Data Organization

In the realm of scientific research, the organization and management of data play a vital role in facilitating transparency, promoting open science practices, and improving overall research efficiency. One notable approach that has gained recognition for its benefits is the use of the Brain Imaging Data Structure (BIDS) format. Adopting the BIDS format as a standard for data organization brings numerous advantages to the research community.

Transparency is a fundamental aspect of scientific inquiry. By organizing data in the BIDS format, researchers can enhance transparency throughout the research lifecycle. BIDS provides a clear and consistent structure for organizing data, making it easier for other researchers to understand, interpret, and reproduce experiments. The standardized directory and file naming conventions in BIDS foster a shared understanding of data organization, enabling efficient data exchange and collaboration among researchers.

Open science, with its emphasis on making research data openly accessible, reproducible, and usable by others, is a cornerstone of scientific progress. The BIDS format aligns perfectly with the principles of open science. With its well-defined structure and standardized metadata, BIDS facilitates data sharing and dissemination. Researchers can confidently publish their data in BIDS format, knowing that others can easily access and utilize it. This openness promotes collaboration, accelerates discoveries, and fosters a culture of knowledge sharing.

Efficiency is a crucial factor in any research endeavor. By adopting the BIDS format, researchers can streamline their data management workflows and enhance research efficiency. The consistent organization and standardized metadata provided by BIDS simplify data analysis, allowing researchers to focus more on the scientific questions at hand. Automated tools and software packages are readily available for BIDS-compatible data processing, reducing the time and effort required for data preprocessing and analysis. This efficiency enables researchers to dedicate more time to the actual exploration and interpretation of scientific findings.

Moreover, the use of BIDS format ensures compatibility and interoperability across different software tools and analysis pipelines. Researchers can seamlessly integrate their data into a variety of neuroimaging workflows, leveraging a wide range of software tools and methods. This interoperability fosters collaboration, as researchers can easily share and combine data from multiple sources, thus enabling large-scale, multi-site studies and meta-analyses.

For EEG projects, you should consult the BIDS framework. For other projects, or to supplement BIDS, you should use the following organizational scheme or something similar:

1. ProjectName/Data

   • contains a folder for raw data - always keep a copy of the raw (i.e., unprocessed) data & keep it separate from the copy that you're using in your pipeline

   • subject folders for processed data

   • this folder also contains a file documenting demographic & other summary info

2. ProjectName/Analysis

   • contains folders for each type of analysis, e.g., AnalysisOne, AnalysisTwo, etc.

3. ProjectName/Task

   • contains folders for stimuli & presentation scripts, as well as any piloting info/data.

4. ProjectName/Resources

   • contains miscellaneous resources relevant to a project, e.g., ROIs, papers that are direct references for particular methods

5. ProjectName/Scripts

   • contains subfolders for different kinds of scripts, e.g., behav, preproc, helper, model, mvpa, etc.

   • the Scripts folder is git-tracked & contains a README.md file that describes as much info as possible about the study

When you archive the dataset, you are required to format it like this (or something similarly transparent in its organization), so might as well start that way.