This document discusses how open source tools can be used to build location intelligence applications and turn big data into actionable information. It provides an overview of commercial vs open source GIS software, describes how to architect applications using open standards like PostGIS, GeoServer and OpenLayers, and how ontologies and metadata can enhance semantic interoperability and spatial reasoning. Upcoming products from TerraFrame that will integrate these open source tools are also highlighted.

1. Turning Big Data into Change You Can See
GIS, Decision Support, Monitoring and Evaluation
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2. Building GIS, Decision Support, and
Location Intelligence Applications Using
Open Source Tools
Turning Data into Actionable Information
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3. Where the Industry was Yesterday
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4. Where the Industry is Today
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5. Where the Industry is Headed
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6. Where the Industry is Headed
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7. How to build Location Intelligence Applications
Open source now allows us to build industry
specific geospatial applications with:
• Enhanced spatial analytics
• Intelligently aggregate and analyze data from
multiple sources – NO DATA SILOS!
Improve information exchange!
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8. Commercial vs. Open Source GIS Software
Commercial GIS Software
•
•
•
•
Is powerful, mature, but, generic (one size fits all)
Requires a GIS professional to use
Is difficult to build industry specific applications
Is very expensive
Commercial vendors cannot meet the wide
demand for industry specific GIS applications
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9. Commercial vs. Open Source GIS Software
Open Source Tools
• Have traditionally been software developer toolkits and
not standalone applications
• Require software developers to heavily customize
• Are more modular for building industry specific
applications
Open source software enables us to build industry
specific applications for less cost than commercial
tools and without any reoccurring licensing fees
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10. Open Source Tool Landscape
• PostGIS – Geospatial database
• GeoServer – Mapping server
• OpenLayers – Web mapping front end
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11. The Case for Open Source
• Open standards historically:
– Lead to breakthroughs in information
exchange
– Encourage technological innovation
– Enrich the masses
• Closed standards historically:
– Are understood by an educated elite
– Hinder information exchange
– Enrich an elite class
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12. Critical Components to Interoperability
• Compatible
– Data Format
– Data Structure
– Content Semantics
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13. Phaistos Disc – 1,700 BC
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14. Comparing Movable Type Technologies
Compatible
Data Format
Data
Structure/Langu
age
Semantics
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Phaistos Chinese Gutenberg
Yes
Yes
Yes
No
Not
Quite
Yes
No
No
No
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15. GIS Tools
Compatible
Data Format
Data
Structure/Langu
age
Semantics
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Commercial
Tools
Open Source
Yes
Yes
No
No
No
No
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16. Introduction to Ontologies
• Formally represents knowledge as a set of concepts
within a domain
• Used in artificial intelligence
• Allows software to make human-like inferences from
data
• Ideal for semantic conflict resolution
• Can enhance spatial reasoning
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17. Ontologies
Subject
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Predicate
Object
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18. Ontologies
Nathan
Is a
Person
Is a
Living
Being
Person Record
Name
Nathan
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Coordinates
POINT <X,Y>
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19. Ontologies
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20. Mapping Attributes with the Ontology
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21. Mapping Values with the Ontology
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22. Ontologies
• Describes a domain (e.g.
medical)
• Stores relationships – e.g.
“is-a”, “has-a”
• Provides knowledge
representation about the
domain
• Captures human knowledge
into machine
representation, enables
automated reasoning
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23. Ontologies
Compatible
Data Format
Data
Structure
Semantics
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Commercial Open Source
Tools
Ontologies
Yes
Yes
No
No
No
Yes
No
No
Yes
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24. Architecting a Location Intelligence Application
It’s the Metadata, Stupid!
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25. Geo-Universals – Boundary Classifications
City
Is Allowed In
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Country
State
Is Allowed In

26. Geo-Ontologies
Geoentity
Name
Coordinates
USA
MULTI POLYGON<….>
USA
Is Located In
Colorado POLYGON <….>
Colorado
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27. Geo-Universals
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GeoEntities
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29. TerraFrame 2013©
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30. Geo-Ontologies
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31. Geo-Ontology
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32. Enhance spatial reasoning by representing locations as an
object node graph
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33. Creating Multi-Thematic Maps with Open Source Tools
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34. Traditional Architecture
Application/Data
Source
• Custom
Application
• Web Service
• MS Access, SQL
Server, PostGIS
Data Conversion
• Shapefile
• Excel
• CSV
• KML, GeoJSON,
etc.
GIS Stack
• ESRI software
suite
• GeoServer
• Map Server
• Quantum GIS

35. Integrated Architecture
Application Stack
GIS Stack
Client
OpenLayers
Server
GeoServer
PostGIS

36. The GIS Stack
(OpenLayers + GeoServer + PostGIS)
Render
Client/Browser
OpenLayers
JavaScript
HTTP
Example: A WMS request
for a layer defined in
PostGIS
Image
GeoServer
SQL
Result Set
PostGIS

37. The Map Structure
Layer 1
Map
Layer 2
Layer N

38. A Standard Layer
Geometry
Data
Layer
Attribute*
Style

39. A Thematic Layer
Data
Layer
Style
Thematic
Attribute
Style

40. Modeling the Style
Generate the style from an intermediary object
Style
• Polygon Fill
• Polygon Width
• Polygon Stroke
• Polygon Opacity
• Point Size
• Point Stroke
• Point Opacity
• Label Size
• Label Font
• Label Opacity
• Layer Opacity
• Text Placement
SLD
KML
Carto

41. Automated Map Cycle
Initial Map Request
OpenLayers places
the image in the
DOM
GeoServer renders
an image (WMS)
Generate the SQL
and SLD
*transactional
Invoke OpenLayers
and request the
layer
Create a new layer
in GeoServer
Serialize the layer
into JSON
Convert the layer
JSON into
JavaScript

42. Runway SDKtm
• Open source enterprise data management platform
– Dynamic type creation
– Role based access control
– Support for mobile
• Integrated ontology engine
Available now on GitHub under LGPL
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43. Runway GIStm
• Manages:
– PostGIS – Geospatial database
– GeoServer – Mapping server
– OpenLayers – Web mapping front end
• Integrated GIS and location intelligence
Available soon on GitHub under LGPL
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44. Runway GeoDashboardtm
Available in early 2014 under LGPL
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45. Existing Closed Platforms
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