Novel Team Science Indicators Used for Strategic Development
of a Scientific Network.
Unni S. Jensen,* Jodi Basner,* Karen Jo,** Nicole M. Moore,** Laurel Haak,* Joshua D. Schnell,*
Jerry S.H. Lee*** and Larry A. Nagahara**
*
unni.jensen@thomsonreuters.com; jodi.basner@thomsonreuters.com; laurel.haak@thomsonreuters.com;
joshua.schnell@thomsonreuters.com
Thomson Reuters Research Analytics Services, Rockville Maryland, 20850 (USA)
**
joky@mail.nih.gov; nicole.moore@nih.gov; larry.nagahara@nih.gov
Office of Physical Sciences – Oncology, Center for Strategic Scientific Initiatives, Office of the Director, National
Cancer Institute, Bethesda Maryland, 20892 (USA)
***
leejerry@mail.nih.gov
Office of the Director, Center for Strategic Scientific Initiatives, Office of the Director, National Cancer Institute,
Bethesda Maryland, 20892 (USA)
Study Purpose
Team science formation and field convergence
indicators are important decision-making tools with
application to a wide range of scientific areas. In this
study we developed and tested team science and field
convergence indicators and explored techniques for
the collection of reliable data to support real-time
evidence based evaluation and decision-making. We
examined the utility of data from grant progress
reports and research publications using the National
Cancer Institute’s (NCI) Physical-Sciences Oncology
Center (PS-OC) program as a case study.
Background
The PS-OC program aims to incorporate physical
sciences approaches and principles with cancer
biology and oncology through the development of
trans-disciplinary research teams and by providing an
infrastructure that facilitates novel research to explore
new and innovative, perhaps unorthodox, approaches
to better understand and ultimately control cancer.
Through cooperative agreements, the PS-OC program
supports a network of twelve centers, bringing
together over 150 investigators from the fields of
physics, mathematics, chemistry, engineering, cancer
biology and clinical oncology. The cooperative
agreement mechanism encourages active coordination
by NCI program officers trained in physical sciences
or oncology and the development of new network
activities and working groups to support the PS-OC
program. Each center has a principle investigator who
is a physical scientist (i.e. physicist, chemist,
mathematician, computation scientist, or engineer)
and a senior investigator who is a cancer biologist or
clinician, and consists of three to five interactive
projects and a minimum of one collaborative core,
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resulting in an average of 10-12 investigators per center.
Members of these trans-disciplinary research teams
engage in a collaborative process to create a shared
conceptual framework that integrates and extends
beyond their individual fields. The goals of the PS-OC
program include (1) successful establishment of
infrastructure to enable these trans-disciplinary teams to
address questions and challenges in cancer research, (2)
training a new generation of trans-disciplinary scientists
that are amenable to incorporating physical sciences
approaches and principles in cancer research, and (3)
development of new physical sciences based
hypotheses/theories/models in cancer research. We
explored custom analytical approaches to test new
indicators targeting each of these goals.
Methods
Data Sources
Research progress and collaborative activities of the
PS-OCs are monitored on an on-going basis through
comprehensive semi-annual progress reports filed by
each center. To assess publication activity we used
two sources: Medline searches for pre-grant activity
(2004-2008) and PS-OC publications reported in
progress reports (2009-current).
Publication Collaborations
To evaluate and visualize changes in trans-disciplinary
collaborations, publication based circular social
networks were generated in Gephi (Bastian, 2009).
Investigator discipline was self-identified. To establish
a baseline of network collaborations, publications for
all PS-OC investigators were queried for five years
prior to the grant. It was hypothesized that monitoring
an increase in these authorship collaborations over time
could provide a measure of collaborative activity due
to the PS-OC program.
Research Project and Reported Collaborations
Thirteen social networks as reported in the progress
reports were generated in Gephi to evaluate and
visualize intra-center collaborations for each of the 12
PS-OCs as well as inter-center collaborations.
Networks were displayed in an edge-weighted force
directed layout with nodes and edges representing
collaborating investigators.
Findings
Publication Collaborations
The number of authors participating in trans-disciplinary collaborations indicates how changes were
distributed across investigators within each discipline
(Figure 1). An increase from 22 to 37 in the total
quantity of trans-disciplinary collaborations from 2008
to 2010 suggests a positive impact of the PS-OC
program on the formation of trans-disciplinary teams.
Figure 1. Publication based social networks for the
years 2006 (left), 2008 (middle) and 2010 (right).
White and black nodes indicate individual scientists
from the field of Physical Sciences and Oncology,
respectively. Grey edges indicate an intra-disciplinary
collaboration while black edges are trans-disciplinary
collaborations. The node size is uniform and the edge
width represents the number of collaborations.
Research Project and Reported Collaboration
All PS-OCs have reported active interactions between
investigators and between some of their research
projects and cores. Five of the PS-OCs have greater
than half of their potential collaborations initiated
during the first 2 years of the PS-OC program. The
sample PS-OCs graphed in Figure 2a and 2b have a
small number of inter-project interactions while the
center in Figure 2c has a high activity between all
projects. About half of the potential center-center
collaborations are occurring. Centers “C” and “L” in
Figure 2d have the highest inter-center activity with
23 collaborations between them.
Discussion and Conclusions
Using time series network graphs, we were able to
show an increase in trans-disciplinary authorship
collaborations between physical scientists and cancer
biologists/oncologists after grant initiation.
Figure 2. Research project social networks, 20092011. Three intra-center graphs (a-c displaying centers
“A”, “B” and “G”) and one inter-center graph (d) are
shown. Nodes are color-coded by research project
within a center with mottled nodes representing
investigators contributing to more than one project.
In addition, more granular analysis showed some
investigators have published results with only intradisciplinary collaborations or no collaborations within
the PS-OC network. The inter- and intra-center
network graphs provide real-time feedback so during
site-visits, program managers were able to share the
center’s graph, providing investigators with a
visualization of reported research project and
collaboration information. This iterative evaluation
process can identify effective program structures and
difficulties early for both program managers and
funded investigators (center leadership and project/core
leads), and help develop program activities to facilitate
a successful initiative. It is possible to implement team
science and field convergence indicators on an ongoing basis using a combination of extant publiclyavailable data, such as publications, and internal data,
such as self-reports of research progress.
Acknowledgments
This work was supported by contracts from the NIH.
References
Bastian, M., Heymann, S. & Jacomy, M. (2009). Gephi:
An Open Source Software for Exploring and
Manipulating Networks. International AAAI Conference on Weblogs and Social Media.
https://sci2.cns.iu.edu/user/documentation.php
Physical Sciences Oncology Centers (PS-OC)
program: http://physics.cancer.gov
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