One of the biggest hurdles of shark conservation is the lack of data on abundance and distribution of about half of their species. To address this challenge we have developed sharkPulse, a modular crowd-sourcing platform combining smartphone technology, web applications, social network/website crawling, computer vision, and machine learning for generating a large image-based sighting database for sharks.

The goal is warehousing shark images available on the web and personal archives, and transform them into occurrence records. This platform aims to show how citizen science can be harnessed to produce big data, inform ecological science and promote conservation.