A survey of biodiversity informatics: Concepts, practices, and challenges

Abstract

The unprecedented size of the human population, along with its associated economic activities, has 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 resources. 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 tools and techniques to generate these indicators require having access to trustworthy data from biological collections, field surveys and automated sensors, molecular data, and historic academic literature. The transformation of these raw data into synthesized information that is fit for use requires going through many refinement steps. The methodologies and techniques applied to manage and analyze these data constitute an area usually called biodiversity informatics. Biodiversity data follow 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. This article is categorized under: Algorithmic Development > Biological Data Mining

Networked computing systems for bio-diversity and environmental preservation

“…Nevertheless, cloud computing platforms provide an invaluable resource for acquiring and processing data related to environmental biodiversity. In this regard, cloud computing platforms play an important role in techno-environment analysis related to bio-diversity as seen in 14 , 15 .…”

“…Gadelha et al . 15 address the challenge of biodiversity preservation in an ecosystem to quantify the biodiversity preservation concern. The considered variables are (1) Number of available species, (2) Number of individuals in each species and (3) Inter-species interaction context (trophic, competitive and symbiotic).…”

“…A semantic approach is also presented by Gadelha et al . 15 via an ecological metadata language. The ecological metadata language is developed to describe acquired ecological data i.e.…”

Open Data Practices among Users of Primary Biodiversity Data

“…As the biodiversity research literature continues to grow, the open sharing of biodiversity data is increasingly recognized as necessary and is quickly becoming normalized (Peterson et al 2018 , Ball-Damerow et al 2019 , Heberling et al 2021 ). Presence-only biodiversity data are relatively representative of broad taxonomic and geographic trends associated with the field of biodiversity as a whole, but they differ in the ease with which they can be shared in accordance with currently recognized best practices (König et al 2019 , Anderson et al 2020 , Wüest et al 2020 , Gadelha et al 2021 ). Therefore, as practices continue to be developed to facilitate the sharing of a wide range of data types (Anderson et al 2020 ), presence-only data can serve as an early indicator to illustrate the progress, challenges, and limitations to the adoption of biodiversity data sharing practices.…”

“…Although any type of data can be openly shared, the biodiversity data type most readily associated with open data sharing is presence-only occurrence data (König et al 2019 , Anderson et al 2020 , Wüest et al 2020 , Gadelha et al 2021 ). Presence-only data consist of the taxonomic identification and location of an organism, often with the time of observation but without further information about species abundance, sampling design, or sites at which the species was not observed.…”