Ontology mapping: the state of the art

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping

Progressive Ontology Alignment for Meaning Coordination: an Information-Theoretic Foundation

We elaborate on the mathematical foundations of the meaning coordination problem that agents face in open environments. We investigate to which extend the Barwise-Seligman theory of information flow provides a faithful theoretical description of the partial semantic integration that two agents achieve as they progressively align their underlying ontologies through the sharing of tokens, such as instances. We also discuss the insights and practical implications of the Barwise-Seligman theory with respect to the general meaning coordination proble

Ontology Mapping: The State of the Art

Ontology mapping is seen as a solution provider in today\u27s landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping

Using Formal Concept Analysis and Information Flow for Modelling and Sharing Common Semantics: Lessons Learnt and Emergent Issues

We have been witnessing an explosion of user involvement in knowledge creation, publication and access both from within and between organisations. This is partly due to the widespread adoption of Web technology. But, it also introduces new challenges for knowledge engineers, who have to find suitable ways for sharing and integrating all this knowledge in meaningful chunks. In this paper we are exposing our experiences in using two technologies for capturing, representing and modelling semantic integration that are relatively unknown to the integration practitioners: Information Flow and Formal Concept Analysis

Investigation of synergetic effects in collaboration using Channel Theory

Collaboration is one of the effective approaches that help us to share knowledge together and exchange ideas within a team. Sometimes, novel worthy knowledge that is not held by the members emerges because of the collaboration. Such knowledge often contributes to create prime solutions in the collaboration process. However, the mechanism of generating such new knowledge is implicit. In this paper, a mathematical model of collaboration mechanism is proposed. Channel theory is utilized to accomplish this goal. Collaboration between engineering course students and entertainment media course students was represented by using the proposed model. As the results, there are two infomorphisms were deduced from the classi cations. It means the students could gain new knowledge from the collaboration process and we can say that the collaboration is effective.ROMBUNNO.SS9-

Knowledge management capabilities of lead firms in innovation ecosystems

Knowledge management is a key capability for innovation. Prior research has typically conceptualized and examined knowledge management capabilities as a property of an individual firm or business unit. More recently, however, the locus of competition and innovation has started to shift from the individual firm to firms working together as an ecosystem. In light of these changing realities, we explicate a set of capabilities that are built, maintained, and exercised by the lead firm in order to enhance innovation within ecosystems. We highlight three knowledge management capabilities: (1) knowledge acquisition, (2) knowledge sharing, and (3) knowledge utilization. Drawing on open and closed action strategies firms use to foster team-based innovation, we develop propositions for the knowledge management capabilities of the lead firm. Our approach highlights three salient tensions that arise from team based innovation: autonomy–control, dissent–consent and uncertainty–certainty. We highlight how the three tensions need to be managed across knowledge management capabilities in order to increase the rate of innovation of the ecosystem. In doing so, we contribute to the evolving marketing literature on sensing and responding in ecosystems in order to provide customers with superior value. We discuss the implications for both managers and theory.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s13162-015-0068-

A Cooperative Approach for Composite Ontology Matching

Ontologies have proven to be an essential element in a range of applications in which knowl-edge plays a key role. Resolving the semantic heterogeneity problem is crucial to allow the interoperability between ontology-based systems. This makes automatic ontology matching, as an anticipated solution to semantic heterogeneity, an important, research issue. Many dif-ferent approaches to the matching problem have emerged from the literature. An important issue of ontology matching is to find effective ways of choosing among many techniques and their variations, and then combining their results. An innovative and promising option is to formalize the combination of matching techniques using agent-based approaches, such as cooperative negotiation and argumentation. In this thesis, the formalization of the on-tology matching problem following an agent-based approach is proposed. Such proposal is evaluated using state-of-the-art data sets. The results show that the consensus obtained by negotiation and argumentation represent intermediary values which are closer to the best matcher. As the best matcher may vary depending on specific differences of multiple data sets, cooperative approaches are an advantage. *** RESUMO - Ontologias são elementos essenciais em sistemas baseados em conhecimento. Resolver o problema de heterogeneidade semântica é fundamental para permitira interoperabilidade entre sistemas baseados em ontologias. Mapeamento automático de ontologias pode ser visto como uma solução para esse problema. Diferentes e complementares abordagens para o problema são propostas na literatura. Um aspecto importante em mapeamento consiste em selecionar o conjunto adequado de abordagens e suas variações, e então combinar seus resultados. Uma opção promissora envolve formalizara combinação de técnicas de ma-peamento usando abordagens baseadas em agentes cooperativos, tais como negociação e argumentação. Nesta tese, a formalização do problema de combinação de técnicas de ma-peamento usando tais abordagens é proposta e avaliada. A avaliação, que envolve conjuntos de testes sugeridos pela comunidade científica, permite concluir que o consenso obtido pela negociação e pela argumentação não é exatamente a melhoria de todos os resultados individuais, mas representa os valores intermediários que são próximo da melhor técnica. Considerando que a melhor técnica pode variar dependendo de diferencas específicas de múltiplas bases de dados, abordagens cooperativas são uma vantagem