Speaker
Description
For our high-content-screening service at TEFOR-Paris-Saclay, we developed a data-management and bioimage-analysis framework, which we share here with the bioimage-analysis-community.
The filesystem-based-image-database (fsdb) is designed to help labs and core facilities manage, analyze, and archive big data while being invisible to the user of the data within.
Using Linux’s authentication and permission system for regulating the access and smb to serve the data, the fsdb is built to run in heterogeneous environments. On connected computers, the fsdb appears as ‘just another hard drive’ containing data with structured but human-readable filenames. This enables the user to use any kind of hardware and software to query, study, and analyze the data.
Working with thousands of big data-sets, we conceived the fsdb for consistently performing mundane tasks such as transferring data. As accessing big data across networks is tiresome, we taught the fsdb to generate ‘secondary data’, lightweight representations, which are quickly accessible across slow networks.
After two complete rewrites and a couple of functionality extensions, we now present the fsdb23 at https://gitlab.com/arnimjenett/fsdb23 and welcome contributions and feedback.
| Authors | Arnim Jenett |
|---|---|
| Keywords | open source, data management, bioimage analysis framework, statistical anatomy, high content screening, |
