Methodology for integration of fisher's ecological knowledge in fisheries biology and management using knowledge representation (artificial intelligence)

Presentado na International Conference "Putting Fisher's Knowledge to Work", Vancouver, Canadá, 27-30 agosto de 2001[abstract] The fisheries crisis of the last decades and the overexploitation of a great number of stocks (FAO 1995) have been due mainly to the inadequacy of scientific knowledge, uncertainties in assessments and/or failures of the management systems. These problems are critical when the management of coastal ecosystems and artisanal fisheries is involved. These systems possess great complexity due to the high number of human factors that influence their functioning and the fishing activity. Small-scale coastal fisheries have a much greater social significance than offshore industrial fisheries, despite the larger economical importance of the latter (only in macro-economic terms). The artisanal coastal fisheries in Galicia (NW Spain) are in a general state of overexploitation derived from the mismatch between management (derived implicitly from models designed for industrial finfisheries) and the biological and socioeconomic context. Freire and García-Allut (2000) proposed a new management policy (based on the establishment of territorial users’ rights, the involvement of fishers in the assessment and management process in collaboration with the government agencies, and the use of protected areas and minimum landing sizes as key regulations) to solve the above problems. As well as a new management system, research should pay special attention to the design and use of inexpensive and rapid methodologies to get relevant scientific data, and introduce local or traditional ecological knowledge of the fishers to the assessment and management process. In this paper, we analyze the values and characteristics of fishers’ ecological knowledge (FEK). Using the artisanal coastal fisheries of Galicia as a case study, we present the objectives of the integration of FEK in fisheries biology and management and propose a methodology for that goal. The use of Artificial Intelligence (AI) as a tool for the analysis and integration of FEK is discussed, and the role of Knowledge Representation, a branch of AI, is described to show the epistemological and technological adequacy of the chosen languages and tools in a non-computer science foru

Transformación de ontologías OWL a UML para la indexación y recuperación mediante esquema basado en grafos

El objetivo de este proyecto es conseguir transformar la información disponible en ontologías OWL en modelos UML para la recuperación e indexación mediante esquemas basados en grafos. Para ello, realizaremos una comparación detallada OWL-UML de forma teórica, donde se establecerán las reglas y operaciones necesarias para realizar la equivalencia entre OWL y UML, desarrollando a continuación el sistema que realice esta tarea. Esta comparación OWL-UML supondrá el grueso del proyecto, realizándose un estudio sobre trabajos similares y publicaciones existentes al respecto, y una vez establecida la transformación teórica más apropiada a nuestras necesidades. Esta aplicación estará integrada en un proyecto más grande, que es UMLModels, donde además se podrá realizar la transformación a otros lenguajes como RSHP a través de librerías previamente desarrolladas.The main purpose of this project is to develop a new application in order to transform OWL ontologies to UML models (based on XMI language). In order to achieve this goal, we need to present a comparison between OWL (Web Ontology Language) and UML model, as a necessary step to design the rules for the transformation. In addition, on this project we will be focused on the comparison of OWL – UML , by analyzing papers, academic publications and documentation about this topic. After that, we will decide which transformation best fits our transformation system and we will develop an application that transforms OWL ontologies into UML. Furthermore, its application is included in a bigger project called UMLModels, that allows transformations to other representation models such as RSHP (Relationship Language).Ingeniería Técnica en Informática de Gestió

An Interactive Visual Language for Term Subsumption Languages

A visual language is defined equivalent in expressive power to term subsumption languages expressed in textual form. To each knowledge representation primitive there corresponds a visual form expressing it concisely and completely. The visual language and textual languages are intertranslatable. Expressions in the language are graphs of labeled nodes and directed or undirected arcs. The nodes are labeled textually or iconically and their types are denoted by six different outlines. Computer-readable expressions in the language may be created through a structure editor that ensures that syntactic constraints are obeyed. The editor exports knowledge structures to a knowledge representation server computing subsumption and recognition, and maintaining a hybrid knowledge base of concept definitions and individual assertions. The server can respond to queries graphically displaying the results in the visual language in editable form. Knowledge structures can be entered directly in the edito..

An Interactive Visual Language for Term Subsumption Languages

A visual language is defined equivalent in expressive power to term subsumption languages expressed in textual form. To each knowledge representation primitive there corresponds a visual form expressing it concisely and completely. The visual language and textual languages are intertranslatable. Expressions in the language are graphs of labeled nodes and directed or undirected arcs. The nodes are labeled textually or iconically and their types are denoted by six different outlines. Computer-readable expressions in the language may be created through a structure editor that ensures that syntactic constraints are obeyed. The editor exports knowledge structures to a knowledge representation server computing subsumption and recognition, and maintaining a hybrid knowledge base of concept definitions and individual assertions. The server can respond to queries graphically displaying the results in the visual language in editable form. Knowledge structures can be entered directly in the editor or imported from knowledge acquisition tools such as those supporting repertory grid elicitation and empirical induction. Knowledge structures can be-exported to a range of knowledge-based systems.