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  • 标题:Reproducible geospatial data science: Exploratory data analysis using collaborative analysis environments
  • 本地全文:下载
  • 作者:Alber Sánchez ; Lubia Vinhas ; Gilberto Queiroz
  • 期刊名称:Revista Brasileira de Cartografia
  • 印刷版ISSN:0560-4613
  • 电子版ISSN:1808-0936
  • 出版年度:2018
  • 卷号:70
  • 期号:5
  • 页码:1844-1859
  • DOI:10.14393/rbcv70n5-45036
  • 出版社:Sociedade Brasileira Cartografia - Geodesia
  • 摘要:Resumo The answers to planetary problems could be hidden in gigabytes of satellite imagery from the last 40 years. Unfortunately, scientists lack the means for processing such amount of data as they are used to work over small quantities of satellite images. To amend this issue, we propose the use of web services from Big Earth data platforms along collaborative analysis environments. Both Web services and collaborative analysis environments fit the hypothesis-test workflow followed by researchers while writing analysis routines. Besides, the early use of Big Earth data structures eases the subsequent process of scaling analysis up to larger extensions. To test our proposal, we use our own Big Earth observation data platform, on which decades of satellite images are arranged into data cubes. By using our Web services platform, we integrate those data cubes into our collaborative analysis environment (a Jupyter notebook). Since our analysis routines consume the same data structure of the whole data sets, it is easier to scale up the analysis.
  • 关键词:Reproducible science; data analysis; time series.
  • 其他关键词:Reproducible science, data analysis, time series.
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