Conversion of measurements of tree ring gains: Canada, Africa, Mexico, South America from RWL- files to JSON format.
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The International Tree Rings Data Bank (ITRDB) is the most comprehensive tree growth database (https://www1.ncdc.noaa.gov/pub/data/paleo/treering). Shoudong Zhao, et al. (2019, 2018) analyzes the representativity of dendrochronological data (ITRDB) and proposes a corrected database with error indications. One of the bottlenecks of data use (ITRDB) is that the data is loaded as a collection of separate files in the Tucson positional format. The purpose of our data presentation is to change the Tucson data format to JSON format and combine the separate files into one. We convert the initial data for the <strong>Canada</strong>, <strong>Africa</strong>, <strong>Mexico</strong> and <strong>Southamerica</strong> rwl-files into Json format of data on tree growth in four files: <strong>canada.json</strong>, <strong>africa.json</strong>, <strong>mexico.json</strong> and <strong>southamerica.json</strong>. The data was converted using the R programming language and the dplR program library Bunn, A. (2008) The experience of developing the structure of dendroclimatic data in JSON format is described in the works of Kachaev A. (2016, 2017, 2020). Description of the structure of JSON data format is attached in the files ReadMe.pdf References Bunn, A. G. (2008). A dendrochronology program library in R (dplR). Dendrochronologia, 26, 115-124. https://doi.org/10.1016/j.dendro.2008.01.002 Kachaev, Alexander (2020), "Compact dataset of dendrochronological data of pri-mary metric characteristics of tree rings of Asia.", Mendeley Data, V1, doi: 10.17632 / p9zhpmzgtk.1 Kachaev A. V. (2017) Model for describing the structure of dendroclimatic data In the collection: Regional problems of remote sensing of the Earth Materials of the IV international scientific conference. Siberian Federal University, Institute of Space and Information Technologies. p. 120-122. (Russia) Kachaev A. V. (2016) NOSQL Approach for Development of Dendroclimatic Data Bank. In the collection: Regional problems of remote sensing of the Earth. Materials of the III International Scientific Conference. p. 89-91. (Russia) Shoudong Zhao, et al. (2019). The International Tree-Ring Data Bank (ITRDB) revisited: Data availability and global ecological representativity. Journal of Biogeography, 46 (2), 355-368. doi: 10.1111 / jbi.13488 Zhao, Shoudong et al. (2018), Data from: The International Tree-Ring Data Bank (ITRDB) revisited: data availability and global ecological representativity, Dryad, Dataset, https://doi.org/10.5061/dryad.kh0qh06
国际树木年轮数据库（International Tree Rings Data Bank, ITRDB）是目前最全面的树木生长数据库，其公开数据地址为https://www1.ncdc.noaa.gov/pub/data/paleo/treering。赵守东等（2019、2018）对树木年代学数据（ITRDB）的代表性开展了分析，并提出了带有误差标注的校正数据库。当前该类数据的使用瓶颈之一，在于其以图森（Tucson）位置格式的独立文件集合形式存储。本数据集旨在将图森格式的数据转换为JSON（JavaScript Object Notation）格式，并将分散的单个文件整合为统一文件。我们依托R编程语言及dplR程序库（Bunn, A. 2008），将加拿大、非洲、墨西哥与南美洲的rwl格式文件转换为JSON格式的树木生长数据，分别生成四个数据文件：canada.json、africa.json、mexico.json以及southamerica.json。关于将树木气候学数据结构开发为JSON格式的实践经验，可参阅Kachaev A.（2016、2017、2020）的相关研究。JSON数据格式的结构说明详见附件文件ReadMe.pdf。 参考文献 1. Bunn, A. G. (2008). A dendrochronology program library in R (dplR). *Dendrochronologia*, 26, 115-124. https://doi.org/10.1016/j.dendro.2008.01.002 翻译：Bunn, A. G.（2008）。基于R语言的树木年代学程序库（dplR）。《树木年代学》，26卷，115-124页。https://doi.org/10.1016/j.dendro.2008.01.002 2. Kachaev, Alexander (2020), "Compact dataset of dendrochronological data of primary metric characteristics of tree rings of Asia.", Mendeley Data, V1, doi: 10.17632/p9zhpmzgtk.1 翻译：Kachaev, Alexander（2020）。《亚洲树木年轮主要度量特征的树木年代学数据集》。Mendeley数据，V1，doi: 10.17632/p9zhpmzgtk.1 3. Kachaev A. V. (2017) Model for describing the structure of dendroclimatic data. In the collection: Regional problems of remote sensing of the Earth: Materials of the IV international scientific conference. Siberian Federal University, Institute of Space and Information Technologies. p. 120-122. (Russia) 翻译：Kachaev A. V.（2017）。树木气候学数据结构描述模型。见：《地球遥感的区域问题——第四届国际科学会议论文集》。西伯利亚联邦大学空间与信息技术学院，120-122页。（俄罗斯） 4. Kachaev A. V. (2016) NOSQL Approach for Development of Dendroclimatic Data Bank. In the collection: Regional problems of remote sensing of the Earth: Materials of the III International Scientific Conference. p. 89-91. (Russia) 翻译：Kachaev A. V.（2016）。树木气候数据库开发的非关系型数据库（NOSQL）方法。见：《地球遥感的区域问题——第三届国际科学会议论文集》，89-91页。（俄罗斯） 5. Shoudong Zhao, et al. (2019). The International Tree-Ring Data Bank (ITRDB) revisited: Data availability and global ecological representativity. *Journal of Biogeography*, 46(2), 355-368. doi: 10.1111/jbi.13488 翻译：赵守东等（2019）。再探国际树木年轮数据库（ITRDB）：数据可用性与全球生态代表性。《生物地理学杂志》，46卷第2期，355-368页。doi: 10.1111/jbi.13488 6. Zhao, Shoudong et al. (2018), Data from: The International Tree-Ring Data Bank (ITRDB) revisited: data availability and global ecological representativity, Dryad, Dataset, https://doi.org/10.5061/dryad.kh0qh06 翻译：Zhao, Shoudong等（2018）。数据集源自：《再探国际树木年轮数据库（ITRDB）：数据可用性与全球生态代表性》，Dryad数据集，https://doi.org/10.5061/dryad.kh0qh06
