56,240 research outputs found
An Editorial Workflow Approach For Collaborative Ontology Development
The widespread use of ontologies in the last years has raised new challenges for their development and maintenance. Ontology development has transformed from a process normally performed by one ontology engineer into a process performed collaboratively by a team of ontology engineers, who may be geographically distributed and play different roles. For example, editors may propose changes, while authoritative users approve or reject them following a well defined process. This process, however, has only been partially addressed by existing ontology development methods, methodologies, and tool support. Furthermore, in a distributed environment where ontology editors may be working on local copies of the same ontology, strategies should be in place to ensure that changes in one copy are reflected in all of them. In this paper, we propose a workflow-based model for the collaborative development of ontologies in distributed environments and describe the components required to support them. We illustrate our model with a test case in the fishery domain from the United Nations Food and Agriculture Organisation (FAO)
Introducing fuzzy trust for managing belief conflict over semantic web data
Interpreting Semantic Web Data by different human experts can end up in scenarios, where each expert comes up with different and conflicting ideas what a concept can mean and how they relate to other concepts. Software agents that operate on the Semantic Web have to deal with similar scenarios where the interpretation of Semantic Web data that describes the heterogeneous sources becomes contradicting. One such application area of the Semantic Web is ontology mapping where different similarities have to be combined into a more reliable and coherent view, which might easily become unreliable if the conflicting
beliefs in similarities are not managed effectively between the different agents. In this paper we propose a solution for managing this conflict by introducing trust between the mapping agents based on the fuzzy voting model
Run-time risk management in adaptive ICT systems
We will present results of the SERSCIS project related to risk management and mitigation strategies in adaptive multi-stakeholder ICT systems. The SERSCIS approach involves using semantic threat models to support automated design-time threat identification and mitigation analysis. The focus of this paper is the use of these models at run-time for automated threat detection and diagnosis. This is based on a combination of semantic reasoning and Bayesian inference applied to run-time system monitoring data. The resulting dynamic risk management approach is compared to a conventional ISO 27000 type approach, and validation test results presented from an Airport Collaborative Decision Making (A-CDM) scenario involving data exchange between multiple airport service providers
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Enterprise application reuse: Semantic discovery of business grid services
Web services have emerged as a prominent paradigm for the development of distributed software systems as they provide the potential for software to be modularized in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). This paper examines an extension of this paradigm to encompass ‘Grid Services’, which enables software capabilities to be recast with an operational focus and support a heterogeneous mix of business software and data, termed a Business Grid - "the grid of semantic services". The current industrial representation of services is predominantly syntactic however, lacking the fundamental semantic underpinnings required to fulfill the goals of any semantically-oriented Grid. Consequently, the use of semantic technology in support of business software heterogeneity is investigated as a likely tool to support a diverse and distributed software inventory and user. Service discovery architecture is therefore developed that is (a) distributed in form, (2) supports distributed service knowledge and (3) automatically extends service knowledge (as greater descriptive precision is inferred from the operating application system). This discovery engine is used to execute several real-word scenarios in order to develop and test a framework for engineering such grid service knowledge. The examples presented comprise software components taken from a group of Investment Banking systems. Resulting from the research is a framework for engineering servic
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Knowledge modelling for integrating semantic web services in e-government applications
Service integration and domain interoperability are
the basic requirements in the development of current
service-oriented e-Government applications. Semantic
Web and, in particular, Semantic Web Service (SWS)
technology aim to address these issues. However, the integration between e-Government applications and SWS is not an easy task. We argue that a more complex semantic layer needs to be modeled. The aim of our work is to provide an ontological framework that maps such a semantic layer. In this paper, we describe our approach for creating a project-independent and reusable model, and provide a case study that demonstrates its applicability
Toward Self-Organising Service Communities
This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.)
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