PhD Position F/M Knowledge Graph-Based Provenance Modeling for the Evaluation of Interactive Visualization Tools

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Contract type : Fixed-term contract

Level of qualifications required : Graduate degree or equivalent

Fonction : PhD Position

Level of experience : Recently graduated

About the research centre or Inria department

The Inria centre at Université Côte d'Azur includes 42 research teams and 9 support services. The centre's staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), but also with the regiona economic players.

With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur  is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.

Context

This PhD subject is part of a doctoral grant awarded by the Université Côte d'Azur following a selection process. The start date is October 1, but can be flexible up to one month.  More details on the selection process can be found on
https://webusers.i3s.unice.fr/edstic/3-2-candidater-en.php and for EUR-DS4H https://ds4h.univ-cotedazur.eu/education/phd

This thesis aims to advance analytical provenance in visualization tools by developing a structured model based on the Semantic Web to systematically capture and represent provenance data. It also proposes an evaluation framework to assess the usability and effectiveness of visualization techniques using this data. Finally, an extensible solution will be designed to seamlessly integrate provenance tracking into widely used web-based visualization libraries like D3.js, without requiring major modifications to existing systems.

Assignment

This PhD research aims to advance analytical provenance in visualization tools by addressing the following key objectives:

  • Designing a Provenance Model: Developing a structured approach based on Semantic Web models to systematically capture and represent analytical provenance data across diverse visualization tools.
  • Establishing an Evaluation Framework: Proposing a methodology that leverages provenance data to assess the usability and effectiveness of visualization techniques, providing insights into how different tools support user reasoning.
  • Seamless Integration with Web-Based Visualization Libraries: Creating an extensible solution that can be easily incorporated into widely used libraries like D3.js, enabling provenance tracking without requiring significant modifications to existing visualization systems.

Main activities

The planned activities are as follows:

  • Literature Review and State-of-the-Art Analysis: Conduct a comprehensive review of existing work on analytical provenance, visualization evaluation to establish a theoretical foundation for the research.
  • Development of a Provenance Model: Design a structured model using Semantic Web languages to represent analytical provenance, ensuring interoperability and extensibility.
  • Implementation of Data Collection Methods: Develop techniques to systematically collect provenance data from visualization tools, considering different types of user interactions and exploration strategies.
  • Integration with Web-Based Visualization Tools: Develop an approach for seamlessly embedding provenance tracking mechanisms into widely used visualization libraries such as D3.js, ensuring ease of adoption by developers.
  • Design and Implementation of an Evaluation Framework: Define a methodology that leverages analytical provenance data to assess the usability and effectiveness of visualization techniques, providing insights into user reasoning and decision-making processes.
  • Case Study Application and Validation: Implement the proposed provenance model and evaluation framework within real-world visualization tools, including MGExplorer for multivariate graph exploration and eSTIMe for mobility data analysis, to assess their effectiveness and adaptability.
  • User-Centered Data Collection through Hackathons: Organize hackathons with end-users to gather analytical provenance data from the case study tools, evaluating the framework's ability to capture and analyze user interactions in practical scenarios.
  • Dissemination of Results: Publish findings in high-impact conferences and journals, participate in research collaborations, and present results at scientific events.
  • Collaboration and Supervision: Work closely with the research team and participate in the supervision of master’s students involved in related topics.

Skills

Technical skills and level required : semantic web, data visualization, human-computer interaction

Languages : english

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Remuneration

Duration: 36 months
Gross Salary per month: 2200€ (2025)