Online collaborative geographic experiments have many advantages in communication, resource sharing, and task coordination; thus, they play a vital role in comprehensive geographic problem solving for interdisciplinary experts. In these collaborative experiments, different experts usually possess different knowledge backgrounds and are responsible for specific tasks, making it difficult to fully understand the entire experimental process and implementation details, which may lead to different experimental ideas and actions, thus reducing the efficiency of the experiment. Therefore, it is necessary to record and trace information to help participants reach a consensus on the understanding of the experiment to support collaboration. However, most of the existing tracing strategies focus on the states of geographic experimental data but ignore the different interactions that impact the generation, flow, and use of these data. Limitations remain for existing strategies in terms of providing comprehensive insight into the geographic experiment process and its implementation details, especially when addressing the requirements of process understanding, error localization, and scheme sharing. Therefore, this study presents a strategy for tracing interactions in online collaborative geographic experiments. This strategy focuses on interactions and their types, structures, and dependencies during the geographic experiment process; designs three components for recording interaction information; and uses corresponding extraction methods to trace interaction information. To verify the feasibility of this strategy, it was implemented in an online prototype system, and a case study of aboveground forest biomass prediction under climate change was conducted with the prototype system. The results indicate that the proposed strategy can help enhance collaboration among different participants, thus effectively improving the performance of collaborative geographic experiments.

中文翻译：

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在线协作地理实验中追踪交互的策略


在线协同地理实验在沟通、资源共享、任务协调等方面具有诸多优势；因此，它们在跨学科专家解决综合地理问题方面发挥着至关重要的作用。在这些协作实验中，不同的专家通常拥有不同的知识背景并负责特定的任务，难以充分理解整个实验过程和实施细节，可能导致实验思路和行动不同，从而降低实验效率。因此，有必要记录和追踪信息，帮助参与者对实验的理解达成共识，以支持协作。然而，大多数现有的追踪策略都关注地理实验数据的状态，而忽略了影响这些数据的生成、流动和使用的不同相互作用。现有策略在提供对地理实验过程及其实施细节的全面洞察方面仍然存在局限性，特别是在满足过程理解、错误定位和方案共享的要求时。因此，本研究提出了一种追踪在线协作地理实验中相互作用的策略。该策略重点关注地理实验过程中的相互作用及其类型、结构和依赖性；设计了三个记录交互信息的组件；并使用相应的提取方法来追踪交互信息。为了验证该策略的可行性，在在线原型系统中进行了实现，并利用该原型系统进行了气候变化下地上森林生物量预测的案例研究。 结果表明，所提出的策略有助于增强不同参与者之间的协作，从而有效提高协作地理实验的性能。