SBVR to OWL 2 Mappings - An Automatable and Structural-Rooted Aproach

La amplia aplicabilidad del mapeo de reglas de negocio en sentencias ontológicas ha sido recientemente reconocida. Algunas de las aplicaciones más importantes son: (1) la utilización de razonadores ontológicos para probar la consistencia de la información del dominio del negocio, (2) la generación de una ontología destinada a ser utilizada en la etapa de análisis del proceso de desarrollo de software, y (3) la posibilidad de encapsular la especificación declarativa del conocimiento del negocio en un sistema de información mediante la implementación de una ontología. El lenguaje denominado Semantics of Business Vocabulary and Business Rules (SBVR) brinda soporte a tal enfoque al proveer al experto del negocio una forma lingüistica de describir semánticamente los conceptos y especificar las reglas de negocio, en forma independiente al diseño del sistema de información. Aunque trabajos previos han presentado algunas propuestas, resta definir un enfoque exhaustivo y automatizable de tales mapeos. Este trabajo presenta un conjunto amplio y detallado de transformaciones que permiten la generación automatizable de una ontología implementada en OWL 2, partiendo de la especificación SBVR del dominio del negocio. Tales transformaciones están basadas en la especificación estructural de ambos estándars, y son descriptas mediante un caso de estudio. Se ha realizado un ejemplo real de validación, abordando la factibilidad de los mapeos mediante la evalución de la calidad de la ontología resultante.Wide applicability of mapping business rules expressions to ontology statements have already been recognized. Some of the most important applications are: (1) using of ontology reasoners to prove the consistency of business domain information, (2) generation of an ontology intended to be used in the analysis stage of a software development process, and (3) the possibility of encapsulate the declarative specication of business knowledge into information software systems by means of an implemented ontology. The Semantics of Business Vocabulary and Business Rules (SBVR) supports that approach by providing business people with a linguistic way to semantically describe business concepts and specify business rules in an independent way of any information system design. Previous work have presented some proposals but an exhaustive and automatable approach for them still is lacking. This work presents a broad and detailed set of transformations that allows the automatable generation of an OWL 2 ontology from the SBVR specications of a business domain. Such transformations are rooted on the structural specication of both standards and are depicted through a case study. A real case validation example was performed, approaching the feasibility of the mappings by the quality assessment of the developed ontology.Fil: Reynares, Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnologica Nacional. Facultad Regional Santa Fe. Centro de Investigacion y Desarrollo de Ingenieria en Sistemas de Informacion; ArgentinaFil: Caliusco, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnologica Nacional. Facultad Regional Santa Fe. Centro de Investigacion y Desarrollo de Ingenieria en Sistemas de Informacion; ArgentinaFil: Galli, Maria Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentin

An Experience Report on using the EDON Method for Building a Team Recommender System

Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.Sociedad Argentina de Informática e Investigación Operativa (SADIO

An Experience Report on using the EDON Method for Building a Team Recommender System

Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Applying EDON Methodology and SBVR2OWL Mappings for Building an Ontology-Aware Software

In Ontology-Aware Software, ontologies are use at run time to, for example, use their content in operations of information searching or as database substitutes for information storage. In order to integrate the software development and ontology building processes, involved in building ontologyaware information system a methodology called EDONhave defined. The main disadvantage of this methodology is that the heuristic to generate an implemented ontology from the requirement elicitation is not complete enough. On the other hand, recently, the Object Management Group (OMG) has standardized a language called Semantics of Business Vocabulary and Rules (SBVR) and different approaches have been proposed to map SBVR expressions into the OWL ontology language. In this paper, we report our experience in developing an ontology-aware information system by using an adaptation of the EDON methodology including the SBVR2OWL mappings.V Workshop innovación en sistemas de softwareRed de Universidades con Carreras en Informática (RedUNCI

Towards a semantic model for heritage description

The new ICTs make available a set of tools that can be useful for the digitalization and access of both material and immaterial heritage. Regarding access to digitized heritage, if we want it to be for different people with different training backgrounds, it is necessary to have an element that allows us to "understand" the digitized information. The key element is ontology. This work presents an ontology network for the semantic description of both cultural and natural heritage, as well as each one of the types of manifestations, their actors and historical periods. This network of ontologies will not only allow access to heritage data, but will allow such data to be processed and integrated; further to that, it will become possible to draw conclusions through automatic reasoning.Las nuevas TICs ponen a disposición de la comunidad un conjunto de herramientas que pueden ser útiles para la digitalización y para el acceso al patrimonio tanto material como inmaterial. En cuanto al acceso del patrimonio digitalizado, si pretendemos que el mismo sea para diferentes personas con diferentes conocimientos es necesario contar con un elemento que permita “entender” la información digitalizada. Ese elemento clave son las ontologías. En este trabajo se muestra una red de ontologías para describir la semántica del patrimonio tanto cultural como natural, así como también cada uno de los tipos de manifestaciones, sus actores y períodos históricos. Esta red de ontologías no sólo permitirá el acceso a datos del patrimonio sino que éstos podrán ser procesados, integrados y a partir de allí se podrán extraer conclusiones mediante razonamientos automáticos.Fil: Caliusco, Maria Laura. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Reynares, Emiliano. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gersbach, Martìn. Fundación Patrimonio Abierto; ArgentinaFil: Champenois, Grégoire. Experto en gestión del patrimonio cultural; Argentin

A strategy for analyzing and enriching domain ontologies

During the last years there is an increasing interest on the ontologies. The way in which the semantics of a domain entity is represented in an ontology may di er depending on the requirements that the ontology should satisfy. However, in general the richness is a desired quality attribute for an ontology. The contribution of this paper is a strategy for evaluating and enriching the representation of real entity semantics in a domain ontology. In addition, an application example is discussed.Presentado en el II Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras en Informática (RedUNCI

Developing an Ontology-Based Team Recommender System using EDON Method : An experience Report

Recently, Team Recommender Systems (TRS) have become ex-tremely common because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest infor-mation. In recent years, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. Despite of the advance done, building methodologies for developing ontology-based systems is still a research area. In this paper, we report our experience in developing an ontology-based TRS by using the EDON method. The developed TRS analyses human resource information to recom-mend a work team for a software development project.Sociedad Argentina de Informática e Investigación Operativ

An Experience Report on using the EDON Method for Building a Team Recommender System

Abstract. Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project

An Experience Report on using the EDON Method for Building a Team Recommender System

Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Prototipo de un sistema de búsqueda de documentos basado en anotado semántico

Gran parte del conocimiento presente en las empresas se encuentra almacenado en objetos de conocimiento. Estos objetos deben ser administrados por una plataforma de gestión de conocimiento en su representación original a fin de facilitar su correcto acceso. Para ello, se debe capturar la semántica de su contenido y proveer herramientas para realizar búsquedas inteligentes. En este contexto, se estableció una vinculación entre el CIDISI, la Fundación Sadosky y la empresa Accion Point S.A. para desarrollar una plataforma prototipo que facilite la búsqueda de documentos asociados a los productos que comercializan. Este trabajo describe la experiencia de un proceso de Desarrollo de un Sistema de gestión de documentos basado en una red de ontologías.Sociedad Argentina de Informática e Investigación Operativ