634 research outputs found

    Collaboration in the Semantic Grid: a Basis for e-Learning

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    The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning

    Dealing with uncertain entities in ontology alignment using rough sets

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    This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Ontology alignment facilitates exchange of knowledge among heterogeneous data sources. Many approaches to ontology alignment use multiple similarity measures to map entities between ontologies. However, it remains a key challenge in dealing with uncertain entities for which the employed ontology alignment measures produce conflicting results on similarity of the mapped entities. This paper presents OARS, a rough-set based approach to ontology alignment which achieves a high degree of accuracy in situations where uncertainty arises because of the conflicting results generated by different similarity measures. OARS employs a combinational approach and considers both lexical and structural similarity measures. OARS is extensively evaluated with the benchmark ontologies of the ontology alignment evaluation initiative (OAEI) 2010, and performs best in the aspect of recall in comparison with a number of alignment systems while generating a comparable performance in precision

    How To Build Enterprise Data Models To Achieve Compliance To Standards Or Regulatory Requirements (and share data).

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    Sharing data between organizations is challenging because it is difficult to ensure that those consuming the data accurately interpret it. The promise of the next generation WWW, the semantic Web, is that semantics about shared data will be represented in ontologies and available for automatic and accurate machine processing of data. Thus, there is inter-organizational business value in developing applications that have ontology-based enterprise models at their core. In an ontology-based enterprise model, business rules and definitions are represented as formal axioms, which are applied to enterprise facts to automatically infer facts not explicitly represented. If the proposition to be inferred is a requirement from, say, ISO 9000 or Sarbanes-Oxley, inference constitutes a model-based proof of compliance. In this paper, we detail the development and application of the TOVE ISO 9000 Micro-Theory, a model of ISO 9000 developed using ontologies for quality management (measurement, traceability, and quality management system ontologies). In so doing, we demonstrate that when enterprise models are developed using ontologies, they can be leveraged to support business analytics problems - in particular, compliance evaluation - and are sharable

    Creation and extension of ontologies for describing communications in the context of organizations

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    Thesis submitted to Faculdade de CiĂȘncias e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceThe use of ontologies is nowadays a sufficiently mature and solid field of work to be considered an efficient alternative in knowledge representation. With the crescent growth of the Semantic Web, it is expectable that this alternative tends to emerge even more in the near future. In the context of a collaboration established between FCT-UNL and the R&D department of a national software company, a new solution entitled ECC – Enterprise Communications Center was developed. This application provides a solution to manage the communications that enter, leave or are made within an organization, and includes intelligent classification of communications and conceptual search techniques in a communications repository. As specificity may be the key to obtain acceptable results with these processes, the use of ontologies becomes crucial to represent the existing knowledge about the specific domain of an organization. This work allowed us to guarantee a core set of ontologies that have the power of expressing the general context of the communications made in an organization, and of a methodology based upon a series of concrete steps that provides an effective capability of extending the ontologies to any business domain. By applying these steps, the minimization of the conceptualization and setup effort in new organizations and business domains is guaranteed. The adequacy of the core set of ontologies chosen and of the methodology specified is demonstrated in this thesis by its effective application to a real case-study, which allowed us to work with the different types of sources considered in the methodology and the activities that support its construction and evolution

    Engineering a semantic web trust infrastructure

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    The ability to judge the trustworthiness of information is an important and challenging problem in the field of Semantic Web research. In this thesis, we take an end-to-end look at the challenges posed by trust on the Semantic Web, and present contributions in three areas: a Semantic Web identity vocabulary, a system for bootstrapping trust environments, and a framework for trust aware information management. Typically Semantic Web agents, which consume and produce information, are not described with sufficient information to permit those interacting with them to make good judgements of trustworthiness. A descriptive vocabulary for agent identity is required to enable effective inter agent discourse, and the growth of trust and reputation within the Semantic Web; we therefore present such a foundational identity ontology for describing web-based agents.It is anticipated that the Semantic Web will suffer from a trust network bootstrapping problem. In this thesis, we propose a novel approach which harnesses open data to bootstrap trust in new trust environments. This approach brings together public records published by a range of trusted institutions in order to encourage trust in identities within new environments. Information integrity and provenance are both critical prerequisites for well-founded judgements of information trustworthiness. We propose a modification to the RDF Named Graph data model in order to address serious representational limitations with the named graph proposal, which affect the ability to cleanly represent claims and provenance records. Next, we propose a novel graph based approach for recording the provenance of derived information. This approach offers computational and memory savings while maintaining the ability to answer graph-level provenance questions. In addition, it allows new optimisations such as strategies to avoid needless repeat computation, and a delta-based storage strategy which avoids data duplication.<br/

    Complex adaptive systems based data integration : theory and applications

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    Data Definition Languages (DDLs) have been created and used to represent data in programming languages and in database dictionaries. This representation includes descriptions in the form of data fields and relations in the form of a hierarchy, with the common exception of relational databases where relations are flat. Network computing created an environment that enables relatively easy and inexpensive exchange of data. What followed was the creation of new DDLs claiming better support for automatic data integration. It is uncertain from the literature if any real progress has been made toward achieving an ideal state or limit condition of automatic data integration. This research asserts that difficulties in accomplishing integration are indicative of socio-cultural systems in general and are caused by some measurable attributes common in DDLs. This research’s main contributions are: (1) a theory of data integration requirements to fully support automatic data integration from autonomous heterogeneous data sources; (2) the identification of measurable related abstract attributes (Variety, Tension, and Entropy); (3) the development of tools to measure them. The research uses a multi-theoretic lens to define and articulate these attributes and their measurements. The proposed theory is founded on the Law of Requisite Variety, Information Theory, Complex Adaptive Systems (CAS) theory, Sowa’s Meaning Preservation framework and Zipf distributions of words and meanings. Using the theory, the attributes, and their measures, this research proposes a framework for objectively evaluating the suitability of any data definition language with respect to degrees of automatic data integration. This research uses thirteen data structures constructed with various DDLs from the 1960\u27s to date. No DDL examined (and therefore no DDL similar to those examined) is designed to satisfy the law of requisite variety. No DDL examined is designed to support CAS evolutionary processes that could result in fully automated integration of heterogeneous data sources. There is no significant difference in measures of Variety, Tension, and Entropy among DDLs investigated in this research. A direction to overcome the common limitations discovered in this research is suggested and tested by proposing GlossoMote, a theoretical mathematically sound description language that satisfies the data integration theory requirements. The DDL, named GlossoMote, is not merely a new syntax, it is a drastic departure from existing DDL constructs. The feasibility of the approach is demonstrated with a small scale experiment and evaluated using the proposed assessment framework and other means. The promising results require additional research to evaluate GlossoMote’s approach commercial use potential
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