An Ontology-based Collaborative Knowledge Management Network to Enhance the Reusability of Inter-organizational Knowledge

A number of knowledge management (KM) approaches based on individual organizational KM strategies and business requirements have been developed without taking system interoperation into consideration. In this paper, a collaborative inter-organizational KM network is proposed to allow various organizations to access and retrieve inter-organizational knowledge. While knowledge engineers can reuse the inter-organizational knowledge to create and evaluate its own organizational knowledge, general users benefit from the effectiveness and efficiency of searching for relevant inter-organizational knowledge within the networ

Fusing Automatically Extracted Annotations for the Semantic Web

This research focuses on the problem of semantic data fusion. Although various solutions have been developed in the research communities focusing on databases and formal logic, the choice of an appropriate algorithm is non-trivial because the performance of each algorithm and its optimal configuration parameters depend on the type of data, to which the algorithm is applied. In order to be reusable, the fusion system must be able to select appropriate techniques and use them in combination. Moreover, because of the varying reliability of data sources and algorithms performing fusion subtasks, uncertainty is an inherent feature of semantically annotated data and has to be taken into account by the fusion system. Finally, the issue of schema heterogeneity can have a negative impact on the fusion performance. To address these issues, we propose KnoFuss: an architecture for Semantic Web data integration based on the principles of problem-solving methods. Algorithms dealing with different fusion subtasks are represented as components of a modular architecture, and their capabilities are described formally. This allows the architecture to select appropriate methods and configure them depending on the processed data. In order to handle uncertainty, we propose a novel algorithm based on the Dempster-Shafer belief propagation. KnoFuss employs this algorithm to reason about uncertain data and method results in order to refine the fused knowledge base. Tests show that these solutions lead to improved fusion performance. Finally, we addressed the problem of data fusion in the presence of schema heterogeneity. We extended the KnoFuss framework to exploit results of automatic schema alignment tools and proposed our own schema matching algorithm aimed at facilitating data fusion in the Linked Data environment. We conducted experiments with this approach and obtained a substantial improvement in performance in comparison with public data repositories

Ontological View-driven Semantic Integration in Open Environments

In an open computing environment, such as the World Wide Web or an enterprise Intranet, various information systems are expected to work together to support information exchange, processing, and integration. However, information systems are usually built by different people, at different times, to fulfil different requirements and goals. Consequently, in the absence of an architectural framework for information integration geared toward semantic integration, there are widely varying viewpoints and assumptions regarding what is essentially the same subject. Therefore, communication among the components supporting various applications is not possible without at least some translation. This problem, however, is much more than a simple agreement on tags or mappings between roughly equivalent sets of tags in related standards. Industry-wide initiatives and academic studies have shown that complex representation issues can arise. To deal with these issues, a deep understanding and appropriate treatment of semantic integration is needed. Ontology is an important and widely accepted approach for semantic integration. However, usually there are no explicit ontologies with information systems. Rather, the associated semantics are implied within the supporting information model. It reflects a specific view of the conceptualization that is implicitly defining an ontological view. This research proposes to adopt ontological views to facilitate semantic integration for information systems in open environments. It proposes a theoretical foundation of ontological views, practical assumptions, and related solutions for research issues. The proposed solutions mainly focus on three aspects: the architecture of a semantic integration enabled environment, ontological view modeling and representation, and semantic equivalence relationship discovery. The solutions are applied to the collaborative intelligence project for the collaborative promotion / advertisement domain. Various quality aspects of the solutions are evaluated and future directions of the research are discussed

The MOUSE approach: Mapping Ontologies using UML for System Engineers

To address the problem of semantic heterogeneity, there has been a large body of research directed toward the study of semantic mapping technologies. Although various semantic mapping technologies have been investigated,  facilitating the process for domain experts to perform a semantic data integration task is still not easy. This is because one is required not only to possess domain expertise but also to have a good understanding of knowledge engineering. This paper proposes an approach that automatically transforms an abstract semantic mapping syntax into a concrete executable mapping syntax, we call this approach MOUSE (Mapping Ontologies using UML for System Engineers). In order to evaluate MOUSE, an implementation of this approach for a semantic data integration use case has been developed (called SDI, Semantic Data Integration). The aim is to enable domain experts, particularly system engineers, to undertake mappings using a technology that they are familiar with (UML), while ensuring the created mappings are accurate and the approach is easy to use. The proposed UML-based abstract mapping syntax is evaluated through usability experiments conducted in a lab environment by participants who have skills equivalent to real life system engineers using the SDI tool. Results from the evaluations show that the participants could correctly undertake the semantic data integration task using the MOUSE approach while maintaining accuracy and usability (in terms of ease of use)

Methodology for enterprise interoperability assessment

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresWith the evolution of modern enterprises and the increasing market competitiveness, the creation of ecosystems with large amounts of data and knowledge generally needing to be exchanged electronically, is arising. However, this enterprise inter and intra-connectivity is suffering from interoperability issues. Not visible when it is effective, the lack of interoperability poses a series of challenging problems to the industrial community, which can reduce the envisaged efficiency and increase costs. Those problems are mostly caused by misinterpretations of data at the systems level, but problems at the organizational and human levels may pose equivalent difficulties. Existing research and technology provides several frameworks to assist the development of collaborative environments and enterprise networks with well-defined methods to facilitate interoperability. Nonetheless, the interoperability process is not guaranteed and is not easily sustainable, changing upon frequent market and requirement variations. For these reasons, there is a need for a testing methodology to assess the capability of enterprises to cooperate at a certain point in time. This dissertation proposes a methodology to assess that capability, with a corresponding framework to evaluate the interoperability process, applying eliminatory tests to assess the structure of the organizations, the conceptual models and their implementation. This work contributes to increase the chances enterprises have of interoperating effectively, and enables the adoption of extraordinary measures to improve their current interoperability situation

Semantic adaptability for the systems interoperability

In the current global and competitive business context, it is essential that enterprises adapt their knowledge resources in order to smoothly interact and collaborate with others. However, due to the existent multiculturalism of people and enterprises, there are different representation views of business processes or products, even inside a same domain. Consequently, one of the main problems found in the interoperability between enterprise systems and applications is related to semantics. The integration and sharing of enterprises knowledge to build a common lexicon, plays an important role to the semantic adaptability of the information systems. The author proposes a framework to support the development of systems to manage dynamic semantic adaptability resolution. It allows different organisations to participate in a common knowledge base building, letting at the same time maintain their own views of the domain, without compromising the integration between them. Thus, systems are able to be aware of new knowledge, and have the capacity to learn from it and to manage its semantic interoperability in a dynamic and adaptable way. The author endorses the vision that in the near future, the semantic adaptability skills of the enterprise systems will be the booster to enterprises collaboration and the appearance of new business opportunities