The system for sharing data about lake and catchment is a key point of the digital platform for researching the lake and catchment. Especially, the data collection system plays a fundamental role in the data sharing system. The strategy of integration and collection on lake and catchment data is analyzed firstly. And then, the framework of lake and catchment data collection system and the collection technical process are studied. Data collection system generally consists of following three parts: (1) Data inspection and acceptance. (2) Entity data management. (3) Metadata management. Some problems need to be resolved in the process of data collection, such as, how many key steps should be gone through, what work should be done within every key step, what standards should be abided by, and how to ensure the data quality. The data of lake and catchment can be categorized into metadata and entity data. The data manufacturing divisions should collate the old data with currently applied standards, establish the corresponding metabase and then convert the old database. The converted data then could be submitted for further checking. If the data is acceptable, the divisions could submit the entity data and metadata to the central database for being shared. A submission system is proposed, which consists of one main center and many sub-centers. All of these centers form a tree-like hierarchical framework. The metadata and entity data can be submitted to one of the sub-centers. The application of above framework shows that it is effective.
['Jiangfeng She', 'Kai Xiao', 'Hongdan Jiang', 'Ronghua Ma', 'Jinduo Xu']
Data collection in research of lake and catchment data sharing