A strategy for tracing interactions in online collaborative geographic experiments

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.