PhD Student Computer Science

Laboratoire d’Informatique de Grenoble (LIG)

STeamer team – Université Grenoble Alpes

PhD Subject : Spatio-temporal modeling and management of Territorial Statistical Information in the Linked Open Data Web.

Supervisors : Marlène VILLANOVA-OLIVER, Jérôme GENSEL, Hy DAO.

Keywords : Territorial Statistical Information, Territory, Spatio-Temporal Ontology, Spatial Data Infrastructure, Web of Data, Decision Support

The aim of this PhD thesis is to publish Territorial Statistical Information (TSI) as semantic data interlinked with LOD. TSI is complex and multi-dimensional: it is both statistical and spatial information. It covers a multitude of themes and measures values on territorial units whose boundaries often evolve over time. The indicator values also change over time (e.g. evolution of the Unemployment rate) as well as the definitions, and the calculation methods dedicated to these indicators evolve in time and/or over space … Thus, in a single period of time, several definitions of the same concept coexist. Moreover, boundaries between territorial units change (e.g. some units disappear or are renamed) with administrative changes, causing ruptures in statistical time-series. Thus, official long time-series are scarcely available online, preventing territorial stakeholders to analyze indicators over a long period of time. However, time-series of such TSI are paramount. They enable analyzing a territory over a long period of time and likewise judging the effectiveness of reforms.

The aim of this research is to propose innovative ontologies and algorithms to describe and process TSI. Such works will provide the STeDI Spatial Data Infrastructure with new modules to process TSI within the Web of data and to analyze TSI through Graphical User Interface. Territorial statistical data will be interlinked over time and space and put into context through links to other data within the Web (e.g. link to DBpedia resources). This will enhance exchange and understanding of territorial statistical data as well as the understanding of their changes over time. Thus stakeholders involved in spatial planning will have mapping tools for analyzing the evolution of TSI through time. They can explore the effects of territorial reorganization in terms of redistribution of statistical data. Then, the analysis of territories through the evolution of statistics over time, within the Web of data, allows stakeholders to be aware of the impact of past policies, to understand territory at present time and then to better build the future.

Allocation de recherche ARC7 – Innovations, Mobilités, Territoires et Dynamiques Urbaines – Financée par la Région Rhône-Alpes

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