. However, ontology development in design engineering demands a great deal of time commitment and human effort to process complex information. When a large variety of products are available, particularly in the consumer market, a more efficient method for building a product family ontology with the incorporation of multi-faceted semantic information is therefore highly desirable. In this study, we propose a methodology for building a semantically annotated multi-faceted ontology for product family modelling that is able to automatically suggest semantically-related annotations based on the design and manufacturing repository. The six steps of building such ontology: formation of product family taxonomy; extraction of entities; faceted unit generation and concept identification; facet modelling and semantic annotation; formation of a semantically annotated multi-faceted product family ontology (MFPFO); and ontology validation and evaluation are discussed in detail. Using a family of laptop computers as an illustrative example, we demonstrate how our methodology can be deployed step by step to create a semantically annotated MFPFO. Finally, we briefly discuss future research issues as well as interesting applications that can be further pursued based on the MFPFO developed.

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Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

The paper presents an introduction to W3C's Simple Knowledge Organisation System (SKOS) , an RDF Schema designed to represent and share controlled vocabularies, such as classifications, glossaries, and thesauri, more simply than ontology languages.

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Abstract

18 August 2009 -- Today W3C announces a new standard that builds a bridge between the world of knowledge organization systems - including thesauri, classifications, subject headings, taxonomies, and folksonomies - and the linked data community, bringing benefits to both. Libraries, museums, newspapers, government portals, enterprises, social networking applications, and other communities that manage large collections of books, historical artifacts, news reports, business glossaries, blog entries, and other items can now use Simple Knowledge Organization System (SKOS) to leverage the power of linked data. As different communities with expertise and established vocabularies use SKOS to integrate them into the Semantic Web, they increase the value of the information for everyone.

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Abstract

The paper analysed here is a kind of position paper. In order to get a better under-standing of the reported work I used the retrieval interface of the thesaurus, the so-called NCI DTS Browser accessible via the Web3, and I perused the cited OWL file4 with numerous "Find" and "Find next" string searches. In addition the file was im-ported into Protégé 2000, Release 2.0, with OWL Plugin 1.0 and Racer Plugin 1.7.14. At the end of the paper's introduction the authors say: "In the following sections, this paper will describe the terminology development process at NCI, and the issues associated with converting a description logic based nomenclature to a semantically rich OWL ontology." While I will not deal with the first part, i.e. the terminology development process at NCI, I do not see the thesaurus as a description logic based nomenclature, or its cur-rent state and conversion already result in a "rich" OWL ontology. What does "rich" mean here? According to my view there is a great quantity of concepts and links but a very poor description logic structure which enables inferences. And what does the fol-lowing really mean, which is said a few lines previously: "Although editors have defined a number of named ontologic relations to support the description-logic based structure of the Thesaurus, additional relation-ships are considered for inclusion as required to support dependent applications."

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Footnote

Rez. in: iwp 62(2011) H.4, S.205-206 (C. Carstens): "Welche Arten der Wissensrepräsentation existieren im Web, wie ausgeprägt sind semantische Strukturen in diesem Kontext, und wie können soziale Aktivitäten im Sinne des Web 2.0 zur Strukturierung von Wissen im Web beitragen? Diesen Fragen widmet sich Wellers Buch mit dem Titel Knowledge Representation in the Social Semantic Web. Der Begriff Social Semantic Web spielt einerseits auf die semantische Strukturierung von Daten im Sinne des Semantic Web an und deutet andererseits auf die zunehmend kollaborative Inhaltserstellung im Social Web hin. Weller greift die Entwicklungen in diesen beiden Bereichen auf und beleuchtet die Möglichkeiten und Herausforderungen, die aus der Kombination der Aktivitäten im Semantic Web und im Social Web entstehen. Der Fokus des Buches liegt dabei primär auf den konzeptuellen Herausforderungen, die sich in diesem Kontext ergeben. So strebt die originäre Vision des Semantic Web die Annotation aller Webinhalte mit ausdrucksstarken, hochformalisierten Ontologien an. Im Social Web hingegen werden große Mengen an Daten von Nutzern erstellt, die häufig mithilfe von unkontrollierten Tags in Folksonomies annotiert werden. Weller sieht in derartigen kollaborativ erstellten Inhalten und Annotationen großes Potenzial für die semantische Indexierung, eine wichtige Voraussetzung für das Retrieval im Web. Das Hauptinteresse des Buches besteht daher darin, eine Brücke zwischen den Wissensrepräsentations-Methoden im Social Web und im Semantic Web zu schlagen. Um dieser Fragestellung nachzugehen, gliedert sich das Buch in drei Teile. . . .

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Abstract

We are proud to announce DBpedia Archivo (https://archivo.dbpedia.org) an augmented ontology archive and interface to implement FAIRer ontologies. Each ontology is rated with 4 stars measuring basic FAIR features. We discovered 890 ontologies reaching on average 1.95 out of 4 stars. Many of them have no or unclear licenses and have issues w.r.t. retrieval and parsing.