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The Future of Survey Research Conference will convene an interdisciplinary group of researchers from a wide range of academic fields and industries to discuss innovations in social, behavioral, and health surveys. Via a virtual platform, it will foster deliberation centered on renewing and augmenting the extensive survey infrastructure the U.S. has developed over the past half century. It will focus on mapping out potential directions for moving survey research toward the future by brainstorming ideas for cutting-edge substantive and methodological innovations, with the objective of maximizing the potential of survey research and survey data to serve science, governments, and industry.
The virtual conference will bring together scholars and practitioners from diverse backgrounds and fields in the various social and behavioral science areas that employ the highest quality survey research to support their activities. The conference focuses on four subject areas over the two days:
1) Data quality and transparency, to help establish the standards by which data collections are evaluated
2) Survey methods innovations, to assemble novel advances at the research frontier
3) Survey Plus (or looking beyond survey responses), to consider integration of auxiliary data, such as administrative records and other new types of “Big Data”
4) Imagining new institutions, building on the earlier foundations to consider the potential for collaborative innovations in survey research across the social and behavioral sciences, governments, and industry
By convening a diverse group of researchers from different disciplines, this conference will provide a venue to share research findings, network, and encourage new collaborations to bridge disciplinary gaps and catalyze innovations. The conference will help to foster a greater understanding of the challenges and opportunities for survey research in the future, with the possibility of transforming future data collection for U.S. federal agencies and private industry.
Hosted by Duke University with support from the NSF, Award #2040847.