Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities
Inria / Raweb 2003
Project: ECOO

Project : ecoo

Section: New Results

Group awareness

Participants : Christophe Bouthier, Gérôme Canals, Alicia Diaz.

Group awareness models and mechanisms have a central situation in the cooperative applications that we are concerned with, because they interact directly with users and are largely responsible for tool acceptation. They allow each participant to be conscious of other participants activities, enhancing in this way the synergy, the coordination and the social links in the group.

Existing mechanisms are too general, as they do not take into account the role and the context of a user, and thus do not provide adapted and pertinent information. Also, they do not support project with an important number of participants. However, these characteristics are primordial in our application domain where roles, objects and groups can be numerous, and the organizational structure can be complex.

We develop two complementary approaches to face these questions: on the one hand advanced mechanisms for group awareness information visualization, and on the other hand, design of a group awareness model taking advantage of an explicit representation of users context for aggregating and adapting information.

Group awareness information visualization

We apply advanced visualization technology of tree diagram data for giving a concise and global representation of group awareness information. Two complementary techniques are combined:

This work has produced an open source visualization library that has been experimented in various domains : medical information (cf 7.4), programming, and knowledge (cf 7.4).

Group awareness and activity context

We use an explicit representation of activity context for on the one hand aggregating and filtering information at the source, and on the other hand for adapting offered information to each user characteristics. Information aggregation is based on Bayesian networks that allows to correlate low level events for abstracting a higher level information. The relationship between source and recipient is implemented by computing a distance between user's contexts. Depending on the distance, we can choose to delay awareness information, to transmit it in a peripheral vision or at the opposite in a very intrusive way.

We apply also this approach in the specific case of practice communities which share common knowledge. Activity context corresponds here to the knowledge and the point of view of a particular user. Bayesian networks are used for following the evolution of knowledge (divergence, convergence) of the different points of view, in the objective to make emerge new knowledge [13].


At short term, our objective is to experiment our mechanisms in the frame of the cooperative work environments developed in ECOO. In a first time, it is a technical integration work of these tools in the platforms; in a second time, it is to develop usage analyses for studying and comparing these mechanisms with regards to existing ones.

At middle term, we will extend adaptation properties of our tools for taking into account the usage context of the cooperation environment. This will allow to offer a continuous support of group awareness, especially for mobile activities disconnected from the usual working environment.