Big Data Tsunami at the Interface of Statistics, Environmental Sciences and Beyond (16w2669)

Arriving in Banff, Alberta Friday, March 11 and departing Sunday March 13, 2016

Organizers

Yulia Gel (University of Texas at Dallas)

Leticia Ramirez Ramirez (Centro de Investigacion en Matematicas)

(University of Maryland Center for Environmental Science)

Objectives

With all the buzz around available Big Data, it is not hype and many capabilities that are possible by innovative combining information across disciplines remain untapped. The primary goal and the key difference of this 2-day workshop from other Big Data events is that it will bridge together disciplines and methodologies that typically never meet or interact at other conferences and scientific gatherings but which are in fact intrinsically close. In particular, we plan to highlight three tightly woven themes: Climate, Infectious Disease Epidemiology and Social Media; Weather, Climate and Complex Socio-Ecological Networks; and Climate Change Vulnerability, Risk Mitigation and Adaptation. Climate, Infectious Disease Epidemiology and Social Media The prompt detection and forecasting of emerging climate-sensitive infectious diseases with rapid transmission and high virulence are critical in the effective defense against these diseases. Despite many promising approaches in modern surveillance methodology, the lack of observations for near real-time forecasting is still the key challenge obstructing operational disease prediction and control. In contrast, fusing non-traditional data sources, such as social media and climate/weather projections, creates a new momentum for real-time epidemiological forecasting and has a potential to revolutionize modern biosurveillance capabilities by predicting an event before its typical manifestation. Critical importance of an interdisciplinary data and methodology fusion to operational forecasting of climate-sensitive infectious diseases is well recognized, for example, by the recent Google Influenza and Google Dengue projects, the CDC2013 and DARPA2014 challenges, to name a few.

Weather, climate and complex socio-ecological networks in turn, the way ecosystem components (e.g., species-species, predator-prey relations etc.) interact and evolve over time at the face of exogenous shocks such as extreme weather events, climate change, and human impact, are shown to be similar to the social network structure of humans, including online social media networks, which is also the modern cornerstone of the first theme.

Climate change vulnerability, risk mitigation and adaptation finally, the adverse effects of climate change bring increasingly more alterations to all aspects of human life and welfare. For example, one of the sectors that is particularly affected by changing climate is the insurance industry. (The year 2013 brought a record amount of claims and losses due to weather related damages, which in Canada alone cost the insurance industry more than $3 billion.) Hence, there exists a critical need to develop a novel methodology for diagnostics and future projection of weather-related risks, with an overall goal to reduce financial and public safety repercussions of volatility related to extreme climatic events. This requires modeling of future dynamics of extreme climate and weather events and quantification of estimation uncertainties at multiple space-time resolutions, which also constitutes the key input factors in the first two themes.

Thus, our ultimate goal is to bring together a productive combination of various modern and yet relatively scarcely investigated perspectives on modeling and fusing massive multi-source multi-scale data and to encourage debate, which will lead to cross-fertilization of ideas and enhancing cohesion between experts from statistics, applied mathematics, computer science, social sciences, geography, ecology, hydrology and other environmental disciplines.