Abstract
AbstractIn recent years, quantifying the impacts of detrimental air quality has become a global priority for researchers and policy makers. At present, the systems and methodologies supporting the collection and manipulation of this data are difficult to access. To support studies quantifying the interplay between common gaseous and particulate pollutants with meteorology and biological particles, this paper presents a comprehensive data-set containing daily air quality readings from the Automatic Urban and Rural Network, and pollen and weather data from Met Office monitoring stations, in the years 2016 to 2019 inclusive, for the United Kingdom. We describe (1) the sources from which the data were collected, (2) the methods used for the data cleaning process and (3) how issues related to missing values and sparse regional coverage were addressed. The resulting data-set is designed to be used ‘as is’ by those using air quality data for research; we also describe and provide open access to the methods used for curating the data to allow modification of or addition to the data-set.
Funder
Alan Turing Institute
RCUK | Engineering and Physical Sciences Research Council
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Reference22 articles.
1. Corrales, D. C., Ledezma, A. I. & Corrales, J. C. A systematic review of data quality issues in knowledge discovery tasks. Revista Ingenierías Universidad de Medellín 15, 125–149, https://doi.org/10.22395/rium.v15n28a7 (2015).
2. Lohr, S. For big-data scientists, ‘janitor work’ is key hurdle to insights. New York Times 17, B4 (2014).
3. Council, N. R. et al. Steps toward large-scale data integration in the sciences: Summary of a workshop (National Academies Press, 2010).
4. Furche, T., Gottlob, G., Libkin, L., Orsi, G. & Paton, N. W. Data wrangling for big data: Challenges and opportunities. In EDBT 16, 473–478 (2016).
5. Reichman, O. J., Jones, M. B. & Schildhauer, M. P. Challenges and opportunities of open data in ecology. Science 331, 703–705 (2011).
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献