Evaluation of the OQuaRE framework for ontology quality

International audienceThe increasing importance of ontologies has resulted in the development of a large number of ontologies in both coordinated and non-coordinated efforts. The number and complexity of such ontologies make hard to ontology and tool developers to select which ontologies to use and reuse. So far, there are no mechanism for making such decisions in an informed manner. Consequently, methods for evaluating ontology quality are required. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies. OQuaRE has been applied to identify the strengths and weaknesses of different ontologies but, so far, this framework has not been evaluated itself. Therefore, in this paper we present the evaluation of OQuaRE, performed by an international panel of experts in ontology engineering. The results include the positive and negative aspects of the current version of OQuaRE, the completeness and utility of the quality metrics included in OQuaRE and the comparison between the results of the manual evaluations done by the experts and the ones obtained by a software implementation of OQuaRE

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

Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies.

Data are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but recently there has been a move to combine multiple ontologies to provide more powerful analytical possibilities. However, it is often not clear how to combine ontologies or how to assess or evaluate the potential design patterns available. Here we use a large and well-characterized dataset of anatomic pathology descriptions from a major study of aging mice. We show how different design patterns based on the MPATH and MA ontologies provide orthogonal axes of analysis, and perform differently in over-representation and semantic similarity applications. We discuss how such a data-driven approach might be used generally to generate and evaluate ontology design patterns.National Institutes of Health (AG038070-05, for the Shock Aging Center) King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/3454-01-01 and FCC/1/1976-08-01. King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. FCS/1/3657-02-0

An ontology knowledge inspection methodology for quality assessment and continuous improvement

Ontology-learning methods were introduced in the knowledge engineering area to automatically build ontologies from natural language texts related to a domain. Despite the initial appeal of these methods, automatically generated ontologies may have errors, inconsistencies, and a poor design quality, all of which must be manually fixed, in order to maintain the validity and usefulness of automated output. In this work, we propose a methodology to assess ontologies quality (quantitatively and graphically) and to fix ontology inconsistencies minimising design defects. The proposed methodology is based on the Deming cycle and is grounded on quality standards that proved effective in the software engineering domain and present high potential to be extended to knowledge engineering quality management. This paper demonstrates that software engineering quality assessment approaches and techniques can be successfully extended and applied to the ontology-fixing and quality improvement problem. The proposed methodology was validated in a testing ontology, by ontology design quality comparison between a manually created and automatically generated ontology.info:eu-repo/semantics/publishedVersio

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

Security Management Framework for the Internet of Things

The increase in the design and development of wireless communication technologies offers multiple opportunities for the management and control of cyber-physical systems with connections between smart and autonomous devices, which provide the delivery of simplified data through the use of cloud computing. Given this relationship with the Internet of Things (IoT), it established the concept of pervasive computing that allows any object to communicate with services, sensors, people, and objects without human intervention. However, the rapid growth of connectivity with smart applications through autonomous systems connected to the internet has allowed the exposure of numerous vulnerabilities in IoT systems by malicious users. This dissertation developed a novel ontology-based cybersecurity framework to improve security in IoT systems using an ontological analysis to adapt appropriate security services addressed to threats. The composition of this proposal explores two approaches: (1) design time, which offers a dynamic method to build security services through the application of a methodology directed to models considering existing business processes; and (2) execution time, which involves monitoring the IoT environment, classifying vulnerabilities and threats, and acting in the environment, ensuring the correct adaptation of existing services. The validation approach was used to demonstrate the feasibility of implementing the proposed cybersecurity framework. It implies the evaluation of the ontology to offer a qualitative evaluation based on the analysis of several criteria and also a proof of concept implemented and tested using specific industrial scenarios. This dissertation has been verified by adopting a methodology that follows the acceptance in the research community through technical validation in the application of the concept in an industrial setting.O aumento no projeto e desenvolvimento de tecnologias de comunicação sem fio oferece múltiplas oportunidades para a gestão e controle de sistemas ciber-físicos com conexões entre dispositivos inteligentes e autônomos, os quais proporcionam a entrega de dados simplificados através do uso da computação em nuvem. Diante dessa relação com a Internet das Coisas (IoT) estabeleceu-se o conceito de computação pervasiva que permite que qualquer objeto possa comunicar com os serviços, sensores, pessoas e objetos sem intervenção humana. Entretanto, o rápido crescimento da conectividade com as aplicações inteligentes através de sistemas autônomos conectados com a internet permitiu a exposição de inúmeras vulnerabilidades dos sistemas IoT para usuários maliciosos. Esta dissertação desenvolveu um novo framework de cibersegurança baseada em ontologia para melhorar a segurança em sistemas IoT usando uma análise ontológica para a adaptação de serviços de segurança apropriados endereçados para as ameaças. A composição dessa proposta explora duas abordagens: (1) tempo de projeto, o qual oferece um método dinâmico para construir serviços de segurança através da aplicação de uma metodologia dirigida a modelos, considerando processos empresariais existentes; e (2) tempo de execução, o qual envolve o monitoramento do ambiente IoT, a classificação de vulnerabilidades e ameaças, e a atuação no ambiente garantindo a correta adaptação dos serviços existentes. Duas abordagens de validação foram utilizadas para demonstrar a viabilidade da implementação do framework de cibersegurança proposto. Isto implica na avaliação da ontologia para oferecer uma avaliação qualitativa baseada na análise de diversos critérios e também uma prova de conceito implementada e testada usando cenários específicos. Esta dissertação foi validada adotando uma metodologia que segue a validação na comunidade científica através da validação técnica na aplicação do nosso conceito em um cenário industrial

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