  New technologies and equipment allow for mass treatment of samples and
research teams share acquired data on an always larger scale. In this context
scientists are facing a major data exploitation problem. More precisely, using
these data sets through data mining tools or introducing them in a classical
experimental approach require a preliminary understanding of the information
space, in order to direct the process. But acquiring this grasp on the data is
a complex activity, which is seldom supported by current software tools. The
goal of this paper is to introduce a solution to this scientific data grasp
problem. Illustrated in the Tissue MicroArrays application domain, the proposal
is based on the synthesis notion, which is inspired by Information Retrieval
paradigms. The envisioned synthesis model gives a central role to the study the
researcher wants to conduct, through the task notion. It allows for the
implementation of a task-oriented Information Retrieval prototype system. Cases
studies and user studies were used to validate this prototype system. It opens
interesting prospects for the extension of the model or extensions towards
other application domains.
