Your digital image doesn't look like you

The digital image shows us a different image.
Bodies are not anymore those that are reflected by the mirror, but those revealed by the statistics of their actions. The digital image of the body is not a virtual reconstruction of its physical structure but a numerical report of how it is performing. It doesn't matter how it looks as long as the body is sending vital signals of what it is doing, how it is doing and where it is. A virtual body is always "checking-in", updating other bodies or machines with its functional data. The new image is one that shows the relational body, one in constant movement. The quantified, bio-mediated body is an informational interface; it is not an autonomous entity with a defined visual image but rather a shapeless body that exists entirely in co-creation with everything it is connected to.

Image source: new-aesthetic.tumblr.com

Big Data: an introduction in 10 tweets

This week, between April 19-28, 2012, the Big Data Week has been taking place in 3 countries simultaneously, consisting in 50 meetups about Dig Data. A panel session held in London featured the brightest minds in the Big Data industry:

* Doug Cutting, co-founder of the Apache Hadoop project and creator of Nutch and Lucene
* Nick Halstead - Founder/CTO DataSift
* Hilary Mason – Bit.ly Chief Scientist
* Andy Kirk – Visualising Data
* Edd Dumbill – Program Chair Strata Conference – Moderator

I couldn't attend the event, but I followed the Twitter conversation on #BigDataWeek. Here there are 10 tweets to help beginners like me understand what kind of issues are involved in the discussion about Big Data:

1. @IanFOsborne Big Data means never having to sample anymore!

2. @michellegallen Education is fragmented and operates in silos. This works against training data scientists who need to work across disciplines

3. @jamesholwell Right on. Insightful data analytics alone won't get board-level attention, has to tell a story (and look pretty!)

4. @jamesholwell Big data in 5 years time: sentiment analysis applied to the whole of humanity (assuming privacy doesn't get in the way)

5. @rosshitch media scientists are rare and tend to generate objective results but businesses need action points

6. @wacinski "There will be regulatory constraints on how we're able to analyse datasets, such as the information held by Facebook"

7. @DavidRajan open data open innovation datascience and big data - is all converging

8. @nick365 okCupid an example of not such big data but very very interesting relationship discoveries from their blog.okcupid.com

9. @FlyingBinary Apart from the finance applications by the panel mentioned there is #bigdata revolution underway in the HR and Research space

10. @darachennis Data is a collection of facts. Can't IP or (c) that. Why not treat data as a legal person? Would prevent lots of dumb lawsuits