1,961 research outputs found
Some Issues on Ontology Integration
The word integration has been used with different
meanings in the ontology field. This article
aims at clarifying the meaning of the word âintegrationâ
and presenting some of the relevant work
done in integration. We identify three meanings of
ontology âintegrationâ: when building a new ontology
reusing (by assembling, extending, specializing
or adapting) other ontologies already available;
when building an ontology by merging several
ontologies into a single one that unifies all of
them; when building an application using one or
more ontologies. We discuss the different meanings
of âintegrationâ, identify the main characteristics
of the three different processes and proposethree words to distinguish among those meanings:integration, merge and use
Overview of methodologies for building ontologies
A few research groups are now proposing a series of steps and methodologies for developing ontologies. However, mainly due to the fact that Ontological Engineering is still a relatively immature discipline, each work group employs its own methodology. Our goal is to present the most representative methodologies used in ontology development and to perform an analysis of such methodologies against the same framework of reference. So, the goal of this paper is not to provide new insights about methodologies, but to put it all in one place and help people to select which methodology to use
An ontology roadmap for crowdsourcing innovation intermediaries
Ontologies have proliferated in the last years, essentially justified by the need of achieving a consensus in
the multiple representations of reality inside computers, and therefore the accomplishment of
interoperability between machines and systems. Ontologies provide an explicit conceptualization that
describes the semantics of the data. Crowdsourcing innovation intermediaries are organizations that mediate
the communication and relationship between companies that aspire to solve some problem or to take
advantage of any business opportunity with a crowd that is prone to give ideas based on their knowledge,
experience and wisdom, taking advantage of web 2.0 tools. Various ontologies have emerged, but at the best
of our knowledge, there isnât any ontology that represents the entire process of intermediation of
crowdsourcing innovation. In this paper we present an ontology roadmap for developing crowdsourcing
innovation ontology of the intermediation process. Over the years, several authors have proposed some
distinct methodologies, by different proposals of combining practices, activities, languages, according to the
project they were involved in. We start making a literature review on ontology building, and analyse and
compare ontologies that propose the development from scratch with the ones that propose reusing other
ontologies. We also review enterprise and innovation ontologies known in literature. Finally, are presented
the criteria for selecting the methodology and the roadmap for building crowdsourcing innovation
intermediary ontology.(undefined
A methodology for designing layered ontology structures
Semantic ontologies represent the knowledge from different domains, which is used as a knowledge base by intelligent agents. The creation of ontologies by different developers leads to heterogeneous ontologies, which hampers the interoperability between knowledge-based applications. This interoperability is achieved
through global ontologies, which provide a common domain representation. Global ontologies must provide a balance of reusability-usability to minimise the ontology effort in different applications. To achieve this balance, ontology design methodologies focus on designing layered ontologies that classify into abstraction layers the domain knowledge relevant to many applications and the knowledge relevant to specific applications. During the design of the layered ontology structure, the domain knowledge classification is
performed from scratch by domain experts and ontology engineers in collaboration with application stakeholders. Hence, the design of reusable and usable ontologies in complex domains takes a significant effort. Software Product Line (SPL) design techniques can be applied to facilitate the domain knowledge classification by analysing the knowledge similarities/differences of existing ontologies. In this context, this thesis aims to define new methodological guidelines to design layered ontology structures that enable to classify the domain knowledge taking as reference existing ontologies, and to apply these guidelines to enable the development of reusable and usable ontologies in complex domains. The MODDALS methodology guides the design of layered ontology structures for reusable and usable ontologies. It brings together SPL engineering techniques and ontology design techniques to enable the classification of the domain knowledge
by exploiting the knowledge similarities/differences of existing ontologies. MODDALS eases the design of the layered ontology structure. The MODDALS methodology was evaluated by applying it to design the layered structure of a reusable and usable global ontology for the energy domain. The designed layered structure was taken as reference to develop the ontology. The resulting ontology simplifies the ontology reuse process in different applications. In particular, it reduced the average ontology reuse time by 0.5 and 1.2 person-hours in in two different applications in comparison with a global energy ontology which does not follow a layered structure.Ontologia semantikoak datu domeinu ezberdinen ezagutza irudikatzen dute, agente adimendunek jakintza oinarri bezala erabiltzen dutena. Ontologiak ingeniari desberdinek garatzen dituzte eta heterogeneoak dira, aplikazioen arteko komunikazioa oztopatuz. Komunikazio hau ontologia globalen bidez lortzen da, domeinuaren
errepresentazio komun bat ematen baitute. Ontologia globalek berrerabilgarritasunerabilgarritasun oreka eman behar dute aplikazio desberdinetan berrerabiltzeko ahalegina murrizteko. Horretarako, ontologia diseinu metodologiek aplikazio askok erabiltzen duten eta aplikazio zehatzetarako garrantzitsua den ezagutza abstrakzio geruzetan sailkatzea proposatzen dute. Geruza egituraren diseinuan zehar, domeinuko adituek eta ontologiako ingeniariek hutsetik sailkatzen dute jakintza, domeinu konplexuetan ontologia berrerabilgarriak eta erabilgarrien diseinu ahalegina areagotuz. Software produktu lerroak diseinatzeko erabiltzen diren teknikak jakintza sailkatzea erraztu ahal dute, ontologien ezagutza antzekotasunak edo desberdintasunak aztertuz. Testuinguru honetan, honakoa da tesiaren helburua: ezagutza garatutako ontologien arabera sailkatzen duen ontologia berrerabilgarri eta erabilgarrien geruza egitura diseinatzeko metodologia bat garatzea; baita metodologia aplikatu ere, ontologia berrerabilgarri eta erabilgarriak domeinu konplexuetan garatu ahal izateko. MODDALS metodologiak ontologia berrerabilgarri eta erabilgarrien abstrakzio geruzak nola diseinatu azaltzen du. MODDALS-ek software produktu lerro eta ontologia diseinu teknikak aplikatzen ditu ezagutza garatuta dauden ontologien antzekotasunen/desberdintasunen arabera sailkatzeko. Planteamendu honek geruza egitura diseinua errazten du. MODDALS ebaluatu da energia domeinurako ontologia berrerabilgarri eta erabilgarri baten egitura diseinatzeko aplikatuz. Diseinatutako geruza egitura erreferentzia gisa hartu da ontologia gartzeko. Egitura onekin, garatutako ontologia berrerabiltzea errazten du aplikazio desberdinetan. Konkretuki, garatutako ontologiak berrerabilpen denbora 0.5 eta 1.2 pertsona-orduetan murriztu du bi aplikazioetan; geruza egitura jarraitzen ez duen ontologia batekin alderatuz.Las ontologĂas semĂĄnticas representan el conocimiento de diferentes dominios, utilizado como base de conocimiento por agentes inteligentes. Las ontologĂas son desarrolladas por diferentes ingenieros y son heterogĂ©neas, afectando a la interoperabilidad entre aplicaciones. Esta interoperabilidad se logra mediante ontologĂas globales que proporcionan una representaciĂłn comĂșn del dominio, las cuales deben proporcionar un balance de reusabilidad-usabilidad para minimizar el esfuerzo de reutilizaciĂłn en diferentes aplicaciones. Para lograr este balance, las metodologĂas de diseño de ontologĂas proponen clasificar en capas de abstracciĂłn el conocimiento del dominio comĂșn a muchas aplicaciones y el que es relevante para aplicaciones especĂficas. Durante el diseño de la estructura de capas, el conocimiento se clasifica partiendo de cero por expertos del dominio e ingenieros de ontologĂas. Por lo tanto, el diseño de ontologĂas reusables y usables en dominios complejos requiere un gran esfuerzo. Las tĂ©cnicas de diseño de lĂneas de producto de software pueden facilitar la clasificaciĂłn del conocimiento analizando las similitudes/diferencias de conocimiento de ontologĂas existentes. En este contexto, el objetivo de la tesis es crear una metodologĂa de diseño de la estructura de capas para ontologĂas que permita clasificar el conocimiento tomando como referencia ontologĂas existentes, y aplicar esta metodologĂa para poder desarrollar ontologĂas reusables y usables en dominios complejos. La metodologĂa MODDALS explica cĂłmo diseñar estructuras de capas para ontologĂas reusables y usables. MODDALS adopta tĂ©cnicas de diseño de lĂneas de producto en combinaciĂłn con tĂ©cnicas de diseño de ontologĂas para clasificar el conocimiento basĂĄndose en las similitudes/diferencias de ontologĂas existentes. Este enfoque facilita el diseño de la estructura de capas de la ontologĂa. La metodologĂa MODDALS se ha evaluado aplicĂĄndola para diseñar la estructura de capas de una ontologĂa global reusable y usable para el dominio de la energĂa. La estructura de capas diseñada se ha tomado como referencia para desarrollar la ontologĂa. Con esta estructura, la ontologĂa resultante simplifica la reutilizaciĂłn de ontologĂas en diferentes aplicaciones. En concreto, la ontologĂa redujo el tiempo de reutilizaciĂłn en 0.5 y 1.2 personas-hora en dos aplicaciones respecto a una ontologĂa global que no sigue una estructura por capas
Ontology Building: An Integrative View of Methodologies
Ontologies are being developed and used in many disciplines now a day and they have become a key tool of data integration and knowledge representation in different domains of interest. The ontology building process identifies the stages through which the ontology should go through during its development. There is a certain set of activities to be performed in each stage of the ontology development process and different methodologies have been proposed by researchers for formalizing the different stages. The present paper investigates the most representative methodologies used in the ontology development to look at the different activities that are performed during the process of ontology development. The paper further attempts to provide an integrative view of the most representative methodologies used in the ontology development to look at the set of different activities that can be performed during the process of the ontology development.
DOI: 10.17762/ijritcc2321-8169.15076
Knowledge formalization in experience feedback processes : an ontology-based approach
Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable
Methodologies, tools and languages for building ontologies. Where is their meeting point?
In this paper we review and compare the main methodologies, tools and languages for building ontologies that have been reported in the literature, as well as the main relationships among them. Ontology technology is nowadays mature enough: many methodologies, tools and languages are already available. The future work in this field should be driven towards the creation of a common integrated workbench for ontology developers to facilitate ontology development, exchange, evaluation, evolution and management, to provide methodological support for these tasks, and translations to and from different ontology languages. This workbench should not be created from scratch, but instead integrating the technology components that are currently available
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