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« Prediction: Channel Consolidation | Main | Asserting Context: A Prerequisite for Smart, Sensemaking Systems »

July 27, 2009

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Rafael Sidi

Jeff, this is a must read piece for any product manager and architect in the scientific, technical and medical (STM) online information industry. Thanks for sharing the full-text.

Kingsley Idehen

Jeff,

Really nice post!

I explicitly refer to "Data" as units of Observation in one of my demystifying Linked Data presentations [1]. I also refer to "discoverability" and its importance, esp. as the Web becomes a Linked Data mesh, in my post about SDQ (Serendipitious Discovery Quotient) [2].

Links:

1. http://tr.im/uARm - Linked Data Presentation section about Data, Information, and Knowledge
2. http://tr.im/iv9e - About SDQ

Mukesh Mohania

Jeff, This is an excellent article, giving deep insights why organizations need to move to "data find data" paradigm. Thanks for your sharing this.

Dave Piscitello

The privacy implications and mining opportunities here are staggering. What if data find data that should not have been accessible to the "seeking data"? Who's accountable or liable if the correlations the seeking data derive from found data breach a privacy reg?

Intriguing stuff, thanks for the post

Jacques Spilka

Hello Jeff,
One step in this direction might be the use of a Subject State rules engine. The engine listens to all published events and reacts only to those events that are relevant to the subject’s current state. When the event and the subject rules are true then take the appropriate action. As appropriate, alter the subject’s profile data and possibly change the subject’s state, and the cycle begins anew.

I do share Dave Piscitello’s view on the privacy implications of this technology. One can see a future where customer profile databases are traded in back alleys at midnight.

Fascinating article! Thank you for the fine post.

software consultant

I would agree with Dave, great post.

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