PhD in Computer Science (M/F) : Computer science thesis (M/F): Design of solutions for collecting SHS data on life courses
- Saint-Martin-d'Hères, Isère
- CDD
- Temps-plein
The thesis will be supervised by Marlène Villanova (Full Pr. in Computer Science, Univ. Grenoble Alpes/LIG) and Pascal Sebille (Ass. Prof. In Sociology/Demography, Univ. Rennes 2, Laboratoire ESO).This computer science thesis will benefit from multidisciplinary supervision (demography, geography, computer science) provided by the members of the consortium involved in the project, of which this thesis will be a part. This project has received financial support from the CNRS through MITI's interdisciplinary programs (80|PRIME - 2024).In the social sciences and humanities, the use of biographical surveys to gather life histories has become widespread. However, while the collection of biographical data using a paper form in the specific Ageven (for Age-Event) format has proved its worth, collecting these retrospective data remains laborious and costly. To date, no digital tool is able to rival this method of data collection. This thesis is part of the CoPaVie project (80 PRIME funding), which aims to develop a data collection tool. The aim is to make a significant contribution to the field of biographical surveys through innovative and operational solutions, by combining the expertise of computer scientists in the development of models, algorithms and digital applications, with the experience acquired by researchers in the humanities and social sciences on this type of survey. A meta-model language, called SaLTo (for Semantic Life Trajectories), has been designed and developed by LIG's Steamer team (Noël, 2019; Gensel et al., 2020), and offers SHS researchers a new way of apprehending the "life history" object. SaLTo makes it possible to jointly manage several dimensions of life histories (family, residential, professional, etc.), made up of episodes and events described by a set of attributes (for example, occupancy status and living space of the dwelling for the residential trajectory). The approach based on the SaLTo meta-model thus enables an SHS expert to build a data model, associated with the biographical survey he intends to conduct and analyze, which will be fed by data collected via an interface to be developed. The design and development of this interface are at the heart of this thesis.
One of the major challenges will be to define and implement graphical components (for data entry and visualization) that will facilitate the interviewee's process of recalling the events that punctuate his or her life story. As part of the CoPaVie project, the PhD student will carry out research aimed at creating an innovative data collection tool that meets the needs expressed by SHS researchers, and takes up the IT challenges posed by the development of a convincing digital alternative to the Ageven paper grid for conducting biographical surveys.The various stages expected are: appropriation of the field of biographical surveys and existing collection tools in SHS, state of the art of software solutions, design and development of a prototype, testing and evaluation of solutions, valorization and publication of results.This computer science thesis is part of a multidisciplinary environment involving researchers in demography, geography, statistics and computer science.This research work in Computer Science will draw on the experience of SHS researchers in survey protocols and available biographical data, which can be mobilized in the design and testing phases of the data collection tool. It will also benefit from the expertise of the team of IT researchers, particularly in life trajectory modeling (SaLTo) and interactive, dynamic and spatio-temporal interfaces.The expected contributions of the thesis will enable us to validate and enhance the contributions of the SaLTo modeling approach, to evolve the methodologies for collecting biographical data in SHS, and to collect semantically rich information that can be exploited in analyses aimed at strengthening understanding of the social, demographic and geographical dynamics of populations.RequirementsResearch Field Computer science Education Level PhD or equivalentResearch Field Mathematics Education Level PhD or equivalentLanguages FRENCH Level BasicResearch Field Computer science Years of Research Experience NoneResearch Field Mathematics » Algorithms Years of Research Experience NoneAdditional InformationWebsite for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Laboratoire d'Informatique de Grenoble Country France City ST MARTIN D HERES GeofieldWhere to apply WebsiteContact CityST MARTIN D HERESSTATUS: EXPIRED
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