Maintaining at home of the elderlu, the disabled or convalescent people is a national priority dictated by the progresses in medicine, the population ageing and the evidence of a better efficiency of medications when the patient is in a personnal environment more usual and more reassuring. It is to notice that this option is also conform for mastering the healthcare expenses, within an integrative organisation « from the Hospital to home »… Numerous efforts, in France and in the world, have been devoted, these last twenty years, for giving this objective credible and accessible : development of telecommunications and telemedicine systems, perfecting innovative sensors and autonomous and portable instrumentations, experimentations of supervision systems like « PROSAFE » that constitute the technical basis of the project: « HOMECARE ». So, all the experts are agree to say the technologies for monitoring are matures and the applications very near of expanding if an offer answering the expectations of the users is proposed to the market, estimated at 4 billions of Euros a year. Starting from these conclusions, HOMECARE aims the conception until the validation, in an operationnal site, of a complete « indoor » supervision system for patients suffering from Alzheimer disease: This system designed in the continuation of the « PROSAFE » démonstrator will integrate new on line identification fonctionnalities of people present on the site and completed functions on the multisensorial data fusion, the alarm diagnosis, the medical and other interfaces... Keep in mind that the HOMECARE concept is based on an original approach, already experimentally validated: that is to say, the danger detection via the « measure of distance » between the data coming from a historical learning model of the patient's habits and the real time data taken on his running behaviour. This approach is integrated in a system architecture composed of localisation sensors, identification sensors, data fusion in embedded algorithms, on line modelling, diagnosis and other system-users interfaces… The work programme associates all the competences needed to go from the improvement of reuse through research/development actions until the integration of a complete system answering the users expectations and later on, to an operationnal site validation: this work programme must be concluded by the constitution of a « valorization file » and the launching of an industrial transfer procedure.

DataLift's ambition is to act as a catalyst for the emergence of the Web of data. The web of data is a recently emerged way to publish data on the Web. It is made of large raw data sources interlinked together. It takes advantage of semantic Web technologies in order to ensure interoperability and intelligibility of the data. More specifically, it consists of: * publishing data as RDF graphs: a very simple data format, * linking these data sets together, by identifying equivalent resources in other data sources, * describing the vocabulary used in published data through ontologies. This Web of data has taken a strong acceleration recently with the publication by UK and US governments of public data (data.gov, data.gov.uk). Similar initiatives are flourishing across the world and, in France, data providers such as INSEE or IGN have already started experiments. Various citizen groups such as the Fondation internet nouvelle génération (FING) and RegardCitoyen.org are willing to take advantage of such data and the Agence du Patrimoine Immatériel de l'État (APIE) aims at providing a "portal" for such public data. However, if isolated data publication initiatives using semantic Web technologies exist, they remain limited for several reasons: 1. Similarly to the Web, the power of which comes from the interconnection of pages together through hyperlinks, the Web of data will only make sense if the data it contains are interconnected. A few interlinking tools already exist but require too much manual intervention for reaching Web scale. 2. A large number of ontologies covering various domains are quickly appearing, raising the following problems: many ontologies overlap and require to be aligned together for proper interoperability between the data they describe. Selecting the appropriate ontology for describing a dataset is a tedious task. Once an ontology selected, the data to be published eventually needs to be converted in order to be linked to the ontology. Solving these technical problems requires expertise, which leads to publication processes that are not suited to the publication of large amounts of heterogeneous data. 3. In order to ensure a publication space which is at the same time open and giving to each publisher its rights on the published data, it is necessary to provide methods for rights management and data access. 4. Finally, and again analogically with the Web, a critical amount of published data is needed in order to create a snowball effect similar to the one that led the Web to take the importance it has nowadays. The goal of DataLift is to address these four challenges in an integrated way. More specifically, it will provide a complete path from raw data to fully interlinked, identified, qualified and "certified" linked data sets; it will develop a platform for supporting the processes of: * selecting ontologies for publishing data; * converting data to the appropriate format (RDF using the selected ontology); * interlinking data with other data sources; * publishing linked data. In order to achieve this ambitious program, DataLift will unlock key obstacles in the development of the web of data by performing research on ontology selection and evaluation, on automatic link generation and evolution, on right expression and management.