The growing complexity and interdisciplinarity of research and applied science questions requires the developments of standards to exchange data within continuously growing communities as well as across domains. In most domains, geo-spatial data is the fundamental base layer for data science and analysis, as the vast majority have some spatial characteristics or apply to elements in space. Using the available standards, a good level of interoperability can already be realized. Nevertheless, the increasing complexity of research questions, the growing number of available data, and the increasing range of data providers, ranging from citizen scientists to fully automated sensor networks making their data directly available at the Internet, require even richer models that need to be developed to enhance the level of interoperability.

1. ®
Geospatial Data and Key
Characteristics of Geospatial
Data Analysis and Science: The
Way Forward
Luis Bermudez, Ingo Simonis
Open Geospatial Consortium
lbermudez@opengeospatial.org
Sep 13, 2016 Denver, CO
© 2016 Open Geospatial Consortium

2. OGC®
Structure of the Talk
• Problem
• Standards
• Challenges
© 2016 Open Geospatial Consortium

3. OGC®
Where is Katrina Going?
© 2016 Open Geospatial Consortium
Prediction: 1 day before first landing (Aug 24 , 2005)

4. OGC®
Where is Katrina Going?
© 2016 Open Geospatial Consortium
1st landing
Keating
Beach
Hurricane
status
85 mph
Seems it is
going to
Florida
Panhandle

5. OGC®
Where is Katrina Going?
© 2016 Open Geospatial Consortium
Moved to
the
Louisiana
coast
Hit Bay St. Louis, Aug 29, 2005 as Category 3

6. OGC®
Who was involved?
• Computer Scientist
• Web Graphic Designers
• Geospatial Analysts
• Coastal Inundation Scientist
• Atmospheric Scientist
• Emergency Responders
• ...
© 2016 Open Geospatial Consortium

7. OGC®
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
© 2016 Open Geospatial Consortium

8. OGC®
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 agreements
on formats and
interfaces

9. OGC®
Zhao, Peisheng December
31, 2010
IGI Global

10. OGC®
10
Web Map
Service
Web Coverage
Service (netCDF)
Web
Feature
Service (GML)
Sensor
Observation
Service
Catalog
Services for
the Web

11. OGC®
Open Geospatial Consortium
534 volunteer organizations
6905 portal users
More than 60 standards

12. OGC®
© 2016 Open Geospatial Consortium

13. OGC®
© 2016 Open Geospatial Consortium

14. OGC®
Tests and certifications
Currently
851 implementations
203 compliant products

15. OGC®
Trends
• Big Data
• Cloud Computing
• Crowdsourcing
• Internet of Things
• ..
© 2016 Open Geospatial Consortium

16. OGC®
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
© 2016 Open Geospatial Consortium
Source: Earth Science Information Partners (ESIP), July 2016

17. OGC®
Current Challenges
1. Supporting rich queries and processes
2. Enable semantic Interoperability
3. Advance use of standards for big data and cloud
environments to support geospatial analysis and scientific
communities
© 2016 Open Geospatial Consortium

18. OGC®
Supporting Rich Queries
© 2016 Open Geospatial Consortium
Get me dry places in
Australia that have been
always dry on the last
10 years.

19. OGC®
WMS Query
http://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
© 2016 Open Geospatial Consortium

20. OGC®
© 2016 Open Geospatial Consortium
WFS Query
http://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>

21. OGC®
Query - Resource Oriented
© 2016 Open Geospatial Consortium
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/1.1
Host: geos-australia.org
Accept: application/hal+json

22. OGC®
OGC Advancing REST
© 2016 Open Geospatial Consortium
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

23. OGC®
OGC Advancing REST
© 2016 Open Geospatial Consortium

24. OGC®
Semantic Issue
© 2016 Open Geospatial Consortium
5.2 oz of
cinnamon
porridge
+
149.4 gr of sweet
oatmeal
= ?

25. OGC®
Two services via WFS using their own model
© 2016 Open Geospatial Consortium

26. OGC®
Conflation
Target Dataset
Source Dataset
Extract similar features
(geometries and location)
Resolve
attribute
similarity

27. OGC®
TESTBED 10

28. OGC®
Testbed 11 – Semantic Enablement of Social Data
© 2016 Open Geospatial Consortium
Social
Media
APIs
Silos
GeoSPARQL
Linked Data
REST API
Web
Access
Layer
Human-
oriented
Clients
. . .
OGC Interfaces for Social Media
Social Media
Analysis WPS

29. OGC®
Big Geo Data
© 2016 Open Geospatial Consortium
High Velocity
Ingest
Geospatial
Databases
Spatial
Modeling
Observation
Sources
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
NoSQL
databases
Graph
databases
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

30. OGC®
Classification Service
© 2016 Open Geospatial Consortium
OGC Testbed 10 – Cloud Computing

31. OGC®
© 2016 Open Geospatial Consortium

32. OGC®
Location Powers: Big Data
• Tuesday 20th September
• Orlando, Florida
© 2016 Open Geospatial Consortium
#LPBigData
http://www.opengeospatial.org/event/1609tc
http://www.locationpowers.net/

33. OGC®
Take Home Message
© 2016 Open Geospatial Consortium
Agreements (standards)
help solve complex
problems across
communities
Technology is advancing
User can do more queries
Let’s make them simpler
Let’s advance further
semantic interoperability
solutions
Let’s advance Big Data/
Cloud geospatial
analytics architectures
using open standards

34. OGC®
The Open Geospatial Consortium
© 2016 Open Geospatial Consortium
Open Geospatial Consortium
www.opengeospatial.org
OGC Standards - freely available
www.opengeospatial.org/standards
OGC on YouTube
http://www.youtube.com/user/ogcvideo
Luis Bermudez
@berdez
lbermudez@opengeospatial.org