Geospatial Data and Key Characteristics of Geospatial Data Analysis and Science

®

© 2016 Open Geospatial Consortium

Geospatial Data and Key Characteristics of Geospatial Data

Analysis and Science: The Way Forward

Luis Bermudez, Ingo SimonisOpen Geospatial Consortium

[email protected] 13, 2016 Denver, CO

mailto:[email protected]

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Structure of the Talk

• Problem• Standards• Challenges


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Where is Katrina Going?


Prediction: 1 day before first landing (Aug 24 , 2005)

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1st landing Keating Beach

Hurricane status

85 mph

Seems it is going to FloridaPanhandle

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Moved to the Louisiana coast

Hit Bay St. Louis, Aug 29, 2005 as Category 3

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Who was involved?

• Computer Scientist• Web Graphic Designers• Geospatial Analysts• Coastal Inundation Scientist• Atmospheric Scientist• Emergency Responders• ...


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Distributed Coastal Laboratory (2009)

A cyber-enabled virtual organization of scientists, sensor networks, forecast models, and computing resources to advance understanding of coastal phenomena and enable transformational science


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1. NHC produces advisory

2. UF produces

winds

5. LSU and TAMU

archive the data

4. Data is catalogued

at UAH

6. OpenIOOS displays

data

3. RENCI, BIO, VIMS, UF run

coastal models

Coordinated community with

agreed agreementson formats and

interfaces

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Zhao, Peisheng December 31, 2010IGI Global

OGC®10

Web Map Service

Web Coverage Service (netCDF)

WebFeature Service (GML)

Sensor Observation Service

Catalog Services for the Web

OGC Stan

dards

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Open Geospatial Consortium

534 volunteer organizations

6905 portal users

More than 60 standards

OGC®© 2016 Open Geospatial Consortium

OGC Standards


Domain Working Groups

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Tests and certifications

Currently851 implementations203 compliant products

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Trends

• Big Data• Cloud Computing• Crowdsourcing• Internet of Things• ..



Earth Science Data Analytics

• Process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data encompassing a variety of data types to uncover patterns, correlations and other information, to better understand our Earth.

• This encompasses: – Data Preparation – Preparing heterogeneous data so that they can be jointly

analyzed– Data Reduction – Correcting, ordering and simplifying data in support of

analytic objectives– Data Analysis – Applying techniques/methods to derive results

Source: Earth Science Information Partners (ESIP), July 2016

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Current Challenges

1. Supporting rich queries and processes 2. Enable semantic Interoperability3. Advance use of standards for big data and cloud

environments to support geospatial analysis and scientific communities


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Supporting Rich Queries


Get me dry places in Australia that have beenalways dry on the last 10 years.

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WMS Queryhttp://myserver/wms?

VERSION=1.3.0&REQUEST=GetMap&SERVICE=WMS&LAYERS=Dry & STYLES=&CRS=..&BBOX=…&WIDTH=400&HEIGHT=300&FORMAT=image/png&BGCOLOR=0xffffff&TRANSPARENT=TRUE


http://myserver/wms


WFS Queryhttp://myserver/wfs?

SERVICE=WFS&REQUEST=GetFeature&VERSION=1.1.0&

typeName=wet_dry_areas& FILTER= <Filter

xmlns="http://www.opengis.net/ogc"> <PropertyIsLike> <PropertyName>ss_cat</PropertyName> <Literal>Dry</Literal>

</ PropertyIsLike > </Filter>

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Query - Resource Oriented


HTTP/1.1 200 OK Content-Type: application/hal+json

{ "_links": { “self": { "href": "/dry" }, “map”: { "href": ”dry/map" }, “vector”: { "href": ”dry/vector" } }, “area_sq_km”: 1,400,000, “description”: “Dry places in Australia for the last 10 years“ }

GET /dry HTTP/1.1Host: geos-australia.orgAccept: application/hal+json

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OGC Advancing REST


The purpose of the RESTful Service Policy Standard Working Group is to create requirements, recommendations and examples for the creation of OGC standards for RESTful Web Services. The result of this work will be formalized in a Policy Standard for the structure and content of the implementation of geospatial standards embodying a uniform approach to RESTful principles

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OGC Advancing REST


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Semantic Issue


5.2 oz of cinnamon porridge

+149.4 gr of sweet

oatmeal= ?

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Two services via WFS using their own model


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Conflation

Target Dataset

Source Dataset

Extract similar features (geometries and location)

Resolve attribute similarity

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TESTBED 10

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Testbed 11 – Semantic Enablement of Social Data


Social MediaAPIsSilos

GeoSPARQL Linked Data REST API

Web AccessLayer

Human-orientedClients

. . .

OGC Interfaces for Social MediaSocial Media Analysis WPS

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Big Geo Data


High Velocity Ingest

Geospatial Databases

Spatial Modeling

ObservationSources

Users and consuming

apps

GeoAnalytics, Machine Learning

Entity-oriented Spatial-temporal

analytics

Grid-oriented Spatial-temporal

analytics

Feature Fusion

Remote sensed data processing

Machine Learning

Array databases

NoSQLdatabases

Graphdatabases

Built environment

models

Integrated environmental

models

Modeling and simulation

IoT Message Streaming

Social Media Message

Processing

ETL Stream processing using

RDF

Wide Area Motion Imagery

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Classification Service


OGC Testbed 10 – Cloud Computing

OGC®© 2016 Open Geospatial Consortium OGC Testbed 13 (2016-17)

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Location Powers: Big Data

• Tuesday 20th September• Orlando, Florida


#LPBigData

http://www.opengeospatial.org/event/1609tc

http://www.locationpowers.net/





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Take Home Message


Agreements (standards) help solve complex problems across communities

Technology is advancingUser can do more queriesLet’s make them simpler

Let’s advance further semantic interoperability solutions

Let’s advance Big Data/ Cloud geospatial analytics architectures using open standards


The Open Geospatial Consortium

Open Geospatial Consortiumwww.opengeospatial.org

OGC Standards - freely available www.opengeospatial.org/standards

OGC on YouTubehttp://www.youtube.com/user/ogcvideo

Luis Bermudez@berdez

[email protected]

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

http://www.opengeospatial.org/standards

http://www.youtube.com/user/ogcvideo