Bring developers + scientists together for Climate and Disaster Resilience
Channel: Andrea Ross
Date: 18/03/2015

The original title was too long for YouTube:
"Bring developers+ scientists together to unlock (Big, Open?) Geospatial Data to Build Climate and Disaster Resilience"

by Beth Tellman

Just like access to money and decision-makers, access to data grants power and privilege for disaster response and preparation which small vulnerable communities and the general public lack. Imagine if we could unlock the best high-computer mapping, vulnerability science and big data to allow any city and any internet user around the world do sophisticated hydrological modeling or predict how their community will be affected by climate change in the coming decades.

I will start the session by briefly showing a proof of concept for a web application that draws from data in the cloud (including elevation, satellite imagery, and census data) to dynamically refine a surface of risk inside a coarse resolution flood prediction zone from a weather service. Through funding from the Google Earth Engine research award, we hope to bring model and its analysis to the public and mid to small sized municipalities to improve early warning system, disaster communication, and preparedness. Under the hood, the algorithm uses a series of social and ecological indicators of vulnerability to flooding derived from cloud based data in Earth Engine to in order to predict who is most at risk from extreme weather today and in a climate change affected future. We are building capacity to input climate scenarios including different emissions regulatory futures to predict how vulnerability for every community will change as our weather and landscapes shift.

As scientists, we are often full of ideas to model socio-ecological systems, but lack the developing/coding expertise to fully bring this knowledge of systems and data to fruition in a streamlined algorithm. In addition, academia can be shackled with licences to non-open source software- meaning many scientist are not trained in powerful open source tools that best poised to help us open source our algorithms and share knowledge production with communities and groups that only have access to open source sofware.

This session is proposal (from a PhD science student) to talk about some of these challenges with a community of open source developers.

In this session I have 3 objectives
1. show my cloud based disaster model/data sets for feedback and to solicit potential collaborators
2. find out how to get involved with the Data Pop Alliance (http://www.datapopalliance.org/) with Director and Founder Emmanuel Letouze as one example network to bring together scientists and deveopers to "unlock" big data potential for humanity
3. get your thoughts and ideas of other already existing networks, forums, and actions we can take to bridge the scientist-developers gap.