Retrieving biodiversity data from multiple sources: making secondary data standardised and accessible.

Biodiversity data, particularly species occurrence and abundance, are indispensable for testing empirical hypothesis in natural sciences. However, datasets built for research programmes do not often meet FAIR (findable, accessible, interoperable and reusable) principles, which raises questions about data quality, accuracy and availability. The 21 century has markedly been a new era for data science and analytics and every effort to aggregate, standardise, filter and share biodiversity data from multiple sources have become increasingly necessary.