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General Server for Rapid Publishing of OGC-Compliant Earth Science Data Products
  • Mattheus Ueckermann,
  • Jerry Bieszczad
Mattheus Ueckermann
Creare LLC

Corresponding Author:[email protected]

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Jerry Bieszczad
Creare LLC
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Abstract

To make timely decisions for weather -and climate-related disasters and vulnerabilities, decision makers need current information that can be readily shared and communicated to stakeholders. To date, geospatial data is distributed using monolithic storage architectures and formats best suited for traditional research applications. Thus, everyday decision-makers face significant “barriers to entry” when trying to access, explore, and modify vast historical archives and real time data feeds. To address this need, we are developing a server architecture for rapidly creating and publishing data products. Privileged users can rapidly create or change products by operating on another product or combining multiple disparate data sources together. Users can then consume these new products using OGC-compliant WMS/WCS clients such as ArcGIS, QGIS, or Leaflet. This enables decision makers to effectively communicate with stakeholders using customized maps. Moreover, this capability enables products to be rapidly updated in cases where timely information is important. Our server architecture is containerized, making it easy to deploy on various architectures including serverless cloud resources. It is implemented in Python, leverages the plug-and-play data wrangling capabilities of the PODPAC library, and uses a custom library for serving OGC-compliant data. The result is an easy-to-use architecture for rapidly publishing custom geospatial products that exploit vast earth science data resources. We will demonstrate our server capabilities by showing how privileged users can build a set of products that are computed on-demand starting from a fresh server. Using Jupyter Lab notebooks, we will create products that modify single data sources as well as products that combine multiple disparate sources. We will then show how users can consume these products using OGC-compliant clients. Next, we will detail our cloud-based, serverless deployment of this technology using Amazon Web Services. Finally, we will discuss the advantages of our approach along with any caveats. Enabling everyday decision makers to rapidly create and share geospatial data will revolutionize their productivity and effectiveness for assessing and remediating weather- and climate-related vulnerabilities and disasters.