Division of
Natural and Applied Sciences

Computer Science PhD 

TRAJECTORIES OF LIVING WELL AND AGEING WELL ON ITS TERRITORY 

*Keywords* 

Big Data, Semantic Web, Heterogenous data, Data analysis, Data Lake, Visualization of semantic trajectories 

*Context* 

In South-West of France between Biarritz and Bordeaux, living well and ageing well in the territory represents a challenge recognized by the Landes departmental council, the MACS community of communes and the Syndicat Mixte de St Geours de Maremne, which is responsible for the development and management of the Atlantisud development park. It is estimated that by 2050, there will be 30,000 dependent Landais men and women, compared with 17,000 in 2015. With this in mind, our project aims to help improve the quality of life through digitalization. It will apply to the field of living well and ageing well in the Landes region. The living environment can range from businesses for working people, to housing, mobility, services, leisure activities and so on. The main idea is to make multi-source, massive and heterogeneous data from partners talk to each other, in order to analyze them and, above all, to highlight shortcomings and recommendations for better living in the region. These partners include, for example, the Département des Landes for Habitat, mobility and travel data, or the social landlord XL Habitat, Hubics for building data… All of this complemented by Open Data. The data will be ingested, stored and analyzed in an eco-responsible Data Lake currently being set up. The main challenges lie in (i) modeling semantic trajectories of living well and ageing well for data collection and integration, (ii) defining corresponding indicators for data analysis, and (iii) designing visuals adapted to presenting analysis results to a non-specialist audience. 

*PhD objective* 

The aim of this Computer Science PhD thesis is to propose data analysis and visualization tools to help local decision-makers understand the evolution of the territory. On the basis of the massive and heterogeneous data collected, the aim is to draw semantic trajectories representing citizens’ activities (travel, access to tourist and health areas, housing, shopping, etc.), including changes over time, with forecasts for the future. 

*Literature references* 

– Maxime Masson, Philippe Roose, Christian Sallaberry, Rodrigo Agerri, Marie-Noëlle Bessagnet, Annig Le Parc-Lacayrelle: APs: A Proxemic Framework for Social Media Interactions Modeling and Analysis. IDA 2023: 287-299 

– Cécile Cayèré, Christian Sallaberry, Cyril Faucher, Marie-Noëlle Bessagnet, Philippe Roose, Maxime Masson, Jérémy Richard: Multi-Level and Multiple Aspect Semantic Trajectory Model: Application to the Tourism Domain. ISPRS Int. J. Geo Inf. 10(9): 592 (2021) 

– Matthieu Viry, Marlène Villanova-Oliver: Geovisualisation Generation from Semantic Models: A State of the Art. W2GIS 2023: 155-165 

*Working conditions* 

– University: UPPA - www.univ-pau.fr  

– Research Laboratory: LIUPPA (http://liuppa.univ-pau.fr) in the T2i Team 

– PhD Director: Franck RAVAT (Full Professor) 

– PhD co-Director: Sébastien LABORIE (Associate Professor) 

– Location: Technopôle Domolandes - https://www.domolandes.fr (50 Allée de Cérès, 40230 Saint-Geours-de-Maremne, France) 

– Start: 01/11/2023 

– Duration: 3 years 

– Monthly salary before taxes: 2044€ 

*Application files for candidates* 

– CV 

– Cover letter detailing candidates’s motivation 

– Copy of the diploma 

– Candidate’s Mac or equivalent: marks and ranking 

– Letters of recommandation 

– Contact details for minimum 2 referees 

*IMPORTANT* 

– Deadline to apply: 10/09/2023 

– Auditions for selected candidates: during the week of 18/09/2023 

*CONTACTS*  

– Franck Ravat: Franck.Ravat@irit.fr 

– Sébastien Laborie: Sebastien.Laborie@univ-pau.fr 

– Philippe Roose: Philippe.Roose@univ-pau.fr 

– Christian Sallaberry: christian.sallaberry@univ-pau.fr