On the Design and Implementation of Easy Access to External Spatiotemporal Datasets in NFDI





Spatiotemporal data access, Workflow platform, Geo Engine


Across many scientific domains, the ability to process large amounts of heterogeneous spatiotemporal data from various sources is crucial for solving challenging research questions. For example, in NFDI4Biodiversity, researchers need to combine observation data with satellite images to correlate the loss of biodiversity with climate change variables. In general, large data sets are not available on the system (called consumer) where the processing is performed, but first have to be retrieved from one or multiple external systems (called providers) that offer a corresponding service. Moreover, a consumer is often unaware of the datasets the providers offer. Ideally, a provider follows FAIR principles and thus supports mechanisms to greatly simplify the data exchange. However, in practice, there are multiple providers with valuable datasets that are not as FAIR as desired or lack spatiotemporal-specific support for data exchange. Instead of improving each potential provider at the source, we propose an intermediary spatiotemporal data exchange layer (SDExL) that helps simplify data exchange so that domain experts easily gain access to valuable data with little technical know-how.


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How to Cite

Beilschmidt, C., Brandenstein, D., Drönner, J., Glombiewski, N., Mattig, M., & Seeger, B. (2023). On the Design and Implementation of Easy Access to External Spatiotemporal Datasets in NFDI. Proceedings of the Conference on Research Data Infrastructure , 1. https://doi.org/10.52825/cordi.v1i.360
Received 2023-04-26
Accepted 2023-06-29
Published 2023-09-07

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