Connecting 131014

Some days it really pays to scroll down a page.

This morning I was scanning through my daily Conversation alert and saw news of Rob Brooks’ latest post.

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Rob started his post thus:

Hasn’t Malcolm Gladwell had a busy fortnight? His latest book, David and Goliath: Underdogs, Misfits and the Art of Battling Giants, shipped on the first of October. And the deluge of reviews washed out a flood of anti-Gladwell bile. He’s an unusually polarising author, Gladwell. And it looks like some of the criticism has stung.

Thereafter he synthesised a number of contributions to the Malcolm Gladwell discussions.

I really enjoyed the way he did this.

I was delighted that he introduced me to Andrew Gelman and his thoughts on over-smoothing. I should have anticipated that the lead contributor to the Statistical Modeling, Causal Inference, and Social Science blog would have a very distinctive take on smoothing and over-smoothing.

I spent much of the morning and two cups of coffee reading through and thinking about some of Andrew’s other posts. How did I miss out on his writing for so long?

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His short post about visualisation introduced me to Dean Eckles, Alex Dow, Lada Adamic, and Adrien Friggeri. A post written in September shared how to set up just-in-time teaching assignments. I liked the way Andrew introduced Vince and his approach to setting up on-line just-in-time assignments.

Whilst contemplating the diversity of Andrew’s interests, another morning alert through Paper.li brought me to Jen Jack Gieseking. By this stage I was primed to read about data visualisation. Jen Jack helped me think about my aspiring interest  in visualisation with her post Opaque is Being Polite: On Algorithms, Violence, & Awesomeness in Data Visualization.

The introductory paragraph in her post is:

Data visualizations are fantastic stuff. Social network analysis, graphic analysis, video, spatial analysis, images, and all other types of #dataviz increasingly capture the imagination and inspire as a way to represent the oft mentioned big data. The failure of many of these new software and analyses in the hand of new, excited scholars and hackers and other excitable folks means that their meaning is often…opaque. Oh, let’s be honest, opaque is being polite. I am sharing these thoughts because while many of you are concerned with the data in big data, I want to turn your attention to the algorithms within and how they mask meanings in many ways.

Jen jack introduced me to Kate Crawford. I would like to join the conversation at the table about algorithms. Andrew and Jen Jack (“data is swell but the algorithms are next and very much up for grabs. However will you join in the conversation to shape them? I look forward to seeing you at the table”) have given me a great lead to do so.

As well as being very late on meeting Andrew, Jen jack and their friends, I appear to be two millennia behind Cicero. I like Tom Standage‘s proposal that “social media does not merely connect us to each other today—it also links us to the past”. Reading about Cicero’s web as one of many historical antecedents of today’s social media reminded me of the remarkable Republic of Letters.

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My morning’s reading concluded with George Couros‘s observation:

Being connected does not make you a great teacher, but in the long run, it can sure help.  If you truly believe that “the smartest person in the room, is the room,” doesn’t it make a difference on how big your room is?

And with Sue Waters’ discussion of Digital Curation: Putting the Pieces Together.

We are living in an era of content abundance. It’s now about finding and putting content into a context, in a meaningful and organised way, around specific topics.

I am awe struck by the sharing that goes on daily. After a day like today, I am hopeful that my big room has a large table to join the conversations Andrew, Jen Jack, George and Sue are having.

Photo Credits

Table, Hampstead Heath ( Nico Hogg, CC BY-NC 2.0)

Dinner conversation (-Ant, CC BY-NC-ND 2.0)

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