Innovations in Visualization

Dr. Samuel Huron


  • Post Doctorate Researcher at Innovis Lab (University of calgary)
  • Lead Designer at IRI team, Pompidou Center

Research Interests

Short bio:

Samuel Huron is Lead Designer at Institute for Research and Innovation of the Pompidou Center (Paris) and Post doctorate researcher at the University of Calgary in the Innovis Lab.

He successfully defend his Ph.D. on "Constructive Visualization : A token-based paradigm allowing to assemble dynamic visual representation for non-experts" at the Pompidou Center (Paris, France) in September 2014, under the supervision of Jean-Daniel Fekete, Vincent Puig and Sheelagh Carpendale. He graduated first candidate in 2009, Master in New Media Art in Paris 1 Panthéon-Sorbonne. He participated in different design research group at Ecole National Supérieur des Arts décoratifs between 2007 and 2009 ENSAD Lab. For over ten years he has been participating in carrying out multiple creative web projects for a broad range of civic, cultural and corporate clients.

His interest is focusing particularly on computer human interactions and visual languages. Web design specialist, he implements this know-how in the field of visualization. Meanwhile, he is a co fonder of the Parisian hackerspace Fabelier.

Projects at Innovis:

An Exploratory Study of Data Sketching for Visual Representation

Constructing Visual Representations: Investigating the Use of Tangible Tokens

Constructive Visualization


  • May 2015 : Best Paper - Honorable Mention Award for "An Exploratory Study of Data Sketching for Visual Representation" from EuroVis 2015 programme committee. Authors: Jagoda Walny and Samuel Huron and Sheelagh Carpendale
  • May 2014 : Best Paper - Honorable Mention Award for "Constructive Visualization" from ACM DIS 2014 programme committee. Authors: Samuel Huron, Sheelagh Carpendale, Alice Thudt, Anthony Tang, Michael Mauerer
  • Sep 2013 : Best Full Paper, an "Honorary Mention" from IFIP Interact 2013 programme committee : "PolemicTweet: Video Annotation and Analysis through Tagged Tweets". Authors: Huron Samuel, Isenberg Petra, Fekete Jean Daniel (2013)
  • Oct 2012 : Best Poster Award, form IEEE InfoVis 2012, for "Towards Visual Sedimentation". Authors: Huron Samuel, Vuillemot Romain, Fekete Jean Daniel.
  • Oct 2011 : Google Dataviz - Challenge Election 2012. for "Bubble Tv". Authors: Samuel Huron, Raphaël Velt, Romain Vuillemot, Yves-Marie Haussonne

Ph.D. Thesis

Defended September 2014, in the Pompidou Center

Samuel Huron (2014). Constructive Visualization: A token-based paradigm allowing to assemble dynamic visual representation for non-experts PhD thesis. Université Paris-Sud: France.



During the past two decades, information visualisation (InfoVis) research has created new techniques and methods to support data- intensive analyses in science, industry and government. These have enabled a wide range of analyses tasks to be executed, with tasks varying in terms of the type and volume of data involved. However, the majority of this research has focused on static datasets, and the analysis and visualisation tasks tend to be carried out by trained expert users. In more recent years, social changes and technological advances have meant that data have become more and more dynamic, and are consumed by a wider audience. Examples of such dynamic data streams include e-mails, status updates, RSS 1 feeds, versioning systems, social networks and others. These new types of data are used by populations that are not specifically trained in information visualization. Some of these people might consist of casual users, while others might consist of people deeply involved with the data, but in both cases, they would not have received formal training in information visualization. For simplicity, throughout this dissertation, I refer to the people (casual users, novices, data experts) who have not been trained in information visualisation as non-experts.

These social and technological changes have given rise to multiple challenges because most existing visualisation models and techniques are intended for experts, and assume static datasets. Few studies have been conducted that explore these challenges. In this dissertation, with my collaborators, I address the question: Can we empower non-experts in their use of visualisation by enabling them to contribute to data stream analysis as well as to create their own visualizations?

The first step to answering this question is to determine whether people who are not trained in information visualisation and the data sciences can conduct useful dynamic analysis tasks using a visualisation system that is adapted to support their tasks. In the first part of this dissertation I focus on several scenarios and systems where different sized crowds of InfoVis non-experts users (20 to 300 and 2 000 to 700 000 people) use dynamic information visualisation to analyse dynamic data.

Another important issue is the lack of generic design principles for the visual encoding of dynamic visualization. In this dissertation I design, define and explore a design space to represent dynamic data for non-experts. This design space is structured by visual tokens representing data items that provide the constructive material for the assembly over time of different visualizations, from classic representations to new ones. To date, research on visual encoding has been focused on static datasets for specific tasks, leaving generic dynamic approaches unexplored and unexploited.

In this thesis, I propose construction as a design paradigm for non-experts to author simple and dynamic visualizations. This paradigm is inspired by well-established developmental psychological theory as well as past and existing practices of visualisation authoring with tangible elements. I describe the simple conceptual components and processes underlying this paradigm, making it easier for the human computer interaction community to study and support this process for a wide range of visualizations. Finally, I use this paradigm and tangible tokens to study if and how non-experts are able to create, discuss and update their own visualizations. This study allows us to refine our previous model and provide a first exploration into how non-experts perform a visual mapping without software. In summary, this thesis contributes to the understanding of dynamic visualisation for non-expert users.

Selected Publications

Full publication list here.


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