Improving Survey Efficiency with Linked Data: The Survey of Doctorate Recipients Story

Lynn Milan Co-Author
National Center for Science and Engineering Statistics, NSF
 
Flora Lan Co-Author
National Center for Science and Engineering Statistics, NSF
 
Kelly Phou Co-Author
National Center for Science and Engineering Statistics, NSF
 
Wan-Ying Chang Speaker
National Center for Science and Engineering Statistics, NSF
 
Tuesday, Aug 6: 2:45 PM - 3:05 PM
Topic-Contributed Paper Session 
Oregon Convention Center 
Federal surveys are facing a multitude of challenges including recent hikes in data collection costs and declining response rates. These motivate federal agencies to explore alternative sources to meet emerging demands for new data assets. Strategies for improving survey efficiency include augmenting related data and refining content design. The Survey of Doctorate Recipients (SDR), conducted by the National Center for Science and Engineering Statistics within the National Science Foundation, has a developing data linkage program built around a network of data - including scientific publications, federal awards, patents, and research fundings - linked to eligible respondents of the SDR. The linked data are used in this study to evaluate burdens and quality of self-reported data on scientific productiveness and receipt of federal support as well as to assess the potential of replacing or supplementing parts of survey content with external data. Findings inform the feasibility and limitations of using surveys for collecting complex data tracking innovation and output of the doctoral population. The results also identify potential quality issues for external sources.