Figure 1.

A graphical representation of the concepts in the BIP Index, and example for four countries. The BIP Index for a country is the Euclidean distance to origin in a four-dimensional space (here represented as a three-dimensional space for simplicity; two of the dimensions have been merged together in the z axis). The dimensions of the space represent the capacity of the country to hold biodiversity data (SPCS), related to concept 1 in the Definitions section; to generate raw biodiversity data (DAT) or quality biodiversity data (GRF), related to concept 2; and to host biodiversity data (HOST), related to concept 3. The green vector signals how BIP increases along the three concept scales: the higher a country ranks against these concepts, the greater its BIP score and therefore its biodiversity informatics potential. Thus, a country occupies a position in this space, and the length of the vector from the origin to the country's position (its Euclidean distance) is the BIP Index. The longer the vector, the higher the BIP score. The highest possible BIP Index is the length of the green vector. The four blue vectors are the BIP Index scores for four example countries. A country can be nearer one plane than other country, meaning that that dimension is more important in that country. For example, Brazil (BRA) has higher potential than Australia (AUS) or Austria (AUT) mainly because of higher biodiversity potential, and these two countries, also with a high BIP Index, owe it more to their hosting capacity. Bolivia (BOL) also lies towards the DAT+GRF and SPCS planes (more so to the latter), but has a lower score and thus a lower overall BIP Index.

AriƱo et al. BMC Bioinformatics 2011 12(Suppl 15):S4   doi:10.1186/1471-2105-12-S15-S4