Specht Alison, Stall Shelley, Machicao Jeaneth, Catry Thibault, Chaumont Marc, David Romain, Devillers Rodolphe, Edmunds Rorie, Jarry Robin, Mabile Laurence, Miyairi Nobuko, O'Brien Margaret, Correa Pedro Pizzigatti, Santos Solange, Subsol Gérard, Wyborn Lesley
Terrestrial Ecosystem Research Network, The University of Queensland, Brisbane, Australia.
American Geophysical Union (AGU), Washington, DC, United States of America.
PLoS One. 2024 Dec 5;19(12):e0311967. doi: 10.1371/journal.pone.0311967. eCollection 2024.
Environmental challenges are rarely confined to national, disciplinary, or linguistic domains. Convergent solutions require international collaboration and equitable access to new technologies and practices. The ability of international, multidisciplinary and multilingual research teams to work effectively can be challenging. A major impediment to innovation in diverse teams often stems from different understandings of the terminology used. These can vary greatly according to the cultural and disciplinary backgrounds of the team members. In this paper we take an empirical approach to examine sources of terminological confusion and their effect in a technically innovative, multidisciplinary, multinational, and multilingual research project, adhering to Open Science principles. We use guided reflection of participant experience in two contrasting teams-one applying Deep Learning (Artificial Intelligence) techniques, the other developing guidance for Open Science practices-to identify and classify the terminological obstacles encountered and reflect on their impact. Several types of terminological incongruities were identified, including fuzziness in language, disciplinary differences and multiple terms for a single meaning. A novel or technical term did not always exist in all domains, or if known, was not fully understood or adopted. Practical matters of international data collection and comparison included an unanticipated need to incorporate different types of data labels from country to country, authority to authority. Sometimes these incongruities could be solved quickly, sometimes they stopped the workflow. Active collaboration and mutual trust across the team enhanced workflows, as incompatibilities were resolved more speedily than otherwise. Based on the research experience described in this paper, we make six recommendations accompanied by suggestions for their implementation to improve the success of similar multinational, multilingual and multidisciplinary projects. These recommendations are conceptual drawing on a singular experience and remain to be sources for discussion and testing by others embarking on their research journey.
环境挑战很少局限于国家、学科或语言领域。趋同的解决方案需要国际合作以及公平获取新技术和新实践。国际、多学科和多语言研究团队有效开展工作的能力可能具有挑战性。不同团队创新的一个主要障碍往往源于对所用术语的不同理解。这些理解可能因团队成员的文化和学科背景而有很大差异。在本文中，我们采用实证方法，遵循开放科学原则，研究一个技术创新、多学科、跨国和多语言研究项目中的术语混淆来源及其影响。我们通过对两个形成对比的团队中参与者的经验进行引导式反思——一个团队应用深度学习（人工智能）技术，另一个团队制定开放科学实践指南——来识别和分类所遇到的术语障碍，并反思其影响。识别出了几种类型的术语不一致情况，包括语言的模糊性、学科差异以及同一含义有多个术语。一个新颖或专业的术语并非在所有领域都存在，或者即便已知，也未被充分理解或采用。国际数据收集和比较的实际问题包括意外需要纳入不同国家、不同权威机构的不同类型数据标签。有时这些不一致情况可以迅速解决，有时则会导致工作流程中断。团队内部积极的合作和相互信任促进了工作流程，因为不相容问题比其他情况得到了更迅速的解决。基于本文所述的研究经验，我们提出六项建议，并附上实施建议，以提高类似跨国、多语言和多学科项目的成功率。这些建议是基于单一经验得出的概念，有待其他踏上研究征程的人进行讨论和检验。
