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.
翻译:人类人口规模之大及其相关的经济活动,对全球环境的影响日益扩大。在全世界,各国对资源消耗不断增长以及生态系统提供生物多样性的能力感到关切。为了有效保护生物多样性,必须使决策者能够以他们能够有效使用的方式公开获得指标和知识。制定和部署制作这些指标的机制取决于能否获得实地调查和自动传感器、生物收集、分子数据以及历史学术文献提供的可靠数据。将这种原始数据转化为适于使用的综合性信息需要经过许多改进步骤。管理和分析这些数据的方法和技术包括一个通常称为生物多样性信息学(或电子生物多样性)的领域。生物多样性数据遵循一个生命周期,由规划、收集、认证、描述、保存、发现、整合和分析组成。研究人员,无论是生物多样性数据的生产者还是消费者,都可能至少开展其中一个步骤的相关活动。本文章探讨了生物多样性数据生命周期的每个阶段,讨论了其方法、工具和挑战。