4. Science and Technology (S&T) Studies
Can be conducted at different levels:
local (individual),
meso (local, e.g., one institute, one funding agency), or
global level (all of science or world wide).
Using
Statistical Analysis/Profiling
Temporal Analysis (When)
Geospatial Analysis (Where)
Topical Analysis (What)
Network Analysis (With Whom?)
Modeling (Why)

5. Type of Analysis vs. Level of Analysis
Micro/Individual
(1-100 records)
Meso/Local
(101–10,000 records)
Macro/Global
(10,000 < records)
Statistical Analysis/Profiling
Individual person and their expertise profiles
Larger labs, centers, universities, research domains, or states
All of NSF, all of USA, all of science.
Temporal Analysis (When)
Funding portfolio of one individual
Mapping topic bursts in 20-years of PNAS
113 Years of Physics Research
Geospatial Analysis (Where)
Career trajectory of one individual
Mapping a states intellectual landscape
PNAS Publications
Topical Analysis
(What)
Base knowledge from which one grant draws.
Knowledge flows in Chemistry research
VxOrd/Topic maps of NIH funding
Network Analysis
(With Whom?)
NSF Co-PI network of one individual
Co-author network
NSF’s core competency
Model – why
Diff levels=diff algorithms, visual renderings 5

6. Type of Analysis vs. Level of Analysis
Micro/Individual
(1-100 records)
Meso/Local
(101–10,000 records)
Macro/Global
(10,000 < records)
Statistical Analysis/Profiling
Individual person and their expertise profiles
Larger labs, centers, universities, research domains, or states
All of NSF, all of USA, all of science.
Temporal Analysis (When)
Funding portfolio of one individual
Mapping topic bursts in 20-years of PNAS
113 Years of Physics Research
Geospatial Analysis (Where)
Career trajectory of one individual
Mapping a states intellectual landscape
PNAS publciations
Topical Analysis
(What)
Base knowledge from which one grant draws.
Knowledge flows in Chemistry research
VxOrd/Topic maps of NIH funding
Network Analysis
(With Whom?)
NSF Co-PI network of one individual
Co-author network
NIH’s core competency
Many studies combine different types. 6

7. Mapping Indiana’s Intellectual Space
Identify
Pockets of innovation
Pathways from ideas to products
Interplay of industry and academia 7

8. Mapping Topic Bursts
Co-word space of the top 50 highly frequent and bursty words used in the top 10% most highly cited PNAS publications in
Mane & Börner. (2004) PNAS, 101(Suppl. 1):
All locally 8

9. Spatio-Temporal Information Production and Consumption of Major U. S
Spatio-Temporal Information Production and Consumption of Major U.S. Research Institutions Börner, Katy, Penumarthy, Shashikant, Meiss, Mark and Ke, Weimao. (2006) Mapping the Diffusion of Scholarly Knowledge Among Major U.S. Research Institutions. Scientometrics. 68(3), pp
Research questions:
1. Does space still matter
in the Internet age?
2. Does one still have to
study and work at major research
institutions in order to have access to
high quality data and expertise and to produce high quality research?
3. Does the Internet lead to more global citation patterns, i.e., more citation links between papers produced at geographically distant research instructions?
Contributions:
Answer to Qs is YES.
Answer to Qs 3 is NO.
Novel approach to analyzing the dual role of institutions as information producers and consumers and to study and visualize the diffusion of information among them. 9

10. Mapping the Evolution of Co-Authorship Networks Ke, Visvanath & Börner, (2004) Won 1st price at the IEEE InfoVis Contest. 10

11. 11

12. Interactive Science Map of NIH Funding Herr II, Bruce W
Interactive Science Map of NIH Funding Herr II, Bruce W., Talley, Edmund M, Burns, Gully APC, Newman, David & La Rowe, Gavin. (2009). 12

13. Interactive World and Science Map of S&T Jobs Angela Zoss, Michael Connover, Katy Börner (in preparation). 13

14. Science and Technology (S&T) Studies
Results are communicated using
Top-N lists
Profiles
Graphs and charts
Geographic map overlays
Science maps
By means of
Alerts
White papers
Reports
Science forecasts

15. Herr II, Bruce W., Gully Burns, David Newman, Edmund Talley. 2007.
This is a similarity-based cluster map of all grants awarded by the National Institutes of Health (NIH) in Approximately 60,000 grants are represented as dots, color-coded by NIH Institute. To generate the map, the content of each grant was assessed using topic modeling, an unsupervised machine learning method based on statistics of co-occurring words in the grants’ abstracts. Grants were placed on the map using a layout algorithm that clusters grants with similar topic mixtures near each other. Clusters are labeled by the computationally derived topics with the highest word allocations in the underlying grants. The result is a cluster map that provides a global view of the NIH funding landscape that can be interactively explored at multiple levels, see zooms for Cardiac Diseases Research and Neural Circuit Research. Shown on the right are funding portfolios of four institutes together with their top-10 topics. By exploring this map, one can see what topics of research are being heavily pursued, how the topics relate to one another, and what research topics each institute is interested in. The interactive version of the map is shown on the left and is available online at
Herr II, Bruce W., Gully Burns, David Newman, Edmund Talley
A Topic Map of NIH Grants Bloomington, IN. 15

16. US does not just have competition from other countries in the STEM fields, but indicates which fields are most at risk. I also enjoy seeing the non-traditionally considered fields of the social sciences and health services.
U.S. Vulnerabilities in Science - Kevin W. Boyack, Richard Klavans 16

17. This is the first map created from large-scale, world-wide scholarly usage data collected by the MESUR project from some of the world’s most significant publishers, aggregators, and large university consortia. It visualizes the collective flow of how information seekers move from one journal to another in their online navigation behavior.
This map is derived from usage data and therefore also reflects the actions of those who read the literature but rarely publish themselves. As a result, practitioner-driven domains are prominently featured.
The social sciences and humanities are much better connected to the natural sciences than expected. Most scientific domains, including the social science and humanities, are highly interdisciplinary, but the latter more so as shown by the concentration of connections in that part of the network.
Mathematics and physics are not strongly connected. Rather mathematics is part of a sub-cluster positioned in the social sciences and humanities that combines statistics, sociology and production research. Biology is strongly connected to the humanities and social sciences via ecology, bio-diversity and architecture. Practitioner-driven domains such as nursing and tourism are strongly manifested in this map because they are highly populated with non-publishing, non-citing scholars that nevertheless read the relevant literature in their domain.
Bollen, Johan, Herbert Van de Sompel, Aric Hagberg, Luis M.A. Bettencourt, Ryan Chute, Marko A. Rodriquez, Lyudmila Balakireva A Clickstream Map of Science. 17

18. Washington, DC. Courtesy of the Council for Chemical Research.
The Council for Chemical Research (CCR) commissioned expert economists to conduct a two-phase study on the quantitative impact of research and development (R&D) in the chemical sciences. Using patent and scientific literature, a 20-year timeline from basic research to market was determined. Furthermore, the experts identified two major feedback cycles: (I) chemical industry innovation is directly linked to federally-supported foundational research and (II) the $1 billion federal investment is leveraged by industry investment of about $5 billion dollars for invention development and technology commercialization.
Experts also calculated that every dollar invested in R&D by the chemical industry over the past twenty years has generated two dollars in increased operating income, a 17% return on investment after taxes. In 2005, researchers from the Los Alamos National Laboratory examined the macroecomonic impacts of the $10 billion chemical industry income on gross national product (GNP) and jobs. Using the REMI Policy Insight model they determined a GNP multiplier of 4 which, applied to the industry operating income of $10 billion, yields $40 billion in GNP; it also creates 600,000 new jobs, and roughly $8 billion in additional tax revenues each year, some of which is invested in chemical R&D, closing the cycle. The original map appears in “Measure for Measure: Chemical R&D Powers the U.S. Innovation Engine” sponsored and published by CCR (2005).
Council for Chemical Research Chemical R&D Powers the U.S. Innovation Engine.
Washington, DC. Courtesy of the Council for Chemical Research. 18

19. Illuminated Diagram Display
W. Bradford Paley, Kevin W. Boyack, Richard Kalvans, and Katy Börner (2007)
Mapping, Illuminating, and Interacting with Science. SIGGRAPH 2007.
Questions:
Who is doing research on what topic and where?
What is the ‘footprint’ of interdisciplinary research fields?
What impact have scientists?
Contributions:
Interactive, high resolution interface to access and make sense of data about scholarly activity.
Large-scale, high resolution prints illuminated via projector or screen.
Interactive touch panel.
VxOrd graph layout tool to recursively cluster the 820,000 most important papers referenced in 2003, resulting in 776 paradigms. The most dominant relationships between paradigms were also calculated and are shown as lines between paradigms. The map of scientific paradigms constitutes a reference system that can be used for multiple purposes. Countries, industries, companies, and individual researchers can all locate themselves within the map, either as a single point, or as a specific collection of paradigms. Science education and discovery can also be enhanced by linking to the map stories and facts that highlight content and relationships between scientific paradigms. 19

20. Katy Börner, Network Workbench: A CI-Marketplace for Network Scientists

22. 22