Cyberinfrastructure: Rise of the Machines Data Acquisition, Synthesis, broader Impacts and Public...

8/6/2019 Cyberinfrastructure: Rise of the Machines Data Acquisition, Synthesis, broader Impacts and Public Outreach

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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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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.


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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Support closed loop scientific activities.

Enable interactive and event-driven control

of the observatory assets based on

interactive and real-time observations and

analyses.


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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Working group has

programmed network to adaptively

detect and conduct experiments


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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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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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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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Increase model resolution Reduce forecast error


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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.

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Cyberinfrastructure: Rise of the Machines Data Acquisition, Synthesis, broader Impacts and Public...

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