Tomasz Miksa and Bernhard Gößwein presented their paper on Data identification and process monitoring for reproducible earth observation research at the 15th IEEE eScience conference in San Diego.
Earth observation researchers use specialised computing services for satellite image processing offered by various data backends. The source of data is often the same, for example Sentinel-2 satellites operated by Copernicus, but the way how data is pre-processed, corrected, updated, and later analysed may differ among the backends. Backends often lack mechanisms for data versioning, for example, data corrections are not tracked. Furthermore, an evolving software stack used for data processing remains a black box to researchers. Researchers have no means to identify why executions of the same code deliver different results. This hinders reproducibility of earth observation experiments. In this paper, we present how infrastructure of existing earth observation data backends can be modified to support reproducibility. The proposed extensions are based on recommendations of the Research Data Alliance regarding data identification and the VFramework for automated process provenance documentation. We implemented these extensions at the Earth Observation Data Centre, a partner in the openEO consortium. We evaluated the solution on a variety of usage scenarios, providing also performance and storage measures to evaluate the impact of the modifications. The results indicate reproducibility can be supported with minimal performance and storage overhead.