A spatially integrated food web of the world derived from hundreds of thousands of interactions, across tens of thousands of species, and thousands of locations.
Sergey Slyusarev, Dimitrios-Georgios Kontopoulos, William Taysom, Adrian Guzman, and Bimlesh Wadhwa used GloBI data to create a food-web map  as part of the Information Visualization MOOC class of 2014 at Indiana University. The map was created by combining interaction data from GloBI’s Darwin Core Archive with terrestrial and marine ecoregions of the world and various openly available taxonomies (e.g., ITIS, NCBI, WoRMS). After eliminating taxa with few recorded interactions, species with similar predator-prey characteristics were grouped by a custom algorithm that was inspired by the Jaccard index, a similarity measure, and based on Infomap, a community-detection algorithm. The resulting interconnected taxa communities were then used to make an information-packed (gorgeous!) food-web visualization. The map was generated with a combination of custom R scripts, existing libraries (e.g., igraph, Reol, rgdal), Cytoscape, and Adobe Illustrator.
Explanation of how color, line width, and node size are used to encode spatial food-web information.
Color encoding of ecoregions around the world, plotted with interaction locations.
I find the integration of spatial information (e.g., marine, terrestrial) in this graph useful because I can quickly relate specific interactions to regions in the world. For instance, I can easily spot a coastal interaction as a filled node that also has a colored border. In addition, the directionality of the interactions are easy to understand thanks to color coding: predator is orange, prey is blue. Opening the high-resolution image in a run-of-the-mill image viewer, I can easily browse the map by zooming and moving with touch-pad gestures. With the help of this visualization, data anomalies in GloBI’s complex data collection were detected, reported through GloBI’s issue list (see here, here, here, and here), and corrected. This alone tells me that the visualization by Slyusarev et al. is a useful research tool.
Special thanks to all GloBI data contributors, Sergey for his suggestions for improving GloBI, and Scott Weingart of Indiana University for inviting GloBI as a client project of IVMOOC 2014. Can’t wait to work with the IVMOOC class of 2015!
 Slyusarev, Sergey; Kontopoulos, Dimitrios-Georgios; Taysom, William; Guzman, Adrian; Wadhwa, Bimlesh (2015): Global Biotic Interactions food web map. figshare. http://dx.doi.org/10.6084/m9.figshare.1297762 Retrieved 03:26, Feb 07, 2015 (GMT)