Does Geospatial Data Unite the World?


This interesting post from BigData-Startups, which newsletter I got today, discusses use of geospatial data in providing better customer service, explains well what those data are about, and gives examples of two startups, SpaceCurve and Loqate, thriving on developing tools for analysis of geospatial data. This reading made me think about usage of geospacial data in biology and medicine.

The possibilities are abandoned and some of the examples are already well-know: Google flu trends around the world based on Google search activities and the online interactive chart of vaccine preventable outbreaks around the world from 2006 to present day that covers outbreaks for measles, mumps, rubella, polio, whooping cough, and “other” (the data are downloadable as a CSV file that includes source citation, country, longitude/latitude, number of cases and fatalities by outbreak type). The image above is the screen-shot of that chart for 2013; it can be seen that in 2013 there was one case of typhoid in San Francisco. Those and similar monitoring systems are important tools for prevention of disease outbreaks and smart transportation and storage of vaccines and medication.

Another possibilities can be seen in the fitness domain, where geospatial data, together with data of people moving activities, can be used for smart distribution of recreational centers and construction of new bike and jogging lanes, not talking about sales and marketing of fitness devices and mobile apps. Same is true for stores and restaurants specialized in health products and organic food, and food banning policies.

Yet, geospatial data coupled with personal medical and genetic data and data coming from apps and wearable sensors monitoring various physiological activities of our bodies, like blood glucose level or pressure, will soon be a powerful tool for a personalized medicine — that account for a person geolocation and time of year as well. Those data will be also helpful in geographically locating populations susceptible to diseases or environmental cataclysms (see this relevant post about search for rare human phenotypes for drug development). And, obviously, no one can talk seriously about environmental data without considering geospatial data as well.

Then think about animals, wild and domesticated, about crops, produce and plants, and water surrounding us — everything is connected, and it appears that we are all connected via data, obviously hugely Big-Big Data; and extracting knowledge and prognoses from these data makes us appreciate and value the diversity of life on Earth more than ever.


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