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Innovative computer system could facilitate global fish stock management

Researchers from the Polytechnic University of Madrid's School of Computing (FIUPM) in Spain are working on an assessment and early warning system to prevent depletion and overfishing of world fish stocks. A paper recently presented at an artificial intelligence meeting finds ...

Researchers from the Polytechnic University of Madrid's School of Computing (FIUPM) in Spain are working on an assessment and early warning system to prevent depletion and overfishing of world fish stocks. A paper recently presented at an artificial intelligence meeting finds that ontology networks could help to rapidly and effectively locate the information needed to assess the status of fish stocks from the massive amount of fisheries data available. 'Managing world fish resources is a very big challenge,' the researchers from the university's artificial intelligence department point out. 'To do this, it is essential to be able to get the best and fullest information, as well as to correlate all the diverse factors that can affect fisheries.' Ontologies, used today in many areas of computer science such as artificial intelligence, software engineering or the Semantic Web, are a structured set of concepts used to attach meaning to information. As a data model, they represent a set of concepts and the relationships between concepts in a particular field of knowledge. They are hence a means of organising and accessing huge volumes of data within a short time. By deploying the system under development, fisheries organisations 'could use ontologies and semantic technologies to help countries to monitor fisheries and the level of critical reserves and implement strategies to improve information about the status and trends of capture fisheries,' the computer scientists say. The research is part of the Lifecycle support for Networked Ontologies (NeOn) project, funded with €10 million under the Sixth Framework Programme (FP6). The 14 project partners, including universities and research institutes as well as organisations from the public and private sectors, believe that the large data sets found today in the fisheries and also the pharmaceuticals sector, are not manageable using current technology. This technology was inherited 'from the days of closed, data-poor systems'. Ontology networks, on the other hand, provide the underpinning for 'intelligent access, integration, sharing and use of data'. It is NeOn's aim to create the first ever service-oriented, open infrastructure and associated methodology to support the development lifecycle of a new generation of semantic applications.

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