1 The Use of Text Mining and Data Visualization to Assist in Managing a Scientific Grants Portfolio Elizabeth Ruben, Jerry Phelps, Kristianna Pettibone,

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Presentation transcript:

1 The Use of Text Mining and Data Visualization to Assist in Managing a Scientific Grants Portfolio Elizabeth Ruben, Jerry Phelps, Kristianna Pettibone, and Christina H. Drew Program Analysis Branch Division of Extramural Research and Training National Institute of Environmental Health Sciences November 4, 2011

NIEHS Mission Reduce the burden of human illness and disability by understanding how the environment influences the development and progression of human disease.

Purpose To investigate the use of the text mining/data visualization tool OmniViz™ as a way to: Help us understand patterns in our portfolio that could inform the management of science in a new way. Visualize the assignment of grants to program officers. Explore emerging areas of science. Identify gaps in research. 3

What is OmniViz? Software designed to find and display trends in large amounts of data. Specifically designed for bio-medical, healthcare, pharmaceutical industries. 4

The Process: 1.Obtain our active grant portfolio data. 2.Limit our data set by grant type and program to focus on our Research Grant Program portfolio. 3.Import data into OmniViz. 4.Select text mining algorithm. 5.Identify words to eliminate in the text mining algorithm. (stop words)

Question 1: Can OmniViz help us understand patterns in a portfolio that could inform the management of science in a new way? 6

7 Galaxy: DERT Active Research Grants Note: Labels are created by NIEHS; not the OmniViz default. 7 = Cluster of grants Legend:. = One grant

8 Galaxy: DERT Active Research Grants Note: Labels are created by NIEHS; not the OmniViz default. 8 = Cluster of grants Legend:. = One grant

9 Galaxy: DERT Active Research Grants Note: Labels are created by NIEHS; not the OmniViz default. 9 = Cluster of grants Legend:. = One grant

10 Galaxy: DERT Active Research Grants Note: Labels are created by NIEHS; not the OmniViz default. 10 = Cluster of grants Legend:. = One grant

11 Galaxy: DERT Active Research Grants Note: Labels are created by NIEHS; not the OmniViz default. 11 = Cluster of grants Legend:. = One grant

Initial View of Grant Clusters DERT Active Research Project Grant Portfolio Basic Science Human Studies Transitional Training/Education 12 Note: Labels are created by NIEHS; not the OmniViz default.

13 DNA Repair Grants Program Officer Number of DNA Repair Grants Program Officer 139 Program Officer 22 Program Officer 31 Program Officer 41 Grand Total43 13

Question 2: Understand Program Administrator Workload Distribution Examples of individuals across galaxy visualization Similar/Different Branch Distribution 14

15 Portfolio Distribution Across Program Officers Legend: Program Officer 1 Program Officer 2 15

16 Portfolio Distribution Across Program Officers Legend: Program Officer 1 Program Officer 3 16

17 Portfolio Distribution Across Branches Legend: Branch A Branch B Branch C 17

18 Galaxy: DERT Active Research Grants Basic Science Human Studies Transitional Training/Education 18 Note: Labels are created by NIEHS; not the OmniViz default.

19 Program Officers by Category of Science Program Officer Human Studies TransitionalBasic Science Training and Education Number of Categories KGX 1 LO X 1 LC X 1 LR X 1 FT X 1 DC X 1 CT X 1 CDXX 2 DB X X 2 DS X X 2 JH XX2 LM XX 2 SN XX 2 CL XX2 KM XX 2 MH XX2 AK XXX3 CSXXXX4

20 Pros and Cons of Using This Tool ProCon Big picture view of our portfolio Output Novel way of doing pattern analysis Ability to identify outliers Cool factor is very high Cost of software ($1,000 annually for education and federal government) Steep learning curve Transferring output to PowerPoint is challenging Difficult to interpret

What questions could this method of analysis answer for you? Strategic planning Emerging areas of science Gaps in research Institute/Center niches/across all Institutes/Centers 21

Contact Information Elizabeth Ruben: