Open AccessEmpowering Data Sharing and Analytics through the Open Data Commons for Traumatic Brain Injury Research
Author(s) -
Austin Chou,
Abel TorresEspin,
J. Russell Huie,
Karen Krukowski,
Sangmi Lee,
Amber Nolan,
Caroline Guglielmetti,
Bridget E. Hawkins,
Myriam M. Chaumeil,
Geoffrey T. Manley,
Michael S. Beattie,
Jacqueline C. Bresnahan,
Maryann Martone,
Jeffrey S. Grethe,
Susanna Rosi,
Adam R. Ferguson
Publication year - 2022
Publication title -
neurotrauma reports
Language(s) - English
Resource type - Journals
ISSN - 2689-288X
DOI - 10.1089/neur.2021.0061
Subject(s) - data sharing , analytics , traumatic brain injury , computer science , data science , machine learning , leverage (statistics) , interoperability , data analysis , artificial intelligence , medicine , data mining , world wide web , psychiatry , alternative medicine , pathology
Traumatic brain injury (TBI) is a major public health problem. Despite considerable research deciphering injury pathophysiology, precision therapies remain elusive. Here, we present large-scale data sharing and machine intelligence approaches to leverage TBI complexity. The Open Data Commons for TBI (ODC-TBI) is a community-centered repository emphasizing Findable, Accessible, Interoperable, and Reusable data sharing and publication with persistent identifiers. Importantly, the ODC-TBI implements data sharing of individual subject data, enabling pooling for high-sample-size, feature-rich data sets for machine learning analytics. We demonstrate pooled ODC-TBI data analyses, starting with descriptive analytics of subject-level data from 11 previously published articles ( N = 1250 subjects) representing six distinct pre-clinical TBI models. Second, we perform unsupervised machine learning on multi-cohort data to identify persistent inflammatory patterns across different studies, improving experimental sensitivity for pro- versus anti-inflammation effects. As funders and journals increasingly mandate open data practices, ODC-TBI will create new scientific opportunities for researchers and facilitate multi-data-set, multi-dimensional analytics toward effective translation.