Where 2.0 NoSQL Presentation 2008 - GeoIQ
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From Data Chaos to Actionable Intelligence: How the Convergence of the GeoWeb and Semantic Web is Revolutionizing the Way We Process Information Where 2.0 2008 Sean Gorman FortiusOne Inc.
description
Presentation at Where 2.0 2008 where we discuss our rational for building a NoSQL data store after reaching limitations with the spatial SQL solution that were available at the time.
Transcript of Where 2.0 NoSQL Presentation 2008 - GeoIQ
From Data Chaos to Actionable Intelligence: How the Convergence of the GeoWeb and Semantic Web is Revolutionizing the Way We Process Information
Where 2.0 2008Sean Gorman
FortiusOne Inc.
AKA: Trying to GeoHack Without Getting Arrested
Geography of the Web
Paul Torrens
Steve Coast
Martin Dodge
Anthony Townsend
Matt Zook
Big Data Sets
Algorithmic Analysis
Map Logical Results to Physical Realities
NYSE – SIAC Routing Vulnerabilities
Then these guys show up
Then these guys rescue you
Geography on the Web
Small data sets with largely unstructured content
Crowdsourcing large structured data sets with quantitative capabilities
Didn’t we try this last year?
What happens when your database reaches 1,683,185,246 features
Rinse and repeat per query type
or
Build a lightweight object database
OpenLocation
Lots of silos of GeoData how can we begin to interconnect them
Infochimps.org
Can we federate our data
OpenLocation
Linked repositories of data form a graph of content
Structured Dataset “Structured Dataset “X”X”
Third Party URL “Third Party URL “Y”Y”
Node “Y” is connected to Node “X” by the link “User Action”
User adds structured dataset “X” to their 3rd Party URL string “Y”
Structured Dataset “Structured Dataset “X”X”
Third Party URL “Third Party URL “Y”Y” Third Party URL “Third Party URL “Z”Z”
Data Set Degree
X 2
Y 1
Z 1
Creates the Ability to Intelligently Serve Content
Structured Dataset “Structured Dataset “X”X”
Third Party URL “Third Party URL “Y”Y” Third Party URL “Third Party URL “Z”Z”
User searches on a term and gets a result based on tags and full text query then weighted by degree and user ratings:
The system can now recommend data URL “Y” and “Z” as data that may be useful context for dataset “X” even though they may have no tags in common
The graph can be encapsulated in code and communicated to the outside world
1. Bring a new class of content/data to the Web
2. Intelligently mix that content with the rest of the Web
3. Enable the content to answer meaningful questions for users
If you would like to check out the Finder! Beta see us for a card or go here:
http://finder.geocommons.com/
If you would like to talk about federating geodata email me at:
