I recently attended a workshop with Rescue Global (RG) and this blog post captures some of the discussion and points that are interesting and useful to digital humanitarians like myself. The better we understand how disaster response works (or doesn’t work) the better we can build our tools and get them used in anger.
One of the projects I have been involved with recently was a collaboration with the Agents, Interaction, and Complexity group at University of Southampton. The same group who we are also involved with in the Orchid project. This particular project was on Measuring and Predicting Departures from Routine in Human Mobility, building on the PhD work by James McInerney (now at Princeton) and his paper Breaking the Habit.
It is well known that humans generally follow very regular and predicable mobility patterns, both spatially and temporally. Lots of work has looked at exploiting and predicting those patterns but much less so on looking specifically at departures from those regular patterns. What can we learn from those departures from routine? How predictable are they?
Its 23:06 as I type this on the train on the way back from the second UK DataDive. I attended the first one in October last year after hearing about DataKind on rce-cast. In a nutshell DataKind are a non-profit who work together with charities, NGO’s and related organizations to help them collect, manage, and analyze data so they can be more effective. So its like RHoK but focused on data analysis and with a stronger sustainability angle.
I have good memories from the last one and the turnout and organization was very similar this time around. Like last time I could only make it for the Saturday and my employer was kind enough to cover travel costs. Charities selected to participate were:
Since about half a year my podcast subscriptions includes RCE-Cast, an interesting show run by very knowledgable hosts about HPC related topics. One of their more recent episodes was on the Datadive project by Datakind.
From the website:
DataKind brings together leading data scientists with high impact social organizations through a comprehensive, collaborative approach that leads to shared insights, greater understanding, and positive action through data in the service of humanity.
I liked the idea and, while I have plenty of scuba diving experience, data diving was not something I was very familiar with. The problems I have worked on so far have pretty much always been big CPU vs big data. Thus I followed their Twitter feed and signed up to the London event (first in the UK/Europe?) when I heard about it.