@conference {JRN54450,
	title = {Facilitating knowledge discovery and visualization through mining contextual data from published studies: lessons from JournalMap},
	booktitle = {100th Annual Meeting of the Ecological Society of America},
	year = {2015},
	month = {08/2015},
	publisher = {Ecological Society of America},
	organization = {Ecological Society of America},
	address = {Baltimore, MD},
	abstract = {<p>Valuable information on the location and context of ecological studies are locked up in publications in myriad formats that are not easily machine readable. This presents significant challenges to building geographic-based tools to search for and visualize sources of ecological knowledge. JournalMap is a scientific literature search engine that was created to enable discovery of relevant research based on location and biophysical attributes along with traditional keyword searching. We will present approaches developed in JournalMap for mining, mapping and visualizing study location information from scientific articles using pattern recognition algorithms and crowdsourcing tools.\&nbsp; IGN 6-5.</p>
},
	author = {Jason W. Karl and Jeffrey K. Gillan}
}
