The Data Network
• An ever-expanding collection of information
• Evolutionary & Revolutionary
• Interconnected and relatable
• No such thing as an “Unrelated Dataset”
Evolution of the Network
Data availability has greatly evolved over the years
Oral Tradition Written Word Books &Encyclopedias
Analog FilingSystems
Digital MediaCloud Computing
Evolution of the Network
• With each new generation, access to information becomes easier and faster
• Process of querying data has gone from a laborious task to simply asking a question
• “OK Google?”
• Increase in capacity of data able to be stored and accessed
Moore’s Law
• Theorized by Intel Co-Founder Gordon Moore in 1975
• States that every two years, computing capacity will essentially double
• Data storage follows a similar trend
Example: One 16GB flash drive = ~53,334 text books
Adding to the Network
• How we collect information influences our interactions with that data
• Data collected in the field
• Acquired from peers
• Crowdsourcing
Mobile Data Collection
• Any information gathered outside a static environment
• Can be collected using:
• Mobile Devices (GPS Units, Laptops)
• Applications (Smartphones, tablets)
• Analog Methods (Verbal interaction)
• Increases your interaction with the public
• Landowners, consumers, etc.
• More “hands on” form of information gathering
Crowdsourcing
• Relatively new phenomenon
• Powered by the internet
• Most common form of data we encounter daily
• Often fueled by social media
• News, reviews, traffic, etc…
Crowdsourcing
Positive• Popular because it is free
and easy
• Response is simple, often quick
• Results in social and often ideological interactions
• Brings innovation
• Can help save lives
Negative• Results are hard to validate
• Everyone’s an expert
• Sometimes based on opinion
• Privacy can be compromised
Interacting with the Data Network
• We interact with the Data Network constantly
• Most commonly through our smartphones and tablets
• Search Engines, Maps, Navigation
• Social Media (Facebook, Twitter, etc.)
• Wi-fi hotspots, Web pages
• We create data, just by going on with our lives
Data Tracking
• Information can be gathered by tracking data as well
• Analytics
• The “Wal-Mart” effect
• Usage Statistics
• Usernames
• Browsing History
• Using your history to gear ads and popups based on recent activity
• Spatial Movement
• Trends
Public vs. Private
• Blurry line between public knowledge and privacy infringement
• How do we respect anonymity?
• Example: Google Street View
• What constitutes public data?
• “Big Data” vs. “Big Brother”
What Goes Too Far?
• We have to balance information gathering with privacy concerns
• Who really owns the data?
• Certain datasets, especially those gathered without public knowledge can go too far in the eyes of some
• What is it being used for?
• “Matter of Public/National Security”
• Accountability
• Metadata
• Metadata
• Metadata
• Metadata
Wander Away• The data network is vast and contains virtually every
piece of information imaginable
• Learning to connect and interact with different datasets can greatly improve how we work and live
• Respect privacy; advocate for those who helped collect the data
• Ensure reliability