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WIREs Data Mining Knowl Discov
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A survey of biodiversity informatics: Concepts, practices, and challenges

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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
Biodiversity informatics life cycle
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Multiple perspectives of a species‐collector network (SCN)
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General workflow of wildlife health monitoring
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Typical ENM steps comprising (1) preprocessing (occurrence data selection and retrieval, abiotic data selection and retrieval, and abiotic data correlation analysis and filtering), (2) modeling (algorithm configuration and execution), and (3) postprocessing (model projection and evaluation)
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Data publication using integrated publishing toolkit (IPT)
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Part of EML metadata in XML
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Relationship between global changes and biodiversity
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Algorithmic Development > Biological Data Mining

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