Data-intensive science applied to broad-scale citizen science

摘要: Identifying ecological patterns across broad spatial and temporal extents requires novel approaches methods for acquiring, integrating modeling massive quantities of diverse data. For example, a growing number research projects engage continent-wide networks volunteers (‘citizen-scientists') to collect species occurrence Although these data are information rich, they present numerous challenges in project design, implementation analysis, which include: developing collection tools that maximize quantity while maintaining high standards quality, applying new analytical visualization techniques can accurately reveal Here, we describe how advances data-intensive science provide accurate estimates distributions at continental scales by identifying complex environmental associations.