Getzlaff, Klaus , Schirnick, Carsten , Scheinert, Markus , Faber, Claas , Weng, Franziska, Paglialonga, Lisa , Mehrtens, Hela and Lehmann, Andreas (2021) THREDDS Data Server a simplified way to discover and access scientific data at GEOMAR. [Talk] In: 5. Data Science Symposium 2021. , 22.01.2021, Bremen, Germany .

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Abstract

One of today‘s challenge is the effective access to scientific data either within research groups or across different institutions to allow and increase the reusability of the data. While large operational modeling and service centers have enabled query and access to data via common web services, this is often not the case for smaller research groups. Especially the maintenance of the infrastructure and simple workflows to make the data available is a common challenge for scientists and data management.

Here we would like to introduce the updated THREDDS Data Server (TDS) available at GEOMAR to provide, query, access and explore scientific data in netcdf format. This includes a simple and well documented workflow with step-by-step guidelines to provide data to the TDS system. This workflow aims to maximize the use of semi-automated processes, such as data integrity including standard metadata, checksums and persistent identifiers. By doing so, this workflow minimizes extra workload for persons involved in the data provision procedure such as scientists, data stewards and data managers but maximizes data reusibility under the FAIR principles.

The TDS is a system developed and maintained by Unidata,a division of the University Corporation for Atmospheric Research (UCAR). The aim of the TDS is 1) to make it simple to enable web service access to existing output files, 2) using free technologies that are easy to deploy and configure, and 3) provide standardized, service-based tools that work in existing research environments. The TDS provides catalog, metadata, and data access services for scientific datasets with remote data access protocols including OPeNDAP, OGC WCS, OGC WMS, and HTTPS.

These standardized services enable reusability and increase the visibility of scientific datasets. We will show examples using viewer technologies to access datasets or directly explore these within common development environments such as Python or MATLAB.

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