链接生态开放数据(LODE):生态数据共享的新途径

Q4 Agricultural and Biological Sciences Taiwan Journal of Forest Science Pub Date : 2011-12-01 DOI:10.7075/TJFS.201112.0106
Guan-Shuo Mai, Yu-Hwang Wang, Y. Hsia, S. Lu, Chau-Chin Lin
{"title":"链接生态开放数据(LODE):生态数据共享的新途径","authors":"Guan-Shuo Mai, Yu-Hwang Wang, Y. Hsia, S. Lu, Chau-Chin Lin","doi":"10.7075/TJFS.201112.0106","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to report and discuss the use of a linked data approach on existing related databases on forest fires, plant specimens, insect collections, forest dynamics plot censuses, and Taiwanese species checklists. We adopted the linked data approach to connect together data intrinsically related from distributed databases. The approach developed a workflow through 4 steps to integrate and publish human- and machine-readable ecological data as linked open data on the web. Results from our work can be found at the web site http://ecowlim.tfri.gov.tw. We conclude that the linked data approach is a new way to improve and advance ecological data sharing.","PeriodicalId":22180,"journal":{"name":"Taiwan Journal of Forest Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Linked Open Data of Ecology (LODE): A New Approach for Ecological Data Sharing\",\"authors\":\"Guan-Shuo Mai, Yu-Hwang Wang, Y. Hsia, S. Lu, Chau-Chin Lin\",\"doi\":\"10.7075/TJFS.201112.0106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this paper is to report and discuss the use of a linked data approach on existing related databases on forest fires, plant specimens, insect collections, forest dynamics plot censuses, and Taiwanese species checklists. We adopted the linked data approach to connect together data intrinsically related from distributed databases. The approach developed a workflow through 4 steps to integrate and publish human- and machine-readable ecological data as linked open data on the web. Results from our work can be found at the web site http://ecowlim.tfri.gov.tw. We conclude that the linked data approach is a new way to improve and advance ecological data sharing.\",\"PeriodicalId\":22180,\"journal\":{\"name\":\"Taiwan Journal of Forest Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Taiwan Journal of Forest Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7075/TJFS.201112.0106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Taiwan Journal of Forest Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7075/TJFS.201112.0106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 9

摘要

本文的目的是报告并讨论连结数据方法在现有森林火灾、植物标本、昆虫收集、森林动态图普查和台湾物种清单等相关数据库中的使用。我们采用链接数据的方法将分布式数据库中内在相关的数据连接在一起。该方法通过4个步骤开发了一个工作流程,将人类和机器可读的生态数据整合并发布为网络上链接的开放数据。我们的工作结果可在网站http://ecowlim.tfri.gov.tw上找到。我们认为,关联数据方法是改善和推进生态数据共享的新途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Linked Open Data of Ecology (LODE): A New Approach for Ecological Data Sharing
The purpose of this paper is to report and discuss the use of a linked data approach on existing related databases on forest fires, plant specimens, insect collections, forest dynamics plot censuses, and Taiwanese species checklists. We adopted the linked data approach to connect together data intrinsically related from distributed databases. The approach developed a workflow through 4 steps to integrate and publish human- and machine-readable ecological data as linked open data on the web. Results from our work can be found at the web site http://ecowlim.tfri.gov.tw. We conclude that the linked data approach is a new way to improve and advance ecological data sharing.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Taiwan Journal of Forest Science
Taiwan Journal of Forest Science Agricultural and Biological Sciences-Forestry
CiteScore
0.20
自引率
0.00%
发文量
0
期刊介绍: The Taiwan Journal of Forest Science is an academic publication that welcomes contributions from around the world. The journal covers all aspects of forest research, both basic and applied, including Forest Biology and Ecology (tree breeding, silviculture, soils, etc.), Forest Management (watershed management, forest pests and diseases, forest fire, wildlife, recreation, etc.), Biotechnology, and Wood Science. Manuscripts acceptable to the journal include (1) research papers, (2) research notes, (3) review articles, and (4) monographs. A research note differs from a research paper in its scope which is less-comprehensive, yet it contains important information. In other words, a research note offers an innovative perspective or new discovery which is worthy of early disclosure.
期刊最新文献
Pinus sylvestris Can Form Ectomycorrhiza with Phialocephala fortinii Carbon Storage and Density of Forest Ecosystems in Heilongjiang Province, China Building allometric models to estimate above-ground and below-ground biomass of mahogany sapling. Effects of Soil Properties on Restoring Indigenous Plants in Coral Reef Landscapes Response variations of Alnus subcordata (L.), Populus deltoides (Bartr. ex Marsh.), and Taxodium distichum (L.) seedlings to flooding stress.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1