Biodiversity informatics is a relatively new discipline extending computer science in the context of biodiversity data, and its development to date has not been uniform throughout the world. Digitizing effort and capacity building are costly, and ways should be found to prioritize them rationally. The proposed 'Biodiversity Informatics Potential (BIP) Index' seeks to fulfill such a prioritization role. We propose that the potential for biodiversity informatics be assessed through three concepts: (a) the intrinsic biodiversity potential (the biological richness or ecological diversity) of a country; (b) the capacity of the country to generate biodiversity data records; and (c) the availability of technical infrastructure in a country for managing and publishing such records.

Broadly, the techniques used to construct the BIP Index were rank correlation, multiple regression analysis, principal components analysis and optimization by linear programming. We built the BIP Index by finding a parsimonious set of country-level human, economic and environmental variables that best predicted the availability of primary biodiversity data accessible through the Global Biodiversity Information Facility (GBIF) network, and constructing an optimized model with these variables. The model was then applied to all countries for which sufficient data existed, to obtain a score for each country. Countries were ranked according to that score.

Many of the current GBIF participants ranked highly in the BIP Index, although some of them seemed not to have realized their biodiversity informatics potential. The BIP Index attributed low ranking to most non-participant countries; however, a few of them scored highly, suggesting that these would be high-return new participants if encouraged to contribute towards the GBIF mission of free and open access to biodiversity data.

The BIP Index could potentially help in (a) identifying countries most likely to contribute to filling gaps in digitized biodiversity data; (b) assisting countries potentially in need (for example mega-diverse) to mobilize resources and collect data that could be used in decision-making; and (c) allowing identification of which biodiversity informatics-resourced countries could afford to assist countries lacking in biodiversity informatics capacity, and which data-rich countries should benefit most from such help.