Modeling cardiac rhythm and heart rate using BFO and DOLCE

This paper presents an application ontology for modeling cardiac rhythm and its anomalies such as tachycardia and bradycardia. We use BFO and DOLCE as ontological reference framework in order to compare their impact on ontology design. 

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Federating distributed and heterogeneous information sources in neuroimaging: the NeuroBase Project.

The NeuroBase project aims at studying the requirements for federating, through the Internet, information sources in neuroimaging. These sources are distributed in different experimental sites, hospitals or research centers in cognitive neurosciences, and contain heterogeneous data and image processing programs. More precisely, this project consists in creating of a shared ontology, suitable for supporting various neuroimaging applications, and a computer architecture for accessing and sharing relevant distributed information. We briefly describe the semantic model and report in more details the architecture we chose, based on a media-tor/wrapper approach. To give a flavor of the future deployment of our architecture, we de-scribe a demonstrator that implements the comparison of distributed image processing tools applied to distributed neuroimaging data

GriDB: A Scalable Distributed Database Sharing System for Grid Environments

International audienceGrid computing technologies provide mechanisms that allow the seamless sharing of distributed and heterogeneous resources, such as supercomputers, storage systems, and data sources, in a large-scale and dynamic environment. Research works in data grids have generally focused on applications where data resources are stored in files. However, many scientific applications are highly dependent on database management systems for organizing and storing their data. This stresses the need for developing techniques that enable the sharing of and access to massively distributed, heterogeneous, and autonomous databases created and managed independently by several research institutions. In this paper, we address this issue and propose GriDB, a database sharing technique that has the following desirable characteristics: (1) it supports data indexing at a finer granularity than the file level, enabling content-based search and access; (2) it allows data sharing without a globally shared schema; (3) it is distinguished by its peer-to-peer flavor, making it highly scalable, auto-configurable, and fully decentralized with no need to centralized or dedicated servers

Ontologie de partage de données et d'outils de traitement dans le domaine de la neuroimagerie

Le domaine de la neuroimagerie a connu un essor remarquable, grâce au développement de techniques d'acquisition de haute technicité, apportant au domaine des neurosciences- fondamentales et cliniques- des outils d'investigation d'une qualité sans cesse croissante. C'est l'un des domaines , dans lesquels une infrastructure permettant le partage de données multi-centriques, pourrait apporter une aide décisive au progrès de la recherche.Neurobase est un projet qui cherche à construire un système fédéré, pour le partage de données et d'ouitls de traitement dans le domaine de la neuroimagerie. Cependant, la réalisation de ce type de système soulève plusieurs défis, l'hétérogénéité sémantique constituant certainement le plus critique. Les ontologies se sont révélées être le paradigme clé utilisé pour résoudre le problème de l'hétérogénéité sémantique et assurer l'interopérabilité entre systèmes hétérogènes.Ainsi, cette thèse , initiée dans le cadre du projet Neurobase, a pour but de construire une ontologie pour le partage de données et d'outils de traitement, dans le domaine de la neuroimagerie. Il s'agit de proposer une conceptualisation de ce domaine, pour les différents types d'imagerie ainsi que pour les outils de traitement appliqués à ces images. L'ontologie résultat de la conceptualisation devrait être une ontologie assez générale, pour embrasser tous les besoins du domaine, respecter des principes ontologiques formels, exprimer une sémantique riche, être richement axiomatisée, être rigoureuse, et enfin être consensuelle. La contribution de nos travaux se décline en deux aspects essentiels. Le premier aspect concerne la démarche originale adoptée pour construire nos ontologies, en définissant un cadre de références ontologiques à différents niveaux d'abstraction. Le second aspect concerne la proposition d'ontologies innovantes, qui répondent à certains besoins du domaine de la neuroimagerie, tout en respectant le cadre de références ontologiques adopté.RENNES1-BU Santé (352382103) / SudocRENNES-INRIA Rennes Irisa (352382340) / SudocSudocFranceF

Towards an ontology for sharing medical images and regions of interest in neuroimaging.

International audienceThe goal of the NeuroBase project is to facilitate collaborative research in neuroimaging through a federated system based on semantic web technologies. The cornerstone and focus of this paper is the design of a common semantic model providing a unified view on all data and tools to be shared. For this purpose, we built a multi-layered and multi-components formal ontology. This paper presents two major contributions. The first is related to the general methodology we propose for building an application ontology based on consistent conceptualization choices provided by the DOLCE foundational ontology and core ontologies of domains that we reuse; the second concerns the domain ontology we designed for neuroimaging, which encompasses both the objective nature of image data and the subjective nature of image content, through annotations based on regions of interest made by agents (humans or computer programs). We report on realistic domain use-case queries referring to our application ontology

Anonymisation de graphes de connaissances par anatomisation

International audienc

Anonymisation de graphes de connaissances par anatomisation

International audienc

OntoNeuroBase: a multi-layered application ontology in neuroimaging

OntoNeuroBase is an application ontology that is being developed within the NeuroBase project, which seeks to create a federated system for the management of distributed and heterogeneous information sources in neuroimaging. Having adopted a specific, multi-layered, modular approach to ontology design, we used DOLCE as a foundational ontology together with three core ontologies: I&DA for modelling documents (texts and images), COPS for modelling programs and software and OntoKADS for modelling problem solving activities. Here, we report on how we built OntoNeuroBase by refining the concepts present in the existing modules. Neuroimaging is a very active and rapidly changing field. It is essential to ensure that a newly developed ontology is compatible with other available ontologies and to enable extension of the new ontology to a variety of neuroscience applications. The work reported here is in line with these ambitious objectives