ecocomDP: A flexible data design pattern for ecological community survey data
ecocomDP: A flexible data design pattern for ecological community survey data
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DOI：
10.1016/j.ecoinf.2021.101374
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发表时间：
2021-07-30
影响因子：
5.1
通讯作者：
Castorani, Max C. N.
中科院分区：
文献类型：
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作者：
O'Brien, Margaret;Smith, Colin A.;Castorani, Max C. N.
协调数据的想法并不新鲜。几十年来，根据当地和全球的社区标准在数据库中积累数据，在一些研究领域比其他研究领域更成功。在抽样方案差异很大、需要了解复杂的环境条件才能正确应用分析方法的研究中，协调数据尤其困难。然而，越来越多的长期生态群落观察正在变得公开，并已被用于重要研究。在这里，我们讨论一种由环境数据储存库与国家天文台合作准备协调社区调查数据的方法。工作流程框架和储存库基础设施用于创建一个分散的、异步的模型，以便在不通过清理或聚合改变原始数据的情况下重新格式化数据，同时保留有关抽样方法和来源的元数据，并实现编程数据访问。这种方法不会创建另一个数据“竖井”，但将允许存储库将可用数据的子集贡献给各种不同的分析就绪数据准备工作。在某些限制(例如，采样协议随时间变化)的情况下，数据更新和下游处理可以完全自动化。除了支持综合科学重复使用社区观测数据外，这种协调和工作流程的一个目标是将这些数据集贡献给全球生物多样性信息基金(GBIF)，以增加数据的发现和使用。
The idea of harmonizing data is not new. Decades of amassing data in databases according to community standards both locally and globally have been more successful for some research domains than others. It is particularly difficult to harmonize data across studies where sampling protocols vary greatly and complex environmental conditions need to be understood to apply analytical methods correctly. However, a body of longterm ecological community observations is increasingly becoming publicly available and has been used in important studies. Here, we discuss an approach to preparing harmonized community survey data by an environmental data repository, in collaboration with a national observatory. The workflow framework and repository infrastructure are used to create a decentralized, asynchronous model to reformat data without altering original data through cleaning or aggregation, while retaining metadata about sampling methods and provenance, and enabling programmatic data access. This approach does not create another data 'silo' but will allow the repository to contribute subsets of available data to a variety of different analysis-ready data preparation efforts. With certain limitations (e.g., changes to the sampling protocol over time), data updates and downstream processing may be completely automated. In addition to supporting reuse of community observation data by synthesis science, a goal for this harmonization and workflow effort is to contribute these datasets to the Global Biodiversity Information Facility (GBIF) to increase the data's discovery and use.