Master Student Internship in Ensuring the re-usability of road safety open data across North West Europe (GRASPER) (M/F)

Reference : ITIS-2019-Intern-002

Type: Intern
Contract type: Internship
Duration: 6 months
Place: Belval

Context

 

Mission will take place in Data Intensive Systems research group (DAISY) aiming to cover all aspects allowing information flows to be transformed into valuable inputs for targeted applications. Big, linked, open and social data sources, complemented with the Internet of Things (IoT) provide the information ground for impact driven innovation.

 

Description

 

BE-GOOD is a transnational project aiming to unlock, re-use and extract value from public open data to develop innovative data-driven services in the area of infrastructure & environment.

Road safety open data is recognized as high value datasets according to the European Commission, however BE-GOOD, in which LIST is the technical partner, allowed the identification of many barriers faced by researchers, civil servants and in general all those involved in road safety in the North-west Europe (NWE) area.

The intern will have to address the following tasks:

  • State-of-the-art: Identification of data required for road safety issues;
  • Mapping the release of road safety open data in NWE;
  • Analysis of available data: types (e.g. networks, traffic, weather, etc.), models, formats, parameters, semantics, quality of data and metadata, etc.;
  • Identification of the barriers to data interoperability;
  • Proposal of solution(s) to overcome identified barriers;

    • Research design taking into account the intern’s background;
    • Design and implementation of a demonstrator based on the intern’s research activities;
    • At least one final scientific publication.

The internship is to be led in an interdisciplinary perspective combining technical approaches (such as data analytics) and qualitative methods, as BE-GOOD allows organizing interviews with road safety practitioners and data scientists from the consortium (NL, FR, etc.).

 


Profile

 

Education

  • Master degree in information science, data science, engineering or computer science

Competencies

  • Experience in data processing and analysis
  • Background in statistics and modelling
  • Development skills especially with Python

Language

  • Working language is English
  • French and Dutch highly appreciated

 

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ITIS-2019-Intern-002


 

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Contact

Dr Slim TURKI
Dr Slim TURKI

 Stéphanie LUCADELLO
Stéphanie LUCADELLO