The Value of Crowd-Sourcing and Private Sector Data Analysis in Disaster Response

Today, Senior Geospatial scientist Steven Ward presented to the class the ways in which his company ‘DigitalGlobe‘ combines ICT, geospatial data, satellite imagery for use in a number of industries, including development. DigitalGlobe operates a number of satellites that take images of the earth’s surface and disseminates them to a number of clients, including the US government, Google, the UN, and various NGOs, among many others. An even more critical aspect of the company is the data analysis it provides, which is largely supplemented by crowdsourcing techniques. For example, scientists like Steven Ward will publicize certain images of a disaster area, such as satellite photographs taken of a mountain range in which climbers have gone missing. DigitalGlobe employees will then look at trends of information tagged on these pictures by the public, an analysis that is augmented by a number of algorithms that help to determine the degree of validity of the information they are receiving. They can then analyze the aggregate data to try and find precisely where the missing climbers set up their base camp, climbed, and eventually fell (find the story here). Though this specific case is tragic, it reveals a host of ways in which vital information can be amassed through ICT techniques such as crowdsourcing, as well as how tech-based firms can contribute their innovations and analysis in times of need.  The company is an important example of the private sector’s role in aiding humanitarian crises as well as its contributions in developing key information systems that can make or break disaster response.

Another important take-way from Ward’s lecture was simply the logic surrounding open-source data analysis, which is an ICT in itself. Ward pointed out that “more hands make light work”, which is a critical notion in time sensitive situations such as Guinea’s recent Ebola outbreak, where health care experts need as much data as possible to determine the pathways of an extremely lethal disease in a population dense area. Though some might worry that information coming from the masses is more likely to be incorrect, this is actually a misconception; Wikipedia, which is a compilation made by thousands of ‘amateurs’ has a credibility ranking of 8/10, while Encyclopedia Britannica, which is a collaboration of fewer ‘experts’, has a score of 8.8/10. The fact that these sources have such similar scores demonstrates a key point of value for crowdsourcing techniques: the more people that contribute to and review the data, the more accurate it is likely to be. Therefore crowdsourcing in itself is many times one of the most valuable approaches to mapping disaster and crises, as well as other, less time sensitive development sectors such as poverty, agribusiness land-grabbing, vulnerable agricultural lands, and thousands of other factors that may be critical to the interventions of stakeholders within the field.

 

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One response to “The Value of Crowd-Sourcing and Private Sector Data Analysis in Disaster Response

  • jboleky

    Mr. Ward did indeed address everyone’s questions and concerns about crowd-sourcing: the reliability factors, the concern it might be abused, weeding out good data from the bad, and how they identify (through ground teams, and other data) who is trying to “rig the system.” However after the cyber security talk we had the idea combined with DigitalGlobe’s involvement in politically sensitive events like the recent events in Ukraine, just how secure is DigitalGlobe? They seem well equipped to deal with a few bad eggs, but what about a coordinated attack by an elite hacking group, this is especially true if they involve themselves in such political events. In many ways this is a concern everyone has because these hacking groups are so powerful, but i wish i would have thought if this during the talk it would have been interesting to see if they had thought of the idea at all. Really what can anyone do against these powerful groups? Post thoughts below.

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