NDI: A platform-independent data interface and database for neuroscience physiology and imaging experiments

Abstract

Collaboration in neuroscience is impeded by the difficulty of sharing primary data, results, and software across labs. Here we introduce Neuroscience Data Interface (NDI), a platform-independent standard that allows an analyst to use and create software that functions independently from the format of the raw data or the manner in which the data is organized into files. The interface is rooted in a simple vocabulary that describes common apparatus and storage devices used in neuroscience experiments. Results of analyses -and analyses of analyses -are stored as documents in a scalable, queryable database that stores the relationships and history among the experiment elements and documents. The interface allows the development of an application ecosystem where applications can focus on calculation rather than data format or organization. This tool can be used by individual labs to exchange and analyze data, and it can serve to curate neuroscience data for searchable archives.Van Hooser lab NDI

FlywheelTools: Data Curation and Manipulation on the Flywheel Platform

“…In addition to providing functionality for searching and categorizing complex source data, imaging databases enhance reproducible research by providing a clear audit trail of image processing applied to the data and its results, including both derived images and other data. Widely used imaging databases include Collaborative Informatics Neuroimaging Suite (COINS) (Landis et al, 2016), eXtensible Neuroimaging Archive Toolkit (XNAT) (Herrick et al, 2016), Longitudinal Online Research and Imaging System (LORIS) (Vaccarino et al, 2018), and others (Helmer et al, 2011;Sherif et al, 2014;Book et al, 2016;Poldrack and Gorgolewski, 2017;Rogovin et al, 2020). More recently, the commercial platform Flywheel has become widely used due to its modern technology, ease of use, and scalability.…”