- From: Antoine Zimmermann <antoine.zimmermann@emse.fr>
- Date: Tue, 15 May 2018 08:51:35 +0200
- To: semantic-web <semantic-web@w3.org>
- Cc: Maxime Lefrançois <maxime.lefrancois@emse.fr>, Alessandro CERIONI <acerioni@grandlyon.com>
Dear SemWebers, This open position may be of interest either to you or to your students. Please forward accordingly. Type French Cifre fellowship - http://www.anrt.asso.fr/sites/default/files/plaquette_cifre_en.pdf Title From Open Data to Linked Open Data for geospatial and spatio-temporal data: semanticising metropolitan open data platforms Company Lyon Metropole Alessandro Cerioni <acerioni@grandlyon.com> Academic laboratory Laboratoire Hubert Curien - Connected Intelligence team - https://laboratoirehubertcurien.univ-st-etienne.fr Flavien Balbo <flavien.balbo@emse.fr>, Antoine Zimmermann <antoine.zimmermann@emse.fr>, Maxime Lefrançois, <maxime.lefrancois@emse.fr> Context The open data platform of Lyon Metropole (https://data.grandlyon.com/) publishes a large amount of open data, allowing data re-users to develop applications and innovative services. However, reusing data sets can be sometimes difficult: each data set uses its own business-specific "vocabulary", particular to the context in which it was generated, which limits its understanding. This heterogeneity becomes even more problematic when multiple data sets must be integrated or when a foreign audience wants to grasp the information heritage of a metropolitan area. Technologies and standards from the Web of data specifically aim at solving this type of issues. They especially offer a resource description framework (RDF), allowing interconnecting said resources, to make more explicit their semantics by the use of ontologies. Models and technologies also exist to semanticise data sets by automatically transforming the data. Nonetheless, writing adapted transformations, finding or reusing pieces of transformations, utilising transformations at the scale of open data platforms, are still very difficult scientific tasks that must be addressed. In particular, geospatial and spatio-temporal data constitute the majority of data available on Lyon's open data platform, and more generally urban open data platforms. This type of data contains patterns and similarities that could be exploited to simplifly semanticization. Researchers at École des Mines de Saint-Étienne develop a service-based platform for solving problems related to spatio-temporal data, called Territoire (http://territoire.emse.fr), that also suffers from the same issues regarding the heterogeneity of data sets. The platform is composed of heteregenous services consuming data sets to perform tasks, and could therefore benefit from the semanticization of data. A host of models and tools were proposed to tackle these problems: SPARQL-Generate allowing to generate RDF from documents in heretogeneous formats (http://ci.emse.fr/sparql-generate); UCUM Datatypes allowing to represent dimensionful values using custom datatypes (http://ci.emse.fr/lindt/); the ETSI standard SAREF-SEAS ontology meant to represent engineering-related knowledge. Objectives At the IT department of Lyon Metropole, the main goal is to make the open data platform evolve towards a linked data and semantic web system in order to facilitate their reusing, make the data more understandable and processable, and such that data from other sources in standardised semantic web formats can be interlinked. The hired student at Lyon Metropole will have to: (1) Choose or develop target knowledge models towards which data from the open data plateform should be semanticised; (2) Contribute to evolving the workflow for collecting, curating, processing, annotating, and deploying data, taking into account semantic interoperability and data linkage; (3) Apply his/her research results to improve the way open data are currently provided on the platform. Working environment The PhD candidate will work part time at Lyon Metropole, and part time at École des Mines de Saint-Étienne and the Laboratoire Hubert Curien (University of Saint-Étienne, https://laboratoirehubertcurien.univ-st-etienne.fr) in the Connected Intelligence team. Funding The CIFRE fellow signs a 3 years full time work contract with Lyon Metropole, the gross annual salary will depend on the candidate: gross annual salary of € 23,484. Profile of the candidate The candidate should have a master degree or equivalent in computer science, with strong background in Semantic Web and Web of data. The candidate should also be a good developer, have a very good level (written and oral) in English, good communication skills (oral and written), be autonomous, and show motivation for research. Application instructions Applications must be composed of a Resume, Cover Letter in English, last grade certificate, Recommendation Letters, and any other relevant document, and must be sent in a compressed archive to: Alessandro Cerioni <acerioni@grandlyon.com>, Antoine Zimmermann <antoine.zimmermann@emse.fr>, Maxime Lefrançois, <maxime.lefrancois@emse.fr> - The application is opened until filled. - Once the candidate is selected, the final decision will be made by the French Cifre fellowship program two month later - The PhD thesis is expected to start Q4 2018. -- Antoine Zimmermann Institut Henri Fayol École des Mines de Saint-Étienne 158 cours Fauriel CS 62362 42023 Saint-Étienne Cedex 2 France Tél:+33(0)4 77 42 66 03 Fax:+33(0)4 77 42 66 66 http://www.emse.fr/~zimmermann/ Member of team Connected Intelligence, Laboratoire Hubert Curien
Received on Tuesday, 15 May 2018 06:52:06 UTC