DataCite
Published February 28, 2023 | Version v2
Report Open

Implementing FAIR Workflows D2.2 Metadata Template Development for Cognitive Neuroscience Research

Creators

  • 1. DataCite
  • 2. Max Planck Institute for Emperical Aesthetics

Contributors

Project leader:

  • 1. DataCite
  • 2. Max Planck Institute for Emperical Aesthetics
  • 3. Stanford

Description

The Implementing FAIR Workflows Project aims to leverage existing persistent identifier infrastructure, research tools, and platforms to build a proof of concept research workflow for neuroscience research that is FAIR on inception. The project will provide an exemplar workflow to enable and encourage the wider neuroscience community to adopt FAIR practices.

Making research outputs FAIR and traceable can be accomplished by applying the correct persistent identifiers (PIDs) and creating rich and complete metadata. However, metadata schemas for PIDs, such as the DataCite metadata schema, are kept discipline-agnostic to ensure wide applicability across domains and resource types. Domain-specific metadata serves research communities with increased discoverability by providing more granular and more relevant facets of data and requires a different, integrated solution. 

As part of the effort to develop domain-specific metadata to make outputs FAIR by adopting semantic standardization and compliance with research community recommendations, the project team has invested in defining and developing a  metadata template for cognitive neuroscience studies with human subjects, using the CEDAR Workbench. This document outlines the background, setup, tools used, the process for metadata definition,  template building, testing, and community feedback. The template in its current form is presented, along with an overview of the challenges encountered while implementing the template.  Future steps entail plans to improve the domain-specific metadata specifications and further evaluate domain ontology building and adoption. We have also identified areas that need improvement, including ease of use of the template interface, and approach to consensus building in the community. Those key future steps will keep the template relevant and useful to the community long term.

Notes

This project was made possible through the support of a grant from Templeton World Charity Foundation, Inc. The opinions expressed in this publication are those of the author(s) and do not necessarily reflect the views of Templeton World Charity Foundation, Inc.

Files

D2.2 Metadata template for human cognitive neuroscience.pdf

Files (2.5 MB)

Additional details

Related works

Is part of
Other: 10.54224/20568 (DOI)
Is supplement to
Output management plan: 10.48321/D1MK72 (DOI)

References

  • Devaraju, Anusuriya, Huber, Robert, Mokrane, Mustapha, Herterich, Patricia, Cepinskas, Linas, de Vries, Jerry, L'Hours, Herve, Davidson, Joy, & White, A. (2022). FAIRsFAIR Data Object Assessment Metrics. https://doi.org/10.5281/ZENODO.6461229
  • Gorgolewski, K. J., Auer, T., Calhoun, V. D., Craddock, R. C., Das, S., Duff, E. P., Flandin, G., Ghosh, S. S., Glatard, T., Halchenko, Y. O., Handwerker, D. A., Hanke, M., Keator, D., Li, X., Michael, Z., Maumet, C., Nichols, B. N., Nichols, T. E., Pellman, J., … Poldrack, R. A. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Scientific Data, 3(1), 160044. https://doi.org/10.1038/sdata.2016.44
  • Musen, M. A., O'Connor, M. J., Schultes, E., Martínez-Romero, M., Hardi, J., & Graybeal, J. (2022). Modeling community standards for metadata as templates makes data FAIR. Scientific Data, 9(1), 696. https://doi.org/10.1038/s41597-022-01815-3
  • Poline, J.-B., Kennedy, D. N., Sommer, F. T., Ascoli, G. A., Van Essen, D. C., Ferguson, A. R., Grethe, J. S., Hawrylycz, M. J., Thompson, P. M., Poldrack, R. A., Ghosh, S. S., Keator, D. B., Athey, T. L., Vogelstein, J. T., Mayberg, H. S., & Martone, M. E. (2022). Is Neuroscience FAIR? A Call for Collaborative Standardisation of Neuroscience Data. Neuroinformatics, 20(2), 507–512. https://doi.org/10.1007/s12021-021-09557-0