Data Science

ACAPS crisis indicators

There are several types of data used by responders in a crisis. Most crisismapping has focused to date on the data generated during and immediately after a crisis: the tweets, messages, reports, alerts and other social media traffic that happens in response to crisis situations and needs. But a country doesn’t suddenly change socially because a crisis happens.  It doesn’t leap, ready-formed, into a new incarnation where the only thing that’s ever happened is the current earthquake, flood, famine etc.  Countries have histories.  Events happen, societies form, agencies and other countries, if needed, help them to develop and become resilient. And all this activity creates data. One of the first things that a response agency does, as it goes into a crisis, is create a profile of that country.  How many people are there?  What’s it society like?  What are its existing needs?  Which crises have happened before (and how…

Data Science

Where do the crisis indicator numbers come from?

I’ve been tracking the provenance of some GIS datasets lately, working on the licenses and attributions that have to be attached to them when they’re released as open data. I’ve also been working on automatically generating development indicator sets for a country – the numbers that help responders understand the state of a country *before* a crisis happens (social problems don’t go away just because an earthquake happens). A lot of crisismapping comes down to persistence, capability and trust. Trust is a biggie: as someone (Gisli Olafssen?) said, a disaster is not the time to be handing out business cards. We need to trust the people we’re working with, the systems we’re using (within sensible limits and the occasional online equivalent of kicking the case in the right place), and we need to (again within sensible limits) trust the data we’re using. Trust in the data that happens during a…