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Article published on September 27, 2016 (by James D. Ford, Simon E. Tilleard, Lea Berrang-Ford, Malcolm Araos, Robbert Biesbroek, Alexandra C. Lesnikowski, Graham K. MacDonald, Angel Hsu, Chen Chen, and Livia Bizikova)

Article Summary

With the advancements made in processing and analyzing “big data”, researchers can leverage this data to improve decision-making, risk management, and research surrounding climate change adaptation, an often overlooked application of big data. The primary adaptation applications of big data include vulnerability assessment, early warning, and monitoring and evaluation. In environmental research, the main advantage of utilizing big data is the ability to use automatically collected real-time data, which saves hours of survey or interview-based methods of data collection. Passively collected digital data have the potential to enhance the monitoring of climate-related threats and vulnerabilities and can provide real-time awareness and feedback to decision makers and emergency services. However, solely using big data in climate change adaptation research can cause issues to due insights that get lost in the massive data sets. Researchers must have an integrated approach with both the big data and rigorous qualitative analysis and small data analytics.

Areas of Application

Vulnerability Assessment

Vulnerability research provides essential information for adaptation decision-making by identifying and characterizing who and what are vulnerable to climate change, to what risks, why, and over what timescales. Big data analytics can help to fill these gaps and have the advantage of being able to use automatically collected real-time data, an important consideration in data-poor environments, especially given the time-consuming nature of survey and interview-based methodologies.

Early Warning

Surveillance and the provision of early warnings is an important component of enhancing the capacity to respond to climate change. Many big data applications have been pioneered for use in early detection, whereby passively collected data from the use of digital services have been variously used: from detecting influenza epidemics based on flu-related queries coming into search engines, to the use of Twitter posts to identify areas affected by earthquakes.

Monitoring and Evaluation

In terms of monitoring and evaluation, because there is limited data on adaptation action and outcomes, big data can process and analyze large sets of cell phone and social media data to garner concrete metrics on perception and behavior.

Combining “Big” and “Small” Data

Although analyzing large sets of data can provide useful insights, there is the possibility of information slipping through the cracks when using big data. Scientists are leaning towards methods involving both quantitative data analysis with in-depth qualitative analysis with small data sets.

Author Information

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James D Ford, the primary author of the article, is a professor and Priestley Chair in Climate Adaptation at McGill University with a multitude of publications regarding climate change adaptation research and trends. His work consists of the interface between climate and society, and his primary interests in climate are change vulnerability and adaptation.

Other academic work and contributions

Next Steps

Big data are not the tell-all solution, but if carefully used, they provide an enormous and untapped opportunity to diversify our understanding of adaptation and inform decision-making. These are some steps that should be taken in the coming years in order to improve the use of data analytics in the climate change adaptation field:

  • Scientists investigating adaptation must reach out to data scientists who have the skills to clean, organize, link, manage, and analyze massive datasets
  • Adaptation specialists must work with data engineers to design information systems to scrape, collect, and sort data
  • Diversify training of adaptation scholars and practitioners to be literate in big data analytics