INCF SIG on Neuroimaging Data Model (NIDM)

This SIG will focus on the development of NIDM-Experiment, NIDM-Results, and NIDM-Workflows which form the three interconnected components of the Neuroimaging Data Model (NIDM)

Contact info

Email: incf-nidash-nidm@googlegroups.com

Team

David Keator (Chair) University of California, Irvine, USA  
Camille Maumet (Deputy Chair) University of Warwick, UK
Jean Baptiste Poline University of California, Berkeley, USA
Krzysztof Gorgolewski Stanford University, USA
Karl Helmer Massachusetts General Hospital, USA
Tibor Auer Royal Holloway University of London, UK
Tom Nichols University of Warwick, UK
Jessica A. Turner Psychology Department & Neuroscience Institute, Georgia State University, Atlanta, USA
Satrajit S. Ghosh McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, USA
Samir Das Montreal Neurological Institute, Canada
Tristan Glatard Montreal Neurological Institute, Canada
Guillaume Flandin University College London, UK
Smruti Padhy Massachusetts Institute of Technology, Cambridge, USA
Dorota Jarecka Massachusetts Institute of Technology, Cambridge, USA

Description

About this SIG

Acceleration of scientific discovery relies on our ability to effectively use data often acquired across multiple domains. Typically, subsets of data collections are shared using lab-specific organizational schemes with little or no information provided to give the data context within the broader experimental protocol nor the ability to efficiently use the data or the results of an analysis for reproducibility outside of the originating site. The Neuroimaging Data Model (NIDM; http://nidm.nidash.org/) was developed to provide a linked data format for describing all aspects of the data lifecycle, from raw data through analyses and provenance. This SIG will focus on the development of NIDM-Experiment, NIDM-Results, and NIDM-Workflows which form the three interconnected components of NIDM.

Goal and outcomes

The NIDM SIG will produce a set of specifications and associated tools and developer’s libraries to support broad adoption of NIDM in the community. Each of the three interconnected components of NIDM will produce custom libraries aiding in the conversion and annotation of data appropriate for the specific NIDM component. The SIG will serve as a venue for discussion and coordinated development of the specifications and tools. We will have meetings bi-annually alongside relevant conferences attended by many of the members. We will have regular Google hangout meetings to remain in sync throughout the year setting specific milestones ahead of our bi-annual meetings.

Past meetings

SIG meeting in Kuala Lumpur, August 22, in conjunction with Neuroinformatics 2017.