Notes from the Science of Team Science Conference at Northwestern University

The event was packed with theories about the motors and challenges of team science and some interesting initiatives and tools. One of the highlights for us was certainly the introduction to UCINET, a social network analysis tool for team science, which might be useful for the further impact analysis of ShareCenter and crowdsourcing tools like our Open Forum. John Skvoretz from the University of South Florida walked us through the basic methods of social network analysis for team science. Using this program we could get better insight into whether these tools help researchers from different disciplines to connect, and whether most users make new connections or connect with people they already know offline which revives the question whether distance is dead. The program can handle a maximum of 32,767 nodes and includes centrality measures, subgroup identification, role analysis, and more. Now, the challenge is to get the data!

Bonnie Spring from Northwestern University presented COALESCE, a CTSA Online Assistance for Leveraging the Science of Collaborative Effort, that will “create, evaluate, and disseminate new, durable, readily accessible on-line learning resources to enhance essential skills needed to perform transdisciplinary, team-based, basic and clinical translational research”. Four learning modules will be developed over the next two years for the “Science of Team Science,” “Team Science Research Process in Basic Science and in Clinical Science”, as well as “Team Science in Behavioral Medicine.” The Team Science module, for example, will introduce the key concepts of team science by showcasing successful national transdisciplinary NIH research programs and interviews with prominent team science experts.

In the spirit of a web portal for collaboration, we learned about a couple of tools that help researchers manage and evaluate collaborations. 1) Gary Olson from UC Irvine talked about a “collaboration success wizard”, a web-based tool to help researchers assess the prospective success of a collaborative project before it starts. The tool is expected to be available July this year. 2) Howard Gadlin, who runs – as he puts it – an emergency room for team science at the NIH Center for Cooperative Resolution, gave a fabulous presentation talking from the other end of the telescope, about the “dark side” of collaboration. He introduced us to a collaborative agreement, a “pre-nuptial agreement” for scientists, to help scientific collaborators commence their project by anticipating, discussing, and resolving possible areas of disagreement. Using the pre-nup, the parties can jointly define a process for constructively handling disputes should they arise in the future. And 3) the National Cancer Center will launch a “team science toolkit” shortly that intends to provide an online hub for team science-related resources and communication.

William Trochim from Cornell University introduced us to concept mapping, a mixed methods participatory approach that combines group processes (brainstorming, sorting, group interpretation) with a sequence of multivariate statistical analyses (multidimensional scaling, hierarchical cluster analysis) – maybe something to explore in the light of our upcoming survey and research projects. See his paper about “Concept Mapping as an Alternative Approach for the Analysis of Open-Ended Survey Responses”.

Katy Boerner  from Indiana University spoke about the “Cyberinfrastructures for Network Science”. She presented a couple of tools, such as 1) the Network Workbench, a large-scale network analysis, modeling and visualization, which purportedly supports network science research across scientific boundaries, and 2) the Scholarly Database (SDB) that focuses on supporting large studies of changes in science over time and communicating findings via knowledge-domain visualizations. The database currently provides access to around 18 million publications, patents, and grants. In the future, Boerner said, she wants to leverage the power of network analysis to understand better what delays and inhibits science. The tools are available at

More resources from the SciTS Conference are available at

Further reading:

Written by: Rachael Sak, Leslie Yuan and Katja Reuter

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