Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : TSCF, INRAE
Durée : 6 mois
Contact : sandro.bimonte@irstea.fr
Date limite de publication : 2021-02-22

Contexte :
Nowadays, more and more trajectory data is collected from new acquisition systems (smartphones, vehicles, etc.). A trajectory is described by temporal and spatial data, and it is accompanied by contextual data (such as field, markets, meteo, etc.). Then, we can consider trajectory data as Big Data presenting 3Vs features: Velocity, Variety and Volume. In particular in the context of the I-Site CAP2025 SupeRob project that aims to provide an information system for the planning and monitoring of autonomous robots planning in the agricultural context a big data set of trajectory data is generated.

Sujet :
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety and volume issues arising from the increasing amounts of heterogeneous data (structured, semi-structured, graph based, etc.) made available. However, when it comes to analyzing these data, traditional data Warehouses (DWs) and OLAP systems fall short because they rely on relational DBMSs for storage and querying, thus constraining data variety into the rigidity of a structured schema. DW and OLAP systems allow the online analysis of huge datasets with simple and userfriendly user interfaces.
This project will provide a preliminary investigation of the performance of MMDBs when used to store multidimensional trajectory Big Data for OLAP analysis. The proposals will be applied to data generated in the context of the SupeRob project to handle robots experts to visually analyze their datasets.

Profil du candidat :
Student with skills in Business Intelligence

Formation et compétences requises :
Excelllent skills in databases
Good skills in Data Warehouse
Skills in spatial data

Adresse d’emploi :
INRAE
9 Avenue Blaise Pascal, Aubiere (Clermont Ferrand)

Document attaché : 202011291300_dossier-m2.pdf