Crossroads: Sharing Social Environment & Genetic Data

United States

Meeting Purpose and Intent:

In order to enhance data sharing and to understand the data infrastructure necessary for next-generation systems science, which will help to alleviate drug abuse, this meeting will focus on sharing social environment/psychosocial and merged social environment/psychosocial and genetic data. Particular emphasis will be placed on identifying barriers and developing recommendations to better facilitate data sharing. Social environment data (SED) are data that include rich environmental, phenotypic, and individual non-biological information, while merged social environment and genetic data (SEGD) include SED but also are linked to, or include, genetic data.

The objectives of this important meeting are to

1. Explore the current culture of sharing drug abuse SED and merged SEGD, as well as consider examples from other areas of research.
2. Highlight data sharing experiences, including consideration of working with shared data, other investigators, institutions, and institutional review boards (IRBs).
3. Highlight the infrastructure that must be in place in order to facilitate sharing.
4. Discuss recent advances and strategies for sharing, including strategies that ensure the protection of human subjects.
5. Identify the next steps for better facilitating sharing drug abuse SED and SEGD.

This meeting initiated a dialogue focused on the sharing of SED and SEGD in the field of drug abuse. Addressing the following questions:

1. What are the implications and realities of data sharing for principal investigators, subjects, local IRBs, and the scientific community?
2. How does a particular scientific community's culture of sharing influence the practical implementation of conducting research with complex data sets?
3. What can be done to better facilitate sharing these types of data?

Meeting Outcome:

Many meeting participants indicated their enthusiasm for sharing and its potential but were unable to follow through on these activities due to lack of resources and infrastructure. Complications include different local IRB practices and a potential disincentive to share given the reward structure in academics, government, and time commitments necessary to make data available for sharing when not factored into the original project. Participants agreed that there is value in sharing data, but the logistics of doing so often make it difficult for investigators. It was clear that NIDA and NIH will have to think creatively about ways to provide incentives, resources, and infrastructure that will support sharing activities among scientists doing this type of research.