Sterner Beckett, Upham Nathan, Gupta Prashant, Powell Caleb, Franz Nico M
Arizona State University, Tempe, United States of America.
Biodivers Inf Sci Stand. 2021;5. doi: 10.3897/biss.5.75587. Epub 2021 Sep 23.
Making the most of biodiversity data requires linking observations of biological species from multiple sources both efficiently and accurately (Bisby 2000, Franz et al. 2016). Aggregating occurrence records using taxonomic names and synonyms is computationally efficient but known to experience significant limitations on accuracy when the assumption of one-to-one relationships between names and biological entities breaks down (Remsen 2016, Franz and Sterner 2018). Taxonomic treatments and checklists provide authoritative information about the correct usage of names for species, including operational representations of the meanings of those names in the form of range maps, reference genetic sequences, or diagnostic traits. They increasingly provide taxonomic intelligence in the form of precise description of the semantic relationships between different published names in the literature. Making this authoritative information Findable, Accessible, Interoperable, and Reusable (FAIR; Wilkinson et al. 2016) would be a transformative advance for biodiversity data sharing and help drive adoption and novel extensions of existing standards such as the Taxonomic Concept Schema and the OpenBiodiv Ontology (Kennedy et al. 2006, Senderov et al. 2018). We call for the greater, global Biodiversity Information Standards (TDWG) and taxonomy community to commit to on how FAIR applies to biodiversity data and include practical targets and criteria for the publication and digitization of taxonomic concept representations and alignments in taxonomic treatments, checklists, and backbones.
充分利用生物多样性数据需要高效且准确地将来自多个来源的生物物种观测数据联系起来(比兹比,2000年;弗兰兹等人,2016年)。使用分类学名称和同义词汇总出现记录在计算上是高效的,但当名称与生物实体之间一对一关系的假设不成立时,已知在准确性方面会有显著限制(雷姆森,2016年;弗兰兹和施特纳尔,2018年)。分类学处理和名录提供了关于物种名称正确用法的权威信息,包括以分布图、参考基因序列或诊断特征等形式呈现的这些名称含义的操作表示。它们越来越多地以精确描述文献中不同已发表名称之间语义关系的形式提供分类学知识。使这些权威信息具有可查找、可访问、可互操作和可重用性(FAIR;威尔金森等人,2016年)将是生物多样性数据共享的变革性进展,并有助于推动采用和扩展现有标准,如分类学概念模式和开放生物多样性本体(肯尼迪等人,2006年;森德罗夫等人,2018年)。我们呼吁全球更大的生物多样性信息标准(TDWG)和分类学界致力于研究FAIR如何应用于生物多样性数据,并纳入分类学概念表示以及分类学处理、名录和主干中的比对的发布和数字化的实际目标及标准。