Abstract
Funding institutions and researchers increasingly expect that data will be shared to increase scientific integrity and provide other scientists with the opportunity to use the data with novel methods that may advance understanding in a particular field of study. In practice, sharing human subject data can be complicated because data must be de-identified prior to sharing. Moreover, integrating varied data types collected in a study can be challenging and time consuming. For example, sharing data from structural imaging studies of a complex disorder requires the integration of imaging, demographic and/or behavioral data in a way that no subject identifiers are included in the de-identified dataset and with new subject labels or identification values that cannot be tracked back to the original ones. We have developed a Java program that users can use to remove identifying information in neuroimaging datasets, while still maintaining the association among different data types from the same subject for further studies. This software provides a series of user interaction wizards to allow users to select data variables to be de-identified, implements functions for auditing and validation of de-identified data, and enables the user to share the de-identified data in a single compressed package through various communication protocols, such as FTPS and SFTP. DeID runs with Windows, Linux, and Mac operating systems and its open architecture allows it to be easily adapted to support a broader array of data types, with the goal of facilitating data sharing. DeID can be obtained at http://www.nitrc.org/projects/deid.
Highlights
Neuroimaging technologies provide a tremendous opportunity to better understand the healthy and impaired human brain (Schmahmann et al, 1999; Irani et al, 2007)
There is a growing expectation that researchers share clinical and experimental data (Poline et al, 2012) with the hope that increased sample sizes and novel methods can lead to more rapid scientific discoveries (Teeters et al, 2008; Miham, 2012; Poldrack, 2012) and enhance scientific integrity
We have provided the DeID tool to increase the feasibility of data sharing
Summary
Neuroimaging technologies provide a tremendous opportunity to better understand the healthy and impaired human brain (Schmahmann et al, 1999; Irani et al, 2007). These expensive studies generate voluminous datasets that can be valuable beyond their initial uses (Drevets, 2001). Funding agencies have established guidelines for sharing these data so that they can be leveraged by other scientists and published findings from the data can be replicated by other research groups (Tenopir et al, 2011). Data sharing is time-consuming and complicated when data were collected from human subjects
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