This paper describes and discusses our vision to develop and reason about best practices and novel ways of curating data-centric geosciences knowledge (data, experiments, models, methods, conclusions, and interpretations). This knowledge is produced from applying statistical modelling, Machine Learning, and modern data analytics methods on geo-data collections. The problems address open methodological questions in model building, models' assessment, prediction, and forecasting workflows.
翻译:本文件介绍和讨论了我们关于发展和认识最佳做法和确定以数据为中心的地球科学知识的新方式(数据、实验、模型、方法、结论和解释)的愿景,这种知识来自应用统计建模、机器学习和地理数据收集现代数据分析方法。 这些问题解决了建模、模型评估、预测和预测工作流程中公开的方法问题。