Overview

The FBI.data project, one of the key missions of France-BioImaging, addresses the questions related to the computational analysis and handling of image data. 

New methodological approaches to extract information from massive amounts of image data are definitively required. If not developed concomitantly, the lack of accurate methods in this field can become the real bottleneck of innovative bioimaging approaches.

Several lines of research and development can be delineated:

  1. Image processing and analysis solutions for bioimaging data quantification and modeling,
  2. Intelligent image data archival and retrieval,
  3. High performance computing infrastructures dedicated to massive computational demands.

Our goals

Quantitative Bioimage Informatics – Image Processing

All technologies offered or developed inside France-BioImaging generate BIG DATA, comparable to the volume produced by NGS (New Generation Sequencing).

This work focuses on these big data processing , analysis and perform intensive development of innovative algorithms, software and automation of image treatment workflows.

BioImage Analysis and Data Management

Facing the volume of Massive Data produced by new technologies requires intelligent image data management, archival and retrieval.

Consequently the use of high performance computing infrastructures dedicated to massive computation is mandatory.

Knowing the nodes and sites needs in this matter and making a precise survey of strength and weaknesses inside France-BioImaging community, is its first mission.

Then, integration to a common and dedicated infrastructure or association to existing ones in other national INBS (Infrastructure Nationale en Biologie et Santé) or International Networks will be decided.

FAIRisation of Data

The FAIRisation of data for Open Science is an initiative fully endorsed by France-BioImaging. Meaning that data are:

  • Findable,
  • Accessible,
  • Interoperable,
  • Reusable.

The benefits for the bioimaging community are numerous:

  • Boost collaboration within the scientific community,
  • Improve transparency and reproducibility,
  • Enhance quality of results,
  • Accelerate scientific progress and method development.