CE33 - Interaction, robotique

Situated Visualizations for Personal Analytics – EMBER

Submission summary

This project will study how situated data visualization systems can help people use their personal data (e.g., fitness and physiological data, energy consumption, banking transactions, online social activity,...) for their own benefit. Although personal data is generated in many areas of daily life, it remains underused by individuals. Rarely is personal data subjected to an in-depth analysis and used to inform daily decisions. This research aims to empower individuals to improve their lives by helping them become advanced consumers of their own data.

This research builds on the area of personal visual analytics, which focuses on giving the general public effective and accessible tools to get insights from their own data. Personal visual analytics is a nascent area of research, but has so far focused on scenarios where the data visualization is far removed from the source of the data it refers to. The goal of this project is to address the limitations of traditional platforms of personal data analytics by exploring the potential of situated data visualizations.

In a situated data visualization, the data is directly visualized near the physical space, object, or person it refers to. Situated data visualizations have many potential benefits: they can surface information in the physical environment and allow viewers to interpret data in-context; they can be tailored to highlight spatial connections between data and the physical environment, making it easier to make decisions and act on the physical world in response to the insights gained; and they can embed data into physical environments so that it remains visible over time, making it easier to monitor changes, observe patterns over time and collaborate with other people.

Although the topic of situated visualization is currently gaining traction in research, currently very few real applications exist, and little empirical data is available on how to design such systems. We will address this gap by building functional prototypes whose utility will be evaluated using rigorous empirical methods, and by deriving theories and general design guidelines that extend beyond the problem areas considered.

The overall research program will be broken down into four research problems led by five researchers from three research labs (Inria Saclay, Inria Bordeaux, Sorbonne Université) with complementary areas of expertise. The consortium will be completed by graduate students, a postdoctoral researcher and short-term interns to work on four specific research problems and develop the hardware and software necessary for the successful completion of the project.

This project is expected to generate benefits at multiple levels, including to society (by empowering individuals with technology), to the scientific community (by extending and unifying two nascent research areas), to the academic partners (by reinforcing existing research links and establishing them as leaders on the topic), and to students (by providing them with unique training opportunities with a diverse team of world-class researchers).

Project coordination

Pierre Dragicevic (Centre de Recherche Inria Saclay - Île-de-France)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

ISIR Institut des Systèmes Intelligents et de Robotique
INRIA Bordeaux Sud-Ouest Centre de Recherche Inria Bordeaux - Sud-Ouest
Inria Saclay - Ile-de-France - équipe AVIZ Centre de Recherche Inria Saclay - Île-de-France

Help of the ANR 712,276 euros
Beginning and duration of the scientific project: February 2020 - 48 Months

Useful links

Explorez notre base de projets financés

 

 

ANR makes available its datasets on funded projects, click here to find more.

Sign up for the latest news:
Subscribe to our newsletter