Users of mobile devices can nowadays easily create large quantities of mobile multimedia documents tracing significant events attended, places visited or, simply, moments of their everyday life. However, they face the challenge of organizing these documents in order to facilitate searching through them at a later time and sharing them with other users. We propose using context awareness and semantic technologies in order to improve and facilitate the organization, annotation, retrieval and sharing of personal mobile multimedia documents. Our approach combines metadata extracted and enriched automatically from the users’ context with annotations provided manually by the users and with annotations inferred by applying user-defined rules to context features. These new contextual metadata are integrated into the processes of annotation, sharing and keyword-based retrieval.

The sustainable management of geographic information through time is fundamental in the field of spatial planning, because handling of long-term statistical indicators is useful for setting up prospective scenarios. Sustainability means the control of complex information which is often incomplete: data come from multiple scales and heterogeneous grids, from various suppliers, at many dates, with a semantic which keeps evolving. Under these conditions, a framework for data quality assessment and estimation of missing values is necessary. This paper draws out a proposition for a system based on an object oriented spatio-temporal data model fit to figure out some relationships of interest when managing missing values, and providing a support for storage and exploitation of metadata through the usage of thematic and geographic ontologies.

This paper presents an approach for incorporating contextual metadata in a keyword-based photo retrieval process. We use our mobile annotation system PhotoMap in order to create metadata describing the photo shoot context (e.g., street address, nearby objects, season, lighting, nearby people...). These metadata are then used to generate a set of stamped words for indexing each photo. We adapt the Vector Space Model (VSM) in order to transform these shoot context words into document-vector terms. Furthermore, spatial reasoning is used for inferring new potential indexing terms. We define methods for weighting those terms and for handling a query matching. We also detail retrieval experiments carried out by using PhotoMap and Flickr geotagged photos. We illustrate the advantages of using Wikipedia georeferenced objects for indexing photos.

The joint development of the Web and of ubiquitous computing increases constantly the potential diversity of the users, access devices and contexts of use of spatiotemporal information systems accessed via these means. Adapting these systems to their users becomes a necessity and a guarantee of usability and longevity. This paper presents a generic approach for the design and generation of adaptive spatio-temporal information systems. The presented framework integrates generic user adaptation mechanisms, aimed at adapting both the content and the presentation of the applications. It gives designers the possibility to integrate these mechanisms into adaptable applications. In order to define the needs and the adaptations of their applications, designers only have to create conceptual models, by instantiating generic models supplied by our framework. MOTS-CLÉS : adaptation à l’utilisateur, adaptativité, conception de systèmes d’information spatio-temporelle, modélisation.

This paper presents GenGHIS, a framework for the design and the generation of spatiotemporal information systems dedicated to the historical survey of natural risks. GenGHIS is a generic spatio-temporal information system that allows designers to create applications for the analysis and the broadcasting of information concerning natural risks by specifying the models that pilot its three modules. GenGHIS contains a presentation module that allows generating interactive spatio-temporal visualization interfaces with multiple views. It also contains an adaptation module, which adapts the application to the user profiles. In order to assist the designers in their modeling task, GenGHIS offers generic models that can be extended by specialization or instantiation. MOTS-CLÉS : système d'information spatio-temporel, gestion des risques naturels, interface de visualisation spatio-temporelle interactive et dynamique, adaptation à l'utilisateur.

This paper presents ASTIS, a framework for the design and generation of adaptive spatio-temporal information systems for the historical study of natural hazard risks. ASTIS is based on a modular architecture in which every module can be personalized by the designer in order to meet the needs of different kinds of users. Personalizations are performed through a model-driven approach, each module is generated from specific models, conceived by the designer. A data management module allows personalizing the content of the application via data viewpoint mechanisms. A presentation module allows designing personalized interactive visualizations. Finally, an adaptation module is in charge of performing the appropriate personalizations at runtime, in order to adapt both the content and the presentation of the information to the user characteristics.

AROM est un systeme de representation de connaissances reposant, a l'image des diagrammes de classes d'UML, sur deux types d'entites de modelisation complementaires : les classes et les associations. Il integre un langage de modelisation algebrique (ou LMA) qui sert de support a differents mecanismes d'inference. Ce langage permet l'ecriture d'equations, de contraintes, et de requetes, impliquant les instances des classes et des associations. La presence d'un module de types en AROM permet d'etendre l'ensemble des types (donc des valeurs et des operateurs) supportes par le LMA. A travers la description du LMA d'AROM, cet article souligne l'apport d'un langage de modelisation algebrique pour un systeme de representation de connaissances tant au niveau de la declarativite qu'en termes des inferences possibles.

RESUME. Cet article presente GenGHIS, un atelier logiciel pour la conception et la realisation de systemes d’information spatio-temporelle dedies au suivi historique des risques naturels (ou SIRN). GenGHIS est un SIRN generique et modulaire. Il permet aux concepteurs de realiser des applications pour l’analyse et la diffusion d’informations relatives aux risques naturels en specifiant les modeles qui configurent les trois modules proposes. GenGHIS integre un module de presentation qui permet de generer des interfaces de visualisation de donnees spatio-temporelles multi-vues et interactives. Il dispose aussi d’un module d’adaptation qui permet de rendre les applications adaptables aux profils des utilisateurs. Afin d’assister les concepteurs de SIRN dans la tâche de modelisation, GenGHIS propose des modeles generiques qui peuvent etre etendus par specialisation ou par instanciation.

Les systemes d'information pour la gestion des risques naturels utilisent habituellement une information pluridimensionnelle, integrant des dimensions thematiques, spatiales, temporelles et documentaires. Pour cette raison, la conception de systemes d'information dedies aux risques naturels (SIRN) necessite des modeles de donnees et des techniques d'interrogation et de visualisation specifiques. Qu 'elle provienne des specialistes de la gestion des risques naturels ou du grand public, la demande de diffusion de l'information a l'aide des SIRN est considerable, mais il existe peu d'outils pour faciliter leur developpement. Nous proposons un cadre logiciel pour la conception et le developpement des SIRN, permettant aux concepteurs de produire facilement des applications dediees aux risques naturels, realise a l'aide d'un systeme de representation de connaissances par objets. Notre approche se base sur l'adaptation d'un systeme d'information generique et guide par des modeles, qui offre une interface pour interroger et visualiser des informations liees aux risques naturels, integrant de facon intuitive des concepts spatio-temporels. Nous proposons un cadre conceptuel qui englobe des concepts spatio-temporels et des concepts communs a tous les genres de risques naturels, qui peuvent etre specialises par les concepteurs de SIRN afin de definir les modeles qui correspondent a leurs propres applications. Tant le modele des donnees que le modele de presentation peuvent etre raffines pour repondre aux besoins precis du SIRN a developper. Nous presentons un SIRN appele SIDIRA, une application dediee au suivi historique des avalanches, developpee a l'aide de notre cadre logiciel.

Nowadays, the management of natural relies on spatio-temporal but also multimedia information. Designing an Information System dedicated to Natural Risks (ISNR) requires a specific approach for modelling, querying, and visualizing such kind of information. Although the needs for developing these Geographical Information Systems are information. Although the needs for developing these Geographical Information Systems are increasing, few tools exit. We present here GenGHIS a tool for designing and developing ISNR. We describe the modelling approach as well as the conceptual kernel common to each ISNR. We illustrate our approach by presenting an application developed with GenGHIS and dedicated to the avalanche risks.