OntoEng: A design method for ontology engineering in information systems

This paper addresses the design problem relating to ontology engineering in the discipline of information systems. Ontology engineering is a realm that covers issues related to ontology development and use throughout its life span. Nowadays, ontology as a new innovation promises to improve the design, semantic integration, and utilization of information systems. Ontologies are the backbone of knowledge-based systems. In addition, they establish sharable and reusable common understanding of specific domains amongst people, information systems, and software agents. Notwithstanding, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. On the basis of the gathered experience during the development of V4 Telecoms Business Model Ontology as well as the conducted integration of the related literature from the design science paradigm, this paper introduces OntoEng and its application as a novel systematic design method for ontology engineering

The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain

The goal of the INCF Digital Atlasing Program is to provide the vision and direction necessary to make the rapidly growing collection of multidimensional data of the rodent brain (images, gene expression, etc.) widely accessible and usable to the international research community. This Digital Brain Atlasing Standards Task Force was formed in May 2008 to investigate the state of rodent brain digital atlasing, and formulate standards, guidelines, and policy recommendations.

Our first objective has been the preparation of a detailed document that includes the vision and specific description of an infrastructure, systems and methods capable of serving the scientific goals of the community, as well as practical issues for achieving
the goals. This report builds on the 1st INCF Workshop on Mouse and Rat Brain Digital Atlasing Systems (Boline et al., 2007, _Nature Preceedings_, doi:10.1038/npre.2007.1046.1) and includes a more detailed analysis of both the current state and desired state of digital atlasing along with specific recommendations for achieving these goals

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

Ontology mapping for semantically enabled applications

In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential of semantically enabled or enriched applications and for meaningful insights, such as drug discovery, using machine-learning technologies. We discuss challenges and solutions for better ontology mappings, as well as how to select ontologies before their application. In addition, we describe tools and algorithms for ontology mapping, including evaluation of tool capability and quality of mappings. Finally, we outline the requirements for an ontology mapping service (OMS) and the progress being made towards implementation of such sustainable services

Modeling sample variables with an Experimental Factor Ontology

Motivation: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users

Evaluating (linked) metadata transformations across cultural heritage domains

This paper describes an approach to the evaluation of different aspects in the transformation of existing metadata into Linked data-compliant knowledge bases. At Oslo and Akershus University College of Applied Sciences, in the TORCH project, we are working on three different experimental case studies on extraction and mapping of broadcasting data and the interlinking of these with transformed library data. The case studies are investigating problems of heterogeneity and ambiguity in and between the domains, as well as problems arising in the interlinking process. The proposed approach makes it possible to collaborate on evaluation across different experiments, and to rationalize and streamline the process

Semantic framework for regulatory compliance support

Regulatory Compliance Management (RCM) is a management process, which an organization implements to conform to regulatory guidelines. Some processes that contribute towards automating RCM are: (i) extraction of meaningful entities from the regulatory text and (ii) mapping regulatory guidelines with organisational processes. These processes help in updating the RCM with changes in regulatory guidelines. The update process is still manual since there are comparatively less research in this direction. The Semantic Web technologies are potential candidates in order to make the update process automatic. There are stand-alone frameworks that use Semantic Web technologies such as Information Extraction, Ontology Population, Similarities and Ontology Mapping. However, integration of these innovative approaches in the semantic compliance management has not been explored yet. Considering these two processes as crucial constituents, the aim of this thesis is to automate the processes of RCM. It proposes a framework called, RegCMantic. The proposed framework is designed and developed in two main phases. The first part of the framework extracts the regulatory entities from regulatory guidelines. The extraction of meaningful entities from the regulatory guidelines helps in relating the regulatory guidelines with organisational processes. The proposed framework identifies the document-components and extracts the entities from the document-components. The framework extracts important regulatory entities using four components: (i) parser, (ii) definition terms, (iii) ontological concepts and (iv) rules. The parsers break down a sentence into useful segments. The extraction is carried out by using the definition terms, ontological concepts and the rules in the segments. The entities extracted are the core-entities such as subject, action and obligation, and the aux-entities such as time, place, purpose, procedure and condition. The second part of the framework relates the regulatory guidelines with organisational processes. The proposed framework uses a mapping algorithm, which considers three types of Abstract 3 entities in the regulatory-domain and two types of entities in the process-domains. In the regulatory-domain, the considered entities are regulation-topic, core-entities and aux-entities. Whereas, in the process-domain, the considered entities are subject and action. Using these entities, it computes aggregation of three types of similarity scores: topic-score, core-score and aux-score. The aggregate similarity score determines whether a regulatory guideline is related to an organisational process. The RegCMantic framework is validated through the development of a prototype system. The prototype system implements a case study, which involves regulatory guidelines governing the Pharmaceutical industries in the UK. The evaluation of the results from the case-study has shown improved accuracy in extraction of the regulatory entities and relating regulatory guidelines with organisational processes. This research has contributed in extracting meaningful entities from regulatory guidelines, which are provided in unstructured text and mapping the regulatory guidelines with organisational processes semantically

Ontology Localization

Nuestra meta principal en esta tesis es proponer una solución para construir una ontología multilingüe, a través de la localización automática de una ontología. La noción de localización viene del área de Desarrollo de Software que hace referencia a la adaptación de un producto de software a un ambiente no nativo. En la Ingeniería Ontológica, la localización de ontologías podría ser considerada como un subtipo de la localización de software en el cual el producto es un modelo compartido de un dominio particular, por ejemplo, una ontología, a ser usada por una cierta aplicación. En concreto, nuestro trabajo introduce una nueva propuesta para el problema de multilingüismo, describiendo los métodos, técnicas y herramientas para la localización de recursos ontológicos y cómo el multilingüismo puede ser representado en las ontologías. No es la meta de este trabajo apoyar una única propuesta para la localización de ontologías, sino más bien mostrar la variedad de métodos y técnicas que pueden ser readaptadas de otras áreas de conocimiento para reducir el costo y esfuerzo que significa enriquecer una ontología con información multilingüe. Estamos convencidos de que no hay un único método para la localización de ontologías. Sin embargo, nos concentramos en soluciones automáticas para la localización de estos recursos. La propuesta presentada en esta tesis provee una cobertura global de la actividad de localización para los profesionales ontológicos. En particular, este trabajo ofrece una explicación formal de nuestro proceso general de localización, definiendo las entradas, salidas, y los principales pasos identificados. Además, en la propuesta consideramos algunas dimensiones para localizar una ontología. Estas dimensiones nos permiten establecer una clasificación de técnicas de traducción basadas en métodos tomados de la disciplina de traducción por máquina. Para facilitar el análisis de estas técnicas de traducción, introducimos una estructura de evaluación que cubre sus aspectos principales. Finalmente, ofrecemos una vista intuitiva de todo el ciclo de vida de la localización de ontologías y esbozamos nuestro acercamiento para la definición de una arquitectura de sistema que soporte esta actividad. El modelo propuesto comprende los componentes del sistema, las propiedades visibles de esos componentes, las relaciones entre ellos, y provee además, una base desde la cual sistemas de localización de ontologías pueden ser desarrollados. Las principales contribuciones de este trabajo se resumen como sigue: - Una caracterización y definición de los problemas de localización de ontologías, basado en problemas encontrados en áreas relacionadas. La caracterización propuesta tiene en cuenta tres problemas diferentes de la localización: traducción, gestión de la información, y representación de la información multilingüe. - Una metodología prescriptiva para soportar la actividad de localización de ontologías, basada en las metodologías de localización usadas en Ingeniería del Software e Ingeniería del Conocimiento, tan general como es posible, tal que ésta pueda cubrir un amplio rango de escenarios. - Una clasificación de las técnicas de localización de ontologías, que puede servir para comparar (analíticamente) diferentes sistemas de localización de ontologías, así como también para diseñar nuevos sistemas, tomando ventaja de las soluciones del estado del arte. - Un método integrado para construir sistemas de localización de ontologías en un entorno distribuido y colaborativo, que tenga en cuenta los métodos y técnicas más apropiadas, dependiendo de: i) el dominio de la ontología a ser localizada, y ii) la cantidad de información lingüística requerida para la ontología final. - Un componente modular para soportar el almacenamiento de la información multilingüe asociada a cada término de la ontología. Nuestra propuesta sigue la tendencia actual en la integración de la información multilingüe en las ontologías que sugiere que el conocimiento de la ontología y la información lingüística (multilingüe) estén separados y sean independientes. - Un modelo basado en flujos de trabajo colaborativos para la representación del proceso normalmente seguido en diferentes organizaciones, para coordinar la actividad de localización en diferentes lenguajes naturales. - Una infraestructura integrada implementada dentro del NeOn Toolkit por medio de un conjunto de plug-ins y extensiones que soporten el proceso colaborativo de localización de ontologías