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Visualizing trends in federal science investments

NSF Award:

DAT: A Visual Analytics Approach to Science and Innovation Policy  (University of North Carolina at Charlotte)

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Understanding and managing investments in science requires tools that can represent complex and shifting relationships. A visualization tool, developed by University of North Carolina-Charlotte researchers, presents a detailed picture of a large collection of research projects and shows how investment in different research topics evolves over time. 

Because the tool analyzes trends in funding across topics rather than by divisional or organizational categories, NSF senior leadership, program officers and analysts can use it to see NSF's entire funding portfolio spread across all disciplines. A deeper understanding of the current portfolio could improve federal stewardship of research and funding.

Wenwen Dou and William Ribarsky created the topic modeling approach, which classifies research based on project descriptions and then builds an intuitive and interactive visual display to allow users to see large trends and to interact with the data. This approach breaks new ground by improving on current analysis software that tends to: 1) categorize science investment by funding source; and 2) visually represent investment trends using maps and network diagrams but captures only a limited amount of information about the topics under investigation. This ignores much richer information contained in the full text of published papers and other sources.

By providing access to all relevant information, not just brief synopses, governmental officials and analysts can more thoroughly research their policy decisions and evaluations of the effectiveness of funding and assessments of future research directions for individual disciplines.

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  • a visualization tool helps users track federal science investment in different areas over time
The visualization tools allows users to track research areas over time.
Wenwen Dou, William Ribarsky, UNC Charlotte

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