Behaverse Data Model (BDM)

Unified dataset format for cognitive tests and questionnaires

There are increasing amounts of behavioral data freely available on the internet. Metadata and semantic web make it easier to find them. However, there are large inconsistencies in the structure of those datasets, the names used for the variables, and even in the meaning of common terms. These inconsistencies make it unnecessarily hard to find and use datasets1 and hinder the development of effective tools.

The Behaverse Data Model (BDM) is an ongoing attempt to define a data format for behavioral datasets that unifies a wide range of cognitive tests and questionnaires. It aims to establish conventions for structuring behavioral datasets and their content.

How to use this website

The website is organized into three main parts:

  • Guides: Tutorials and how-tos for integrating BDM into your projects.
  • Specifications: Formal specifications of the BDM datasets.
  • Explanations: Detailed explanations of fundamental concepts and design decisions.

You can also check:

  • Datasets: Examples of datasets that conform to the BDM.
  • Glossary: A controlled vocabulary for cognitive and behavioral data.

Evolution of the BDM

To suggest improvements, please read the design process and visit discussions on GitHub. Everyone is welcome to contribute.

Citation

To learn more about the ideas behind the BDM, see “the structure of behavioral data” on arXiv. If you want to use the BDM in your research, feel free to cite this paper.

@misc{defossez2020structurebehavioraldata,
      title={The structure of behavioral data}, 
      author={Aurélien Defossez and Morteza Ansarinia and Brice Clocher and Emmanuel Schmück and Paul Schrater and Pedro Cardoso-Leite},
      year={2020},
      eprint={2012.12583},
      archivePrefix={arXiv},
      primaryClass={q-bio.NC},
      url={https://arxiv.org/abs/2012.12583}, 
}
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Footnotes

  1. Hulsebos, M., Lin, W., Shankar, S., & Parameswaran, A. (2024, June). It took longer than i was expecting: Why is dataset search still so hard?. In Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics (pp. 1-4). https://doi.org/10.1145/3665939.3665959↩︎