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R Based tools for open and collaborative science
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Scott Chamberlain
July 26, 2013
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R Based tools for open and collaborative science
Ignite talk at ESA on R-based tools for open and collaborative science
Scott Chamberlain
July 26, 2013
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Transcript
R-based tools for open and collaborative science @recology_ Scott Chamberlain
Science needs to be more open
http://everyoneknowsbest.files.wordpress.com/2008/08/bodysculpture.jpg We build on the knowledge of others http://everyoneknowsbest.files.wordpress.com/2008/08/bodysculpture.jpg
Less mistakes More things can happen b/c data is open
http://everyoneknowsbest.files.wordpress.com/2008/08/bodysculpture.jpg The public paid for it!
http://www.fotopedia.com/items/flickr-4796633039 But we need tools to do it!!!!!
What kinds of tools? Not these
These!!!!!!
• Collect data • Manipulate data • Visualize • Analyze
• Write What does an ecologist do?
R is a good solution
• R is Open source = Free + Rapid change
• R = entire workflow in 1 place • R = reproducible science Why?
Get some data from the web library(RCurl); library(RJSONIO) dat <-
fromJSON(getURL("https://api.github.com/users/hadley/repos")) Manipulate the data library(plyr); library(reshape2) dat_melt <- melt(ldply(dat, function(x) data.frame(x[names(x) %in% c("name","watchers_count","forks")]))) Run some statistical model lm(value ~ variable, data = dat_melt) Visualize results library(ggplot2) ggplot(dat_melt, aes(name, value, colour = variable)) + geom_point() + coord_flip() Write the paper # Introduction...
Data increasingly on the web
The toolbelt
Literature library(rplos) plot_throughtime('phylogeny', 300) + geom_line(size=2)
Taxonomy library(taxize) classification("Abies procera", db = "itis") rankName taxonName
tsn Kingdom Plantae 202422 Subkingdom Viridaeplantae 846492 Infrakingdom Streptophyta 846494 Division Tracheophyta 846496 Subdivision Spermatophytina 846504 Infradivision Gymnospermae 846506 Class Pinopsida 500009 Order Pinales 500028 Family Pinaceae 18030 Genus Abies 18031 Species Abies procera 181835
Species occurrences from GBIF library(rgbif) splist <- c('Accipiter erythronemius', 'Junco
hyemalis', 'Aix sponsa', 'Podiceps cristatus') out <- occurrencelist_many(splist) gbifmap_list(out)
Occurrence from USGS’s BISON service library(rbison) out <- bison(species="Helianthus annuus",
count=500) bisonmap(input=out, tomap="county")
Climate data from the World Bank library(rWBclimate) country.list <- c("USA",
"MEX") country.dat <- get_historical_temp(country.list, "year") ggplot(country.dat, aes(x = year, y = data, group = locator)) + geom_point() + geom_path() + labs(y="Average annual temperature of Canada", x="Year") + theme_bw() + stat_smooth(se = F, colour = "black") + facet_wrap(~locator, scale = "free")
Take action! FontAwesome http://fortawesome.github.io/Font-Awesome/ fontawesome 2 png https://github.com/odyniec/font-awesome-to-png Presentation available
here: http://bit.ly/16tuVbu