2013 keynote com.geo_reed v2

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Copyright © 2013 Open Geospatial Consortium

Big Data, Sensors Everywhere, and OGC Standards

Carl Reed, PhD

July 22, 2013

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The Open Geospatial Consortium

Not-for-profit, international voluntary consensus standards organization; leading development of geospatial standards

• Founded in 1994.

• 485+ members and growing

• 38 standards

• Thousands of implementations

• Broad user community implementation worldwide

• Millions of users

Commercial41%

Government18%

NGO9%

Research7%

University24%

© 2012, Open Geospatial Consortium

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OGC at a Glance

Not-for-profit, international voluntary consensus standards organization; leading development of geospatial standards

• Founded in 1994.

• 485+ members and growing

• 38 standards

• Thousands of implementations

• Broad user community implementation worldwide

• Millions of users

© 2012, Open Geospatial Consortium

Africa; 4 Asia Pacific; 59

Europe 203

Middle East 7

North America 163

South America 2

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Thought

• And this process of digitizing the world's physical objects may prove the defining element of the age of data. "All the objects in the world are going to become alive and Internet-connected in a way that they weren't before."

• So what's next? . . . the "age of data ubiquity," one in which a new generation of nimble, data-centric apps exploit massive data sets generated by both enterprises and consumers.

– [Hoskins, CTO Pervasive Software, April 2013]. • http://

www.informationweek.com/big-data/news/big-data-analytics/the-age-of-data-ubiquity-sensors-spread/240151991?cid=nl_IW_cio_2013-04-01_html&elq=503df1e8cada4443aba3d7abe37e6f0a


http://www.informationweek.com/big-data/news/big-data-analytics/the-age-of-data-ubiquity-sensors-spread/240151991?cid=nl_IW_cio_2013-04-01_html&elq=503df1e8cada4443aba3d7abe37e6f0a



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How does this relate to the future of geo-technology and location services?

The rise of mobile applications is a good example of this trend. They are very thin

skins representing some data asset behind the scenes.


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Convergence

Network accessible sensors, cloud computing, big data, modeling, augmented reality, business

intelligence, decision support. Sensor data may pose the greatest challenge


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Premise

We live and operate in a space-time continuum!


NASA

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Premise

Everything we do, every event happens somewhere, sometime!


Health

Education & Research Sustainable Development

EnergyConsumer Services, Real Time Information

Geosciences

E -Government

Infrastructure -Transportation

Aviation

Tourism

Emergency Services

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Premise

• Geography and location have significant impacts on our lives


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Fact

• Geography Seen as a Barrier to Climbing Class Ladder

• Analyzed massive amounts of location based income and tax data. Millions of records as well as census data

• Many geographic factors, such as income diversity within a community versus separation into distinct income communities

• New York Times, July 22, 2013


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Premise

Every decision we make has a location (geographic) element


Where to live? eat?get gas? buy shoes? to build? to hike? Is closest drinking water?Is a hospital? Is last place I fished

What is:Fastest way to school?Safest way through swamp?Rainfall pattern?Stream flow for rafting?Best patrol allocation?Floor plan for mall?

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Fact

We need geographic context and location information in most (all) decisions we make.

AKA Geospatial Intelligence


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Fact

Deployment of location enabled sensors and the Internet of Things is rapidly evolving – and creating a data centric requirement


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Major industrials have been preparing for IoT

• Internet of things to give $10-15 trillion boost to global economy:

General Electric

© 2013 Open Geospatial Consortium

• “In 2008, the number of devices connected to the Internet exceeded the number of people on Earth. By 2020, there will be 50 billion devices connected” - CISCO

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"Redefining the language of geospatial industry"Ola Rollen, President and CEO, Hexagon AB.

http://blogs.cisco.com/news/the-internet-of-things-infographic/

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Big Data = 4Vs[M. Stonebraker and IBM]

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Volume

http://www.information-management.com/issues/21_5/big-data-is-scaling-bi-and-analytics-10021093-1.html

Twitter 90 Million tweets / day8 terabytes / day

640 terabytes of operational data on just one Atlantic crossing

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Velocity

3 GB per second LOFAR: distributed sensor array farms for radio astronomy

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Veracity

How was this calculated ?

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Variety – Benefit Areas

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Variety – Systems

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Variety - Sensors

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Variety - Models

Short Term Long Term

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What’s in common?


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Location

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Power of Location

• “Location targeting is holy grail for marketers”– Sir Martin Sorrell, WPP CEO, MWC 2011

• By measuring the entropy of each individual’s trajectory, we find a 93% potential predictability in user mobility – Limits of Predictability in Human Mobility, Science 2010

• 1st law of geography: "Everything is related to everything else, but near things are more related than distant things.” – Waldo Tobler

© 2013 Open Geospatial Consortium 25

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Geospatial Integration

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How ?

http://geoplatform.ideascale.com

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Big Data, the Internet of Things and OGC Standard


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GSC MSTF Conference at Georgia Tech Research Institute – Atlanta, GA , USA – May 7, 2013

Region-Centric Geospatial Information

Feature-Centric Geospatial Information

Human-Centric Geospatial Information

Device-Centric Geospatial Information

1980s 1990s 2000s 2010s

Steve Liang (PhD)

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Steve Liang (PhD)

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Steve Liang (PhD)

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Indoor Space





Steve Liang (PhD)

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Indoor Space

IoTSpace

Steve Liang (PhD)

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OGC Sensor Web Enablement Standards enable the World-wide Sensor Web Vision

• Standard Information Models and Schema– Observations and Measurements (O&M) – Core models and

schema for observations– Sensor Model Language (SensorML) for In-situ and Remote

Sensors - Core models and schema for observation processes: support for sensor components, georegistration, response models, post measurement processing

Standard Web Service Interfaces– Sensor Observation Service - Access Observations for a sensor

or sensor constellation, and optionally, the associated sensor and platform data

– Sensor Planning Service – Request collection feasibility and task sensor system for desired observations

– Sensor Registries – Discover sensors and sensor observations

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Soil Moisture

Flow meter

Meteorological sensors

Rain Gauge

Load cell

Geophone

Water Level Meter

Sensors in Debris Flow Monitoring Station

CCD Camera

Wire Sensor

Spotlight


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OGC SWE-IoT Status

•SWE-IoT SWG uses a lightweight RESTful web interface to access sensor observations and to task acuators

•Current design supports JSON representations of SWE formats.

•Plan to release the draft for public review mid-2013

•Plan to submit the specification to TC for voting in 2013 Q4• http://www.opengeospatial.org/projects/groups/sweiotswg

http://www.opengeospatial.org/projects/groups/sweiotswg

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Crowd Sourcing, Social Media, Big Data and OGC Standards in Action


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Social Networking User Generated Information / Crowdsourcing

• Ushahidi• InRelief• OpenStreetMap• Sahana• CrisisCommons

Source: http://www.sahanafoundation.org

Source: www.inrelief.org

Source: http://www.ushahidi.com/

Source: http://www.openstreetmap.org/

Source: Erik (HASH) Hersman. Flickr

http://www.sahanafoundation.org/

http://www.inrelief.org/

http://www.ushahidi.com/

http://www.openstreetmap.org/

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COBWEB

• Crowdsourced environmental datato aid decision making

• Introduce quality measures and reduce uncertainty

• Fusion of crowdsourced data with reference data…

• Security

• Spatial Data Infrastructure - like initiatives– National SDI’s in UK, Greece and Germany– INSPIRE– GEOSS

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Take away:

• Crowdsourcing– Quality measures and reduce uncertainty– Fusion of crowdsourced data with reference data– Sensor Web / IoT / WoT– Security– Use of Open Standards– SDI, INSPIRE & GEOSS– Economically sustainable– Society's ability to cope with change

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Economist, April 2013

CITI-SENSE Project

Goal: Development of sensor-based Citizens‘ Observatory Community for improving quality of life in cities

Community-based environmental monitoring and information

systems using innovative and novel earth observation applications

27 Participating Organizations from 14 countries

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CITI-SENSE Objective

To develop ”Citizen’s Observatories” to empower citizens to:• Contribute to and participate in environmental governance• Support and influence community and policy priorities and

associated decision making• Contribute to Global Earth Observation System of Systems

(GEOSS)• Improve decision making

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CITI-SENSE Architecture

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Initial CITI-SENSE platform test

CivicFlowcrowdsourceWeb and App(U-Hopper)

SensApp (SINTEF)

SenML SenML

Loader(Snowflake)

Publisher(Snowflake)

Sensor packages(Airbase,GeoTech)

Sensing&ControlVisualisation widgets

Sensor API

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Some slides from Wouter LosUniversity of Amsterdam

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ESFRI Environmental Research Infrastructures

• Tropospheric research aircraft

COPAL

• Upgrade of incoherent SCATter facility

EISCAT-3D

• Multidisciplinary seafloor observatory

EMSO

• Plate observing system

EPOS

• Global ocean observing infrastructure

EURO-ARGO

• Aircraft for global observing system

IAGOS

• Integrated carbon observation system

ICOS

• Biodiversity and ecosystem research infra

LIFEWATCH

• Svalbard arctic Earth observing system

SIOS

23/10/2012

W. Losi - ENVRI @ EUDAT46

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29/03/12

Pasquale Pagano - ENVRI @ EGI CF 201248

Radar interference dataGas (CO2 etc) fluxes

∂ (concentration)

Areal andsatelliteobservation

Species data, distributions, abundance, biomass, etc.

Observations, sensor data,collection data, DNA, etc

Marinesensors

Currents, salinity,deposition, etc

Platetectonics

Seismic data,satellite data,sensors, etc

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Geospatial Data Services

Geospatial Repositories

Data Discovery

Data Access Data Process

OGCOpenSearch

Linked Open DataCatalogue Services

OGCWCS

THREDDS

OGCWPS

WPS 52N

P1 P2 P..

WPS Hadoop

Hadoop Cluster

HD

FS

Data Pub. /Vis.

OGCWMS, WFS

GeoServer

gC

ub

e D

ata

stag

ing

by courtesy of P. Pagano

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But

•Provenance•Data Quality•Privacy


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Provenance

• "to come from", refers to the chronology of the ownership, custody or location of a historical object. A type of metadata.


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Data Quality

• Are (the data) fit for their intended uses in operations, decision making and planning" (

J. M. Juran). Metadata, provenance, and uncertainty measures important!


http://en.wikipedia.org/wiki/Joseph_M._Juran

http://en.wikipedia.org/wiki/Joseph_M._Juran

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Privacy

• In the context of the location data collected by so many mobile apps these days, anonymization generally refers to the decoupling of the location data from identifiers such as the user’s name or phone number.

• Except, according to research published in Scientific Reports on Monday, people’s day-to-day movement is usually so predictable that even anonymized location data can be linked to individuals with relative ease if correlated with a piece of outside information. Why? Because our movement patterns give us away.

» David Meyer Mar. 25, 2013 (http://gigaom.com/2013/03/25/why-the-collision-of-big-data-and-privacy-will-require-a-new-realpolitik/)


http://www.nature.com/srep/2013/130325/srep01376/full/srep01376.html



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Privacy

• You can be constantly tracked through your mobile device, even when it is switched off. What’s more, those sensors you’re pairing with your device make it ridiculously easy to identify you.

• simply by looking at the data (from the Fitbit) what they can find out is with pretty good accuracy what your gender is, whether you’re tall or you’re short, whether you’re heavy or light, but what’s really most intriguing is that you can be 100 percent guaranteed to be identified by simply your gait – how you walk.

» CIA CTO Ira “Gus” Hunt (2013)


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And a final thought!


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Questions & Comments

Carl [email protected]

Open Geospatial Consortiumwww.opengeospatial.org

Copyright © 2012, Open Geospatial Consortium,

http://vast.uah.edu/SensorML

http://mail.opengeospatial.org/mailman/listinfo/sensorml

2013 keynote com.geo_reed v2

Technology

Transcript of 2013 keynote com.geo_reed v2