Catalysing virtual collaboration: The experience of the remote TIES working groups

IF 1.5 3区环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES

Environmetrics Pub Date : 2024-05-23 DOI:10.1002/env.2855

M. Meis, M. Pirani, C. Euan, S. Castruccio, S. Simmons, J.R. Stroud, M. Blangiardo, C.K. Wikle, M. Wheeler, E. Naumova, L. Bravo, C. Miller, Y. Gel

{"title":"Catalysing virtual collaboration: The experience of the remote TIES working groups","authors":"M. Meis, M. Pirani, C. Euan, S. Castruccio, S. Simmons, J.R. Stroud, M. Blangiardo, C.K. Wikle, M. Wheeler, E. Naumova, L. Bravo, C. Miller, Y. Gel","doi":"10.1002/env.2855","DOIUrl":null,"url":null,"abstract":"<p>During the COVID-19 pandemic, the idea of collaboration and scientific exchange between members of the scientific community was enhanced by technology. Virtual meetings and work platforms have become common resources to continue generating research, partially replacing instances of joint in-person work before, during or after a conference. The idea of teleworking played a fundamental role in remote collaboration groups within The International Statistical Society (TIES), a community of interdisciplinary scientists such as statisticians, mathematicians, meteorologists, and biologists, among others working on quantitative methods to enhance solutions to environmental problems. In 2021 the Society launched three working groups with the aim of improving networking across the Society's members and develop creative collaboration, while advancing statistical and computational methods motivated by real-world driven applications in environmental research. Here, we provide insights from this virtual collaborative initiative.</p>","PeriodicalId":50512,"journal":{"name":"Environmetrics","volume":"35 6","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmetrics","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/env.2855","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}

引用次数: 0

Abstract

During the COVID-19 pandemic, the idea of collaboration and scientific exchange between members of the scientific community was enhanced by technology. Virtual meetings and work platforms have become common resources to continue generating research, partially replacing instances of joint in-person work before, during or after a conference. The idea of teleworking played a fundamental role in remote collaboration groups within The International Statistical Society (TIES), a community of interdisciplinary scientists such as statisticians, mathematicians, meteorologists, and biologists, among others working on quantitative methods to enhance solutions to environmental problems. In 2021 the Society launched three working groups with the aim of improving networking across the Society's members and develop creative collaboration, while advancing statistical and computational methods motivated by real-world driven applications in environmental research. Here, we provide insights from this virtual collaborative initiative.

查看原文本刊更多论文

促进虚拟协作：远程 TIES 工作组的经验

在 COVID-19 大流行期间，科学界成员之间的合作和科学交流理念因技术而得到了加强。虚拟会议和工作平台已成为继续开展研究的常用资源，部分取代了会前、会中或会后的现场联合工作。国际统计学会（TIES）是一个由统计学家、数学家、气象学家和生物学家等跨学科科学家组成的团体，其中包括研究定量方法以提高环境问题解决方案的科学家。2021 年，学会成立了三个工作组，旨在改善学会成员之间的网络联系，发展创造性合作，同时推进以环境研究中的实际应用为动力的统计和计算方法。在此，我们将从这一虚拟合作倡议中提出自己的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Environmetrics 环境科学-环境科学

CiteScore

2.90

自引率

17.60%

发文量

审稿时长

18-36 weeks

期刊介绍： Environmetrics, the official journal of The International Environmetrics Society (TIES), an Association of the International Statistical Institute, is devoted to the dissemination of high-quality quantitative research in the environmental sciences. The journal welcomes pertinent and innovative submissions from quantitative disciplines developing new statistical and mathematical techniques, methods, and theories that solve modern environmental problems. Articles must proffer substantive, new statistical or mathematical advances to answer important scientific questions in the environmental sciences, or must develop novel or enhanced statistical methodology with clear applications to environmental science. New methods should be illustrated with recent environmental data.