http://www.mn.uio.no/ifi/english/research/news-and-events/events/conferences-and-seminars/iiios2014/

The  previous III workshop at the University of Edinburgh (9-11 October 2012)

http://www.stis.ed.ac.uk/issti/events/events/innovation_in_information_infrastructures

had provided the basis for a recently published special edition of the Journal for the Association of Information Systems  edited by Eric Monteiro, Neil Pollock and Robin Williams.

http://aisel.aisnet.org/jais/vol15/iss4/4/

With this collection of papers, infrastructure studies had  “come of age”, Robin suggested. However more systematic and comparative studies are needed to explicate the Uneven Contours of Information Infrastructure Innovation. We need to understand better the opportunities for, and barriers to generativity and generification – whereby local innovations may be encouraged and come to be widely adopted, incorporated in generic solutions.

I am thinking about my ten minute introduction for next week’s Producing Data event.

I want to talk about data visualisation as a profession and its position in the data supply chain. I am reminiscent as I write of Micheal Pryke’s very interesting paper on the “money eye” when he says ““Numbers are not everything”. Interestingly,  Pryke’s is one of the few papers where fieldworker ventures into the realm of computational architecture groups that are responsible of shaping the way (analyst and ourselves) perceive markets.

Next tuesday 2nd of September we will have the privilege of hosting one of them. I met Hermann Zchiegner of www.two-n.com thanks to our common friend and colleague Gordon Haywood in 2012. Hermann was Edinburgh to work to a new data visualisation project at Wood MacKenzie and I interviewed him. Here is one excerpt:

Hermann Zchiegner: “Working with data you are working with something that is there, that is factual. Applying a visualization layer on top of data brings a certain bias with it. You know, based on the same dataset, it can create two very different sorts of pictures. This is one of the biggest challenges of data visualization anyway…to have as much as you can an unbiased view, unless is serving the purpose. I want to help me making an argument with these sets of data. That’s a different kind of story. There is this unbiased view: give me the data, let me help you understand the data, let the data speak to you. The role of the dataviz guy is in a certain way very much so a creative process because you are creating something out of the context of the data that in itself becomes something new, that stands for itself. There is this big difference between data visualization and this big thing that is becoming more and more predominant that is infographics. Data visualization relies of data sets where we have data notes in the hundreds of thousands. Infographics usually deals with small datasets and its purpose is always artistic: I drawing you a picture of a fact. Whilst data visualization is open ended because you are just creating a framework for the data to speak but you are not creating an end product. You are really just creating the framework.”

What I really wanted to understand at that time was when and to what extent pictures bias numbers. I really wanted to find an evidence of this performativity. Hermann’s words hinted at that direction.

My research progressed from that into the study of how even the simple figurations – the dot, the line, the list, the two by two matrix make a difference. I read with great enjoyment Micheal Lynch description of the ‘device of the dot’, Tim Ingold book – an entire book! – on the line. And Chris Carter and Mark Kornberger’s analysis of how a list can make a difference, creating competition between previously unrelated entities and magnifying irrelevant difference (such as the difference between ‘first’ and ‘second’).

I worked over the last few years on the idea that even big numbers and complex calculations need to come down to something people can communicate and understand. Something that they can use to take decisions.My own empirical field of research being the IT market – IT business consultancy and analysis – I started doing research in collaboration with Neil Pollock on the (in)famous Magic Quadrant.

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