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Researchers from the School of Computing are partnering the development of a computer system to prevent the depletion of world fishery resources

Researchers from the Ontology Engineering Group at the Universidad Politécnica de Madrid’s School of Computing (FIUPM) are developing a world fishery stock depletion assessment and early warning system to prevent stock depletion and overfishing. This system will apply ontology networks to rapidly and effectively locate the exact information required from amongst a huge volume of data in the fishery resources domain.

The research has been developed within the NeOn (Lifecycle Support for Networked Ontologies) integrated project in partnership with the Food and Agriculture Organization of the United Nations (FAO). The project is funded by the European Community under the Sixth Framework Programme.

The results of this research were presented at the Conference of the Spanish Association for Artificial Intelligence (CAEPIA), held last month in Salamanca. CAEPIA is a two-yearly meeting bringing together members of the research community working on topics related to Artificial Intelligence to present and discuss the latest scientific and technological advances in this field. The Artificial Intelligence Technology Transfer meeting (TTIA) was held in conjunction with CAEPIA. The TTIA meeting is a forum where researchers present and discuss work that applies innovative Artificial Intelligence techniques to complex, specific and real problems.

Las jornadas de Transferencia Tecnológica de Inteligencia Artificial (TTIA) se celebraron al mismo tiempo que la CAEPIA. Las jornadas TTIA son el foro en el que se presentan y discuten los trabajos de investigación que suponen una aplicación de técnicas innovadoras de la Inteligencia Artificial a problemas complejos, concretos y reales.

It was at this meeting that the FIUPM’s paper, which was selected as the best TTIA application, was presented. The paper was prepared by Óscar Muñoz-García and Asunción Gómez-Pérez from the Ontology Engineering Group of the FIUPM’s Department of Artificial Intelligence and FAO employees Marta Iglesias-Sucasas and Soonho Kim.

Collaboration with the FAO

The paper presented at Salamanca focused on the study developed in conjunction with the FAO on applying ontology networks in the fisheries domain. The aim of this research is to set up an early warning system to prevent overfishing in waters all over the world and to encourage fisheries planning.

The paper explains how the concept of ontology networks can help to gather, analyse, interpret and disseminate information about nutrition and fishery, which are a key part of the FAO’s research fields.

The paper also describes the group’s work on applying different ontology development lifecycles to the fisheries domain, the results of this research and the methodology used to develop the ontologies in this particular case.

NeOn Consortium

NeOn is a 14.7 million euros project involving 14 European partners, including research institutions and technology companies. The project partners intend to create a new open infrastructure designed to support the development of scalable semantic applications at geographically disperse institutions.

NeOn’s aim is to create the first ever service-oriented, open infrastructure and associated methodology to support the development lifecycle of a new generation of semantic applications.

NeOn is targeting two sectors that are as far apart as pharmaceuticals, and agriculture and fisheries. These sectors handle a huge volume of distributed data that are difficult to integrate and manage with today’s technology.

The FAO’s contribution to the project is to give access to its databases on world fisheries. Additionally, the UN organization’s specialists are working jointly with a group of experts on the development of the new systems. It is as part of this European project that the FIUPM researchers have developed the research described in the paper.

Fisheries sector management problems

Managing world fisheries resources is a very big challenge. 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.

Fish accounts for over 20 per cent of the animal protein intake of more than 2500 million people all over the world. However, some fish banks are shrinking rapidly due to overfishing, misguided fishery practices and environmental degradation.

According to the latest FAO report on the state of agriculture and aquaculture, 52% of fishery resources are fully fished, 20% are moderately fished, 17% are overfished, and 7% are depleted.

By deploying the system under development, the FAO 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.

Ontologies

The technological strategy is based on what are called ontologies. In computing and information sciences, ontologies are a structured set of concepts used to attach meaning to information. The ontology is a data model that represents a set of concepts and the relationships between concepts in the field of knowledge. This related data structure is extremely useful for optimizing knowledge and information usage and databases, as the fisheries study findings corroborated.

 

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