Warning! Do not click on the map above unless you have a device that takes steroids and lifts weights, as it links to a MASSIVE map of Boston Harbour. Absolutely beautiful, and there for no reason other than that I collect maps, and found this one, which seems to be the perfect balance of detail vs scale. But it's bad practice to have it here as I should really give visitors the choice of size of images to view.
Above is also a link to my mostly not very current blog. It's a bit messy and often incoherent. But it helps me to sort out some of my thoughts in a kind of public / private space.
At present I'm researching themes, narratives and frames around crime, crime open data, and other sorts of crime data, such as closed crime data (a lot of cybercrime data is kept hidden), crowdsourced data, and crime or policing social machines (that generate data).
A key theme for me is the narrative of risk and fear around cybercrime, and how to use real data to find out how to work out risks. Cybersecurity is an amazing area to look at with regard to data - part myth and part real threat. One of my interests is how we unpick the narratives, understand how to actually conceptualise crime in the digital domain, and from that look at what the so-called "skills gap" in this area might be, how to understand who are the sorts of people who might help, leaving behind outdated psychological concepts and psychometrics, and where to apply the most effort most effectively.
Where crowd-sourcing data comes in, I have looked at the concept of social machines as a sort of useful hand-waving classification exercise that enables some short cuts in the inevitable theorising around people and technologies. Yes, some of what's being said isn't new. Yes, some sociologists have done this all before. Thousands of years before that, some philosophers have too! However, that's a discussion for the pub, perhaps, or for when you're suffering from insomnia!
I'm also looking at how conceptualising these crime social machines (or just web-mediated crime technologies, if you prefer) might change some of our ideas about ethical areas such as the intersection of 'data' with privacy and civil liberties. Also interested in: what liberty actually is - not the children's playground that so many seem to assume - crime statistics, (whose feet does open crime data hold to the fire?) policing, democracy, (again not the happy skipping free-for-all so many seem to assume) mapping, markets and mechanisms of distrust and surveillance. I'm using network science methods to do some of this. It's getting slightly more serious now, as I'm approaching the end of my PhD and need to filter out about 90 per cent of the above.
I've also been lucky enough to do some work in technical counter-surveillance. This practical work creates a way of keeping me focussed on the most salient aspects of surveillance theory.