  The easy access to large data sets has allowed for leveraging methodology in
network physics and complexity science to disentangle patterns and processes
directly from the data, leading to key insights in the behavior of systems.
Here we use to country specific food production data to study binary and
weighted topological properties of the bipartite country-food production
matrix. This country-food production matrix can be: 1) transformed into overlap
matrices which embed information regarding shared production of products among
countries, and or shared countries for individual products, 2) identify subsets
of countries which produce similar commodities or subsets of commodities shared
by a given country allowing for visualization of correlations in large
networks, and 3) used to rank country's fitness (the ability to produce a
diverse array of products weighted on the type of food commodities) and food
specialization (quantified on the number of countries producing that food
product weighted on their fitness). Our results show that, on average,
countries with high fitness producing highly specialized food commodities also
produce low specialization goods, while nations with low fitness producing a
small basket of diverse food products, typically produce low specialized food
commodities.
