Scientific Discovery Within Data Streams - Ambient Intelligence for Scientific Discovery - page 79

changing dimensions as new token influence the status quo. Monitors covering
the walls could hold representations of individual data items or other miscella-
neous statistics. They could also provide expressions of other researchers, con-
nected in from a remote location. We envision the HI-SPACE itself holding the
ThemeRiver visualization, but enhanced to allow users to use hand gestures to
indicate topics of interest. They may use phicons [15], physical objects regis-
tered with the HI-SPACE as placemarkers. These could be placed as stopblocks
on themes that are not considered essential to the current study, or in some
alternative manner so to affect the themes presented. Usability studies will be
required to ascertain the usefulness of an ambient approach to such scientific
discovery, but we believe that by becoming more intrinsically involved with the
data, scientists may be able to uncover unique findings, previously undiscovered.
An artist's rendition of our concept can be seen in Fig. 11.
6 Summary
We have presented our vision for a next generation analytical environment for
scientific discovery within data-streams. By utilizing components from our re-
search portfolio in Information Analytics, Rich Interaction Environments and
Knowledge Engineering, we envision a system that can handle massive data
streams of differing data types, present the most important elements of these
streams visually and allow for advanced interactions within a group context.
Acknowledgements
The authors would like to thank their colleagues across numerous departments
at PNNL that made these individual components possible.
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