Common Big Data Challenges in Bio, Geo, Climate, and
Social Sciences
Moderator
Panelists
Event Type
Panel
Applications
Data Analytics
Data management
Scientific Computing
TimeThursday, November 16th10:30am -
12pm
Location201-203
DescriptionSpatiotemporal data, whether captured through remote
sensors, ground and ocean sensors, social media and
handhelds, traffic-related sensors and cameras, medical
imaging, or large scale simulations have always been
“big.” A common thread among all these big collections
of datasets sets is that they are spatial and temporal.
Processing and analyzing these datasets requires
high-performance computing infrastructures. Despite
these commonalities, leading big data communities of
bio, geo, climate and social sciences, are highly
fragmented and work in silos, resulting in solutions
that are difficult to discover, integrate, and
cross-fertilize. This panel aims to bring together the
aforementioned, diverse yet overlapping communities with
substantive big data and compute problems under SC
umbrella to facilitate dialogue to reduce the
impedances.
Panel Questions:
- HPC and Spatial-temporal Computing - two ships passing in the night?
- Does HPC offer a mechanism to facilitate cross-fertilization?
- Impedances to large-scale adoption of Spatial Computation and Analytics?
Panel Questions:
- HPC and Spatial-temporal Computing - two ships passing in the night?
- Does HPC offer a mechanism to facilitate cross-fertilization?
- Impedances to large-scale adoption of Spatial Computation and Analytics?
Links
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Panelists
