A standardisation framework for bio‐logging data to advance ecological research and conservation
A standardisation framework for bio‐logging data to advance ecological research and conservation
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用于推进生态研究和保护的生物记录数据标准化框架
DOI：
10.1111/2041-210x.13593
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发表时间：
2021
影响因子：
6.6
通讯作者：
Pye, Jonathan
中科院分区：
文献类型：
--
作者：
Sequeira, Ana M.;O'Toole, Malcolm;Keates, Theresa R.;McDonnell, Laura H.;Braun, Camrin D.;Hoenner, Xavier;Jaine, Fabrice R.;Jonsen, Ian D.;Newman, Peggy;Pye, Jonathan
通过标记动物获得的生物记录数据是应对全球保护挑战的关键。然而，数以千计的现有生物测井数据集不容易发现，不具有普遍可比性，也不容易通过现有存储库和跨平台访问，从而减缓了生态研究和有效管理的速度。需要一套通用的标准来确保生物测井数据的可发现性、互操作性和有效地将其转化为研究和管理建议。我们提出了一个标准化框架，遵循现有的数据原则(公平：可找到、可访问、可互操作和可重复使用；信任：透明度、责任、用户焦点、可持续性和技术)，并涉及使用简单的模板来创建从制造商和研究人员到合规存储库的数据流，其中应建立自动化程序，将数据可用性准备为四个标准化级别：(A)解码的原始数据，(B)精选数据，(C)内插数据和(D)网格数据。我们的框架允许集成简单的表格数组(例如CSV文件)，并创建可共享和可互操作的网络通用数据表单(NetCDF)文件，其中包含使用准确性、正确归属(确保数据提供商在整个过程中保持所有权)和数据保存安全所需的所有信息。我们展示了标准化对所有涉及的利益相关者的好处，并通过重点关注海洋动物和通过提供跨所有数据级别的工作流示例来说明我们框架的应用，包括在级别之间处理数据的填充模板和代码，采用我们的框架将有助于收集基本海洋变量(EOV)，以支持全球海洋观测系统(GOOS)和政府间评估(如世界海洋评估)，并将为在动物生态学的所有领域建立可互操作的生物记录数据格式的更广泛努力提供一个起点。
Bio‐logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio‐logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio‐logging data into research and management recommendations.We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy‐of‐use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security.We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing.Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter‐governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio‐logging data formats across all fields in animal ecology.
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影响因子：
3.8
作者：
Eikeset, Anne Maria;Mazzarella, Anna B.;Stenseth, Nils Chr.
通讯作者：
Stenseth, Nils Chr.
影响因子：
64.8
作者：
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通讯作者：
Raymond, Ben
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影响因子：
56.9
作者：
D. Kroodsma;Juan Mayorga;Timothy Hochberg;Nathan A. Miller;K. Boerder;F. Ferretti;A. Wilson;Bjorn Bergman;T. White;B. Block;P. Woods;Brian Sullivan;C. Costello;B. Worm
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B. Worm
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DOI：
--
发表时间：
2017
期刊：
影响因子：
--
作者：
K. Scales;E. Hazen;M. Jacox;C. Edwards;Andre M. Boustany;M. Oliver;S. Bograd
通讯作者：
S. Bograd
影响因子：
3.7
作者：
Bailey H;Fossette S;Bograd SJ;Shillinger GL;Swithenbank AM;Georges JY;Gaspar P;Strömberg KH;Paladino FV;Spotila JR;Block BA;Hays GC
通讯作者：
Hays GC