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An approach for managing specimen-sample-taxon-trait data from the 27 projects of the DFG priority program 1991 ‘Taxon-Omics’

An approach for managing specimen-sample-taxon-trait data from the 27 projects of the DFG priority program 1991 ‘Taxon-Omics’
管理来自 DFG 优先计划 1991“Taxon-Omics” 27 个项目的标本-样本-分类群-性状数据的方法
批准号:
410254097
负责人:
Professor Dr. Miguel Vences, since 10/2020
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Priority Programmes
财政年份:
2018
资助国家:
德国
项目状态:
已结题
起止时间:
2017-12-31 至 2023-12-31

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中文摘要
翻译
在过去的10年里,分类学发生了重大转变,因为它转向了基于DNA的数字化数据,这些数据可以很容易地共享。这为合作和回答以前无法解决的问题开辟了新的途径。认识到这一点,德国研究基金会决定资助DFG-SPP 1991年“Taxon-Omics--发现和命名生物多样性的新方法”下的27个单独项目。11个项目关注动物,8个关注植物,5个关注微生物,3个关注真菌。我们在此提交博士后和中场科学数据馆长的附加请求,以实施一种机制,通过该机制,27个项目中的每个项目都可以立即开始在符合DFG的GFBio数据基础设施的工作环境中存储与标本、样本、特征或分类学相关的数据。我们的方法将依赖于数字对象识别符(DOI)和具有图形用户界面(GUI)的识别符注册表,该注册表将建立在用于管理与样本和分类单元相关的、分类单元组学和特征数据的现有解决方案的基础上,目标是在GBIF和GFBio平台上免费提供数据。作为第二个目标,我们将鼓励私人投资机构提供合适的数据,以测试使用机器学习方法的高通量物种划界算法。这一项目将极大地促进1991年战略规划项目之间的联网,并鼓励私营部门开始以一种便于今后多用途再利用的形式存档数据。
英文摘要
Over the past 10 years, taxonomy has undergone a major shift because of its move towards DNA-based and digitized data, which can readily be shared. This has opened new avenues for collaboration and the ability to answer questions that could not be tackled before. In recognition of this, the German Research Foundation decided to fund 27 individual projects under the umbrella of DFG-SPP 1991 on “Taxon-Omics – new approaches for discovering and naming biodiversity.” Eleven projects focus on animals, eight on plants, five on microorganisms, and three on fungi. We are here submitting an add-on request for a postdoc and a halftime scientific data curator to implement a mechanism by which each of 27 projects could immediately start depositing data linked to specimens, samples, traits, or taxonomies in a working environment compliant to the DFG’s GFBio data infrastructure. Our approach will rely on Digital Object Identifiers (DOIs) and an identifier registry with a graphic user interface (GUI) that will build on existing solutions for managing sample- and taxon-related, taxon-omics and trait data, with the goal of making data freely available on GBIF and GFBio platforms. As a secondary objective, we will encourage PIs to contribute suitable data for testing a high-throughput species delimitation algorithm using machine-learning approaches. This project will strongly contribute to an increased networking among SPP 1991 projects and encourage PIs to start archiving data in a form that will facilitate future multi-purpose reuse.
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