  The unprecedented size of the human population, along with its associated
economic activities, have an ever increasing impact on global environments.
Across the world, countries are concerned about the growing resource
consumption and the capacity of ecosystems to provide them. To effectively
conserve biodiversity, it is essential to make indicators and knowledge openly
available to decision-makers in ways that they can effectively use them. The
development and deployment of mechanisms to produce these indicators depend on
having access to trustworthy data from field surveys and automated sensors,
biological collections, molecular data, and historic academic literature. The
transformation of this raw data into synthesized information that is fit for
use requires going through many refinement steps. The methodologies and
techniques used to manage and analyze this data comprise an area often called
biodiversity informatics (or e-Biodiversity). Biodiversity data follows a life
cycle consisting of planning, collection, certification, description,
preservation, discovery, integration, and analysis. Researchers, whether
producers or consumers of biodiversity data, will likely perform activities
related to at least one of these steps. This article explores each stage of the
life cycle of biodiversity data, discussing its methodologies, tools, and
challenges.

Populations and Evolution;Databases