Data: A Cautionary Tale by Daniel Katz

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A Cautionary Tale

The Big Picture Collect Clean Model Store Present

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The Open Data Movement is in Full Swing Governments Institutions Scientists Enthusiasts

http://vimeo.com/2598878

Commercial tools and open source are starting to converge

There will always be assumptions

Bring it down

FreeBase – Entity Graph Info Chimp Twitter Facebook

Data.gov MTA

Arduino Smart Phone Other sensors

Don’t be intimidated by data from disparate sources

Clean up messy data Inconsistent data points Identify patterns Combine data from disparate

sources

Collection of Twitter Responses from API

Value.parseJson().user.screen_name

Depending on the type of data you are collecting, there are appropriate places to

store it

Non-programmers Google Fusion Tables

For programmers Geo Database and programming tools

PostGIS (Postgresql) GeoTools (Java)

Non-programmers Google Docs (Read into processing) Microsoft Excel (internal charting tool) Text based formatting (visualize with

Google Chart API)

For programmers Any relational database

MySql PostgresSql

Graph Database

http://www.infochimps.com/datasets/tweets-during-state-of-the-union-address

http://code.google.com/p/google-refine/

http://dev.twitter.com/doc/get/geo/search

http://flowingdata.com/2009/07/14/how-does-the-average-consumer-spend-his-money/

http://www.bls.gov/cex/ http://www.google.com/

fusiontables/Home