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Observatory provide a new mode for collecting, but more
importantly living adaptively with data 24:7 365 days a year
Cyberinfrastructure: Rise of the MachinesData Acquisition, Synthesis, broader Impacts and Public Outreach
Schofield: Rutgers University - Coastal Ocean Observation Lab
Today
A) Quick picture of OOI cyberinfrastructure
B) What will it do?
C) Will it work?
D) How will it help outreach?
Today
A) Quick picture of OOI cyberinfrastructure
B) What will it do?
C) Will it work?
D) How will it help outreach?
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A) OOI is one investment for understanding the global carbon issues
B) ARGO is one investment for understanding the global carbon issues
C) Models will help synthesize observation for understanding the global carbon issues if they
effectively parameterized and if we build super ensembles
ARGO combined with satellites the pre-
eminent global ocean sampling arrayOOI in valuable
locations provide
infrastructure
capable of
sampling ocean
intensely to
support processstudies and help
develop model
parameterization
Sargasso Sea
Front
Sargasso Sea
Front
Sargasso Sea
Front
Cold CoreEddy
Cold CoreEddy
Cold CoreEddy
Warm CoreRemnant
Warm CoreRemnant Warm Core
Remnant
Modelsimproved
with in situ
data via data
assimilation
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Observatory Requirements:
Provide one integratedobservatory interface to all users
inside and outside the OOI.
Enable the users to investigate
observations, manage the
observatory and its assets and
collaborate with each other inteams.
Engineering Drivers:
A geographically distributed
system of systems with
observatories at multiple scales
and operational authority. OOI-wide need for data distribution,
storage, processing and
command and control.
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Observatory Requirements:
Enable communities of users towork with the instruments and
observatory assets they need
from across all OOI sites in a
uniform observatory
environment. Support multiple
virtual observatories in parallel.
Engineering Drivers:
Multiple heterogeneous
communities of users accessing
shared observatory assets across
the OOI. Enable access to
observatory assets based on user
authorization level and
observatory policy.
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Observatory Requirements:
Support closed loop scientific activities.
Enable interactive and event-driven control
of the observatory assets based on
interactive and real-time observations and
analyses.
Engineering Drivers:
Workflows accessing real-time
measurements, external data
sources, real-time processing, QA
and event-detection, complex
numerical models leading tocontrol of mobile and stationary
observatory assets.
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NEPTUNE
Canada
NFS OOI
Network
NOAA N-Wave
Network
Global Lambda
Integrated Facility
Engineering Driver:
The topology used by
the OOI program is
easily integrated into
national and
international cyber-networks. This will
facilitate collaboration
for developing the
international ocean
observing network
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What will we get? Given a rapidly changing technology?
~30 years ago
Apple II introduces 4k
of memory
Will it be useful? Or will we be inducted into the patheon of the worlds most useless inventions?
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The science interactions enabled through social network tools
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9
Data Provenance: Enabling a community shift
Dekas et al. 2009. Science
nanoSIMS: Shows the
Microbial consortia fix and
use nitrogen
Young untenured scientist inspired
writes an NSF proposal to miniaturize
His proposal seduces the panel, and
he is funded first submittal
Built
DEPLOYED
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Science Community Workshop 1 10
Adaptive sampling
Many scientists form a distributed team to study earthquake modulation of
seafloor biota. They use the cyber tools to form a social network to design
experiments, explore data, and publish results
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Science Community Workshop 1 11
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Working group has
programmed network to adaptively
detect and conduct experiments
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Science Community Workshop 1 13
Scientist has subscribed
to the vent working group.
The scientist is alerted to
an event occurring.
The
event alerts all scientists
in the working group to
the event. They can
interact and modifyongoing experiments.
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Science Community Workshop 1 14
Scientist logs into
system to assess visuallystatus of the experiment
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For the carbon questions raised today how might this adaptive sampling be useful?
1) Fluxes are episodic
Are the fluxes dominated
by mean (seasonal) or
fluctuating terms
(days/weeks)?
2) How is material
transformed during
its gentle rain (not)
to the deep sea?
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Will this work?
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Observatory (simulated) data
Virtual Ocean
Design, Testing and Deploy
Models
Data Assimilation
Data
Analysis
Science Questions & Drivers
~100 m
~3 km
Sensor &
Platform
Data Synthesis: Nowcast & Data Impact
Experimental concept
May 2009 Virtual test Sept. 2009
Wet test
Nov. 2009
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W
e
at
h
er
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Multiple Satellite passes
of varying resolution
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Model A Model B
Model C Model D
n ensemble of different numerical models run by different laboratori
WE ARE ON THE VERGE OF THESUPER ENSEMBLES
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A fleet of four gliders
October 30 November 20, 2009
4 Deployments
77 in-water days
1608 km flown
Over 23,000
vertical casts
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Science Community Workshop 1 23
Model A Model B Model C Model D
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COMBINING THEFIELD ASSETTS WITH OCEANFORECASTS
FOR PLANNING AND PROSECUTIONEFFORTS
Known constraints (slow 0.5 knot,
Battery, shipping lanes) Uncertain constraints (time-varying
3D currents)
Operate autonomously & re-plandaily
From A to B in the shortest time
Follow a time-varying feature(shelf-slope salinity intrusion)
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PLANNING FOR THE PRESENT
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PLANNING IN THE FUTURE
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Science Community Workshop 1 28
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Increase model resolution Reduce forecast error
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Science Community Workshop 1 3030
ScienceAgents
Science Event Manager
Processes alerts and
Prioritizes response observations
ASPEN
Schedules observations on EO-1
EO-1 Flight Dynamics
Tracks, orbit, overflights,
momentum management
Science
Alerts
Observation
Requests
Updates to
onboard plan
Science
Campaigns
Scientists
Hyperion
on EO-1
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Here glider looked at its own data to make a decision underwater on its own.The glider brains will be key to provide adaptive sampling of ocean features
of high science priority
Make the network smart
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OOI will build the Education and Public Engagement tools that will be open to all
communities.
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Undergraduate Educators
Example: Educators
using real-time observatory data in
an undergraduate research course
Free Choice Content Developers
Example: OOI Project Educator
Janice McDonnell focusing on real-time data use in an after-school 4-H
club program
Selective Crowd Sourcing (APP Builders)
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EPE: Concept Map Builder Case
Study Karen Orcutt and Kjell Gundersen (Univ.Southern Mississippi, USM) reworked the
NSTA map to address Deepwater Horizon
oil spill microbial activity for the pilotResearch-based Online Learning Event
webinar (July 2009)
Over90 people pre-registered for their
follow-on webinar (May 12, 2011)
35
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Why else do we need this? Scientists are dedicated and
committed; however often are, at best, challenged to tell of
their journeyScientist humor hasselective appeal
Their outreach does notplay well with wider
community
Often we are unaware
of how others perceive us.Right now I think I
am this to you
Right now you are seeing thisMy entry to Rutgers
Comedy Night
My entry to NYC
fashion week
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So going forward, we will hopefully have:
1) a range of tools that will enable our
community to work in a digital ocean,
1) link all ocean programs to each other
so that we can leverage the range of
space and time sampling and,
1) if successful, we can change the
number of eyes on the problem.