Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse.
Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse.
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DOI：
10.1186/s13742-015-0067-4
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发表时间：
2015
期刊：
影响因子：
9.2
通讯作者：
Webster KE
中科院分区：
文献类型：
--
作者：
Soranno PA;Bissell EG;Cheruvelil KS;Christel ST;Collins SM;Fergus CE;Filstrup CT;Lapierre JF;Lottig NR;Oliver SK;Scott CE;Smith NJ;Stopyak S;Yuan S;Bremigan MT;Downing JA;Gries C;Henry EN;Skaff NK;Stanley EH;Stow CA;Tan PN;Wagner T;Webster KE
虽然有相当多的关于个别或各组生态系统的基于地点的数据，但这些数据集分散得很广，有不同的数据格式和惯例，而且往往难以获得。在更广泛的范围内，国家数据集存在大量的土地，水和空气的地理空间特征，需要充分了解这些生态系统之间的变化。然而，这些数据集来自不同的来源，具有不同的空间和时间分辨率。通过采取开放科学的观点，并结合基于站点的生态系统数据集和国家地理空间数据集，科学获得了提出与大规模环境挑战相关的重要研究问题的能力。建议通过同行评审的论文记录这种复杂的数据库集成工作，以促进集成数据库的再现性和未来使用。在这里，我们描述的主要步骤，挑战和考虑因素，在建立一个综合数据库的湖泊生态系统，称为拉各斯（湖泊多尺度地理时空数据库），这是在美国17个州（180万平方公里）的次大陆研究范围内开发的。拉各斯包括两个模块：LAGOSGEO，研究范围内表面积大于4公顷的每个湖泊的地理空间数据（约50，000个湖泊），包括在一系列空间和时间范围内测量的气候、大气沉积、土地利用/覆盖、水文、地质和地形;和LAGOSLIMNO，湖泊水质数据来自研究范围内（约10，000个湖泊）湖泊子集的约100个单独数据集。整合数据集的程序包括：创建灵活的数据库设计;编写和整合元数据;记录数据来源;量化地理数据的空间计量;对整合和衍生数据进行质量控制;以及广泛记录数据库。我们的程序使一个大型的，复杂的，集成的数据库可复制和可扩展，允许用户提出新的研究问题与现有的数据库或通过添加新的数据。这项任务的最大挑战是数据、格式和元数据的异构性。数据集成的许多步骤需要来自不同领域的专家的手动输入，需要密切合作。本文的在线版本（doi：10.1186/s13742-015-0067-4）包含补充材料，可供授权用户使用。
Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km2). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration. The online version of this article (doi:10.1186/s13742-015-0067-4) contains supplementary material, which is available to authorized users.
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影响因子：
10.3
作者：
Hampton, Stephanie E.;Strasser, Carly A.;Porter, John H.
通讯作者：
Porter, John H.
影响因子：
6.1
作者：
de Roos, AM;Leonardsson, K;Mittelbach, GG
通讯作者：
Mittelbach, GG
影响因子：
10.3
作者：
Cheruvelil, Kendra S.;Soranno, Patricia A.;Read, Emily K.
通讯作者：
Read, Emily K.
影响因子：
10.1
作者：
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通讯作者：
Porter, John H.
影响因子：
10.1
作者：
Soranno, Patricia A.;Cheruvelil, Kendra Spence;Stow, Craig A.
通讯作者：
Stow, Craig A.