PlugDB (ANR - RNTL) (Feb 2007 - Feb 2010) PlugDB is an ANR (National Agency for Research) project, started in February 2007, coordinated by SMIS team, in collaboration with Gemalto, Santeos, and ALDS. The project goal is to develop a personal data server based on newly available technology. DIM team is involved in two aspects: data exchange and synchronization, and data mining. We have proposed and implemented a generic relational to XML mapping tool, and applied it to produce XML exchange file based on the HL7 CDA-r2 standard format. Concerning data mining, we investigate episode mining in order to trigger alerts from the patient events.
ROSES (ANR - RNTL) (Jan 2008 - Jan 2011) ROSES is a research project financed by the French National Agency for Research (ANR) and supported by the French business cluster ("pôle de compétitivité") CapDigital. It aims at defining a set of web resource syndication services and tools for localizing, querying, generating, composing and personalizing RSS feeds available on the Web. The proposed approach is based on the observation that web content syndication can be considered as a particular large-scale distributed data management problem that might be solved by combining peer-to-peer data sharing infrastructures, XML data management and continuous query processing.
MobiScope (May 2008 - ) MobiScope (Effective Analysis of Mobility and Sensor Data) has been partly supported by Digiteo, in the context of OMTE program. It is mainly a data server especially designed for the emerging applications of mobile sensing through mobile objects. It implements a model view of mobile sensor traces as well as an efficient spatio-temporal query engine.
FURET (ANR - VD) (Sept 2008 - Sept 2012) FURET is an ANR project belonging to the program “Villes Durables”. It aims at optimizing the duration of urban works while taking into account the environmental impact in addition to traditional criteria. The task led by PRiSM-DIM concerns precisely the extension of multi-criteria analysis methods to spatial and temporal criteria. The first challenge will be to model and integrate environmental impact scenarios within a spatiotemporal data warehouse. Then, we need to investigate multi-criteria analyses in order to select only the scenarios minimizing the impact. Our approach is to extend the Skyline queries to spatial and temporal dimensions.