Live Blogging Media ‘08: Richard MacManus

Finally, a chance to meet the big guy… :-) His full presentation will be available on R/WW tomorrow; get the scoop here! Double :-) :-)

Major trend that web sites are becoming web services.

Data becoming available through APIs, RSS, etc.; pages are no longer the center of the Web; data and services are.

Coming era of the web is about intelligence.

Semantic web: machines talking to machines, making the Web more ‘intelligent’. Tim Berners-Lee: computers ‘analyzing all the data on the Web, the content, links and transactions between people and computers.’

  • Bottom up: annotate, metadata, RDF!
  • Top down: simple

Semantic app: not necessarily W3C Semantic Web; it’s an app that determines the meaning of text and other data, and then creates connections for users. Data portability and connectibility are keys (ref: Nova SPivack).

Example: Calais. Reuters launched Open Calais last month, does a semantic markup on unstructured html docs, recognizing people, places, companies and events.

More semantic apps: Twine, Freeset, Powerset, Talis, TrueKnowledge, AdaptiveBlue, etc.

Open Data: data-driven web, APIs, portable data, making data available on the Web via APEs, web services, open data standards

“Data silos and walled gardens are a huge loss of opportunity and more people are figuring that out every day.” -Marshall Kirkpatrick, R/WW, January 2008.

Open data: products & standards

Products: Google Android mobile OS, data remix products (Dapper, Yahoo Pipes), maships, lifestreaming apps

Standards: portability, OpenIS, OpenSocial, APML

Mobile web is a key trend: portable, location-aware, integrated with physical world, always on, always carried, built-in payment model, mobile phone is a creative tool at point of creative impulse

5 essential mobile web apps: Gmail Java app for mobile phone; Google Maps for Mobile; Opera Mini; Fring (VoIP, IM); Shozu (send media to Web)

Twitter

Recommendation engines: another key trend they’re following. Personalization is the driving force. 4 approaches: personalized recommendation, social recommendation, item recommendation, or a combination of those three.

Examples: Amazon, Netflix, Pandora, StumbleUpon, del.icio.us.

MyStrands invested $55 million so far, aims to lead the social recommendation industry. Right now it’s a musical discovery and social networking site that covers the PC, mobile and physical worlds. Mission: to help people discover new things. Working on open data formats for describing user taste data; may also use APML?

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