into algorithm plug-ins, it is algorithmically possible to modularize visualization and interaction design. Future
work will focus on developing “
visualization layers” supporting selection
and combination of reference systems, projections/distortions, graphic
designs, clustering/grouping, and interactivity.
Streaming data. The number of
data sets that are generated and must
be understood in real time is increasing; examples are patient-surveillance
data streams and models of epidemics
that predict the numbers of susceptible, infected, and recovered individuals in a population over time. EpiC
tool development funded by the National Institutes of Health contributes
algorithms that read and/or output
streams of data tuples, enabling algorithms to emit their results as they run,
not only on completion. Data-graph visualizations plot these tuple streams
in real time, resizing (shrinking) the
temporal axis over time.
Web services. The OSGi/CIShell-based tools discussed here are standalone desktop applications supporting offline work on possibly sensitive
data, using a GUI familiar to target
users. However, some application domains also benefit from online deployment of macroscopes. While the OSGi
specification provides basic support
for Web services, CIShell must still be
extended to make it easy for domain
scientists to design their own macroscope Web services.
Incentive design. Many domain
experts have trouble trying to use an
evolving set of thousands of possibly
relevant data sets compiled for specific
studies of inconsistent quality and coverage, saved in diverse formats, and
tagged using terminology specific to
the original research domains. In addition, thousands of algorithms that support different functionality and diverse
input and output formats are written
in different languages by students and
experts in a range of scientific domains
and packaged as algorithms or tools
using diverse licenses. More-effective
means are needed to help domain experts find the data sets and algorithms
most relevant for their work, bundle
them into efficient workflows, and relate the results to existing work. Scholarly markets resembling a Web 2.0
version of Craigslist.org can help ease
the sharing, navigation, and utilization
of scholarly data sets and algorithms,
reinforcing reputation mechanisms
by, say, providing ways to cite and acknowledge users who share, highlight
most downloaded and highest-rated
contributions, and offer other means
for making data sets, algorithms, workflows, and tutorials part of a valued
I would like to thank Micah Linnemeier and Russell J. Duhon for stimulating
discussions and extensive comments.
Bruce W. Herr II, George Kampis,
Gregory J. E. Rawlins, Geoffrey Fox,
Shawn Hampton, Carol Goble, Mike
Smoot, Yanbo Han, and anonymous
reviewers provided valuable input
and comments to an earlier draft. I
also thank the members of the Cyberinfrastructure for Network Science
Center ( http://cns.iu.edu), the Network Workbench team (http://nwb.
cns.iu.edu), and Science of Science
project team ( http://sci2.cns.iu.edu)
for their contributions toward this
work. Software development benefits
greatly from the open-source community. Full software credits are distributed with the source, but I especially
acknowledge Jython, JUNG, Prefuse,
GUESS, GnuPlot, and OSGi, as well as
Apache Derby, used in the Sci2 tool.
This research is based on work supported by National Science Foundation grants SBE-0738111, IIS-0513650,
and IIS-0534909 and National Institutes of Health grants R21DA024259
and 5R01MH079068. Any opinions,
findings, and conclusions or recommendations expressed here are those
of the author and do not necessarily
reflect the views of the National Science Foundation.
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Katy Börner ( email@example.com) is the Victor h. yngve
Professor of Information science at the school of library
and Information science, adjunct Professor at the school
of Informatics and Computing, and Founding Director
of the Cyberinfrastructure for network science Center
( http://cns.iu.edu) at Indiana university, bloomington, In.
© 2011 aCm 0001-0782/11/0300 $10.00