Jorrit Poelen jhpoelen

	predator name	prey name
	Homo sapiens	Canis familiaris

What do great white sharks (Carcharodon carcharias) eat?

Global Biotic Interactions (GloBI, http://globalbioticinteractions.org) uses neo4j to capture recorded interactions between living organisms on our planet. This page give an introduction into how the interactions are currently captured and how to make queries to retrieve specific information.

This page not only serves as a getting started guide, but also as a way to solicit feedback on the way the data is modeled. So . . . please don’t hesitate to share comments or ask questions.

	# see Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and
	# analyze species-interaction datasets. Ecological Informatics. http://dx.doi.org/10.1016/j.ecoinf.2014.08.005

	# rasterize locations, retrieve stats for bounding boxes, plot graphs
	if (!'package:raster' %in% search()) {
	install.packages(c('raster','maps'), repos='http://cran.us.r-project.org')
	library('raster')
	library('maps')
	}

	# install rgbif and rglobi libraries (see http://ropensci.org for more info)
	install.packages(c('rgbif', 'rglobi'))

	# define geometric bounding box (around california)
	geo1 <- "POLYGON((-126 32, -114 32, -114 41, -126 41, -126 32))"

	# retrieve a bunch of occurrences of Mustelidae with the geometric area
	mustelidaeOcc <- rgbif::occ_search(scientificName='Mustelidae', fields='minimal', geometry = geo1)$data

	# get any interactions records involving unique taxa occurrences at bbox geo1

	#install rglobi (see ropensci.org for more info)
	install.packages(c('rglobi'))

	# read species list after exporting as csv
	krak <- read.csv(file='Krak_list_DELETE.csv', stringsAsFactors=F)
	# pick unique families
	taxonList <- unique(krak$Family)

	# find and aggregate interactions for each species . . . one by one
	interactions <- Reduce(function(accum, taxon) {

	{
	"creator":"jhpoelen",
	"notification_address": ["[email protected]"],
	"predicate":
	{
	"type":"and",
	"predicates": [
	{"type":"equals","key":"HAS_GEOSPATIAL_ISSUE","value":"false"},
	{"type":"equals","key":"HAS_COORDINATE","value":"true"}
	]

	# retrieve trophic interactions related to species
	# that were recorded at or near McLaren Park
	# using GloBI and GBIF

	install.packages(c('rglobi', 'rgbif'))

	mcLarenWKT <- 'POLYGON((-122.435 37.726,-122.406 37.726, -122.406 37.710, -122.435 37.710, -122.435 37.726))'
	mcLarenObs <- rgbif::occ_search(geometry= mcLarenWKT)

	gbifSpeciesKeys <- na.omit(unique(mcLarenObs$data$speciesKey))