The Next Phase of Web 2.0: Data – Jamie Taylor #w2e #w2edata

The Next Phase of Web 2.0: Data

Jamie Taylor – Freebase
#w2edata

Co-Author: Programming the Semantic Web
Building flexibly applications with Graph Data

Freebase – Open, socially managed database
12 million nodes and over 350 million links to those nodes
Trying to understand the relationship between different data objects

Native to the Web of Data – Tom Coates

Network Effects
Stone Soup Example – fable where villagers contribute a little to create something bigger to be shared by all
Community is another word for economy

Models of Participation
Flickr, YouTube, Wikipedia – what most people think about but participation is low
Pyramid of Contribution – following Bradley Horowitz
Small group of Creators around 1%, Synthesizers modify the creators content and a majority are consumers of content
Perhaps it is that the creators are contributing content that is built out by the synthesizers into another pyramid

Threaded discussions are difficult to follow as content branches off
Ubuntu Bugs does a good job of combining threads into relevant content
But the difficulty is finding a way to analyze the content

Percolation
Like Twitter and how RT work and move through different circles of friends
You can use math to model
A .6% is where you get the best length of time for a message to exist

Coupling
Investigations – Stuart Kauffman
Learning how complex systems work – NK Boolean Networks
When you think about how users interact with data you need to think about how one change permeates thought the network

Scale
How does value scale in these systems
Metcalf's Law – Like the telelphone growth/adoption creating value
Reed's Law – Group Formation Networks: Take any Social Network and create lots of value and very quickly
Examples: Broadcast = N, Email = N squared, Chatrooms = 2N
In Twitter the # creates a broadcast in a network to people looking for the hashtag which creates a new sub group looking to participate

Controlled Vocabulary
With the hashtag you have to get people to the proper 'channel'
Facebook has a good way to provide good vocabulary through the activities preferences
Freebase you can use leverage the suggest – http://freebase.com/docs/suggest

Semantics Inside
HTML 5 Microdata, Freebase, Facebook Open Graph

Cumulative Advantage
Ex: Clocks The current clock face started with all sorts of different models, but ultimately the current model won out
Is Justin Timberlake a Product of Cumulative Advantage? – http://www.nytimes.com/2007/04/15/magazine/15wwlnidealab.t.html
The foundation behind: Scale Free Networks & Small World Networks
Dan Bricklin: Cornucopia of the Commons 3 Ways to build a database

Stone Soup Review
Multiplying a scare resource via community
Cumulative advantage
Architecture for participation
Community at all scales

Wrap up
Think about data accumulation in interaction design
Design for Network Effects
– Allow the community to work at all scales
– Provide tools for bifurcation management
– Facilitate Percolation (but don't over connect)
-Couple contributions loosely
– Foster Group Forming Networks (2N scaling)
– Guide data convergence through vocabulary
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