Seamless Access to Long-Tail and Big Data in Earth and Space Science via the EarthCube Brokering Cyberinfrastructure BALTO

Abstract:

The EarthCube brokering cyberinfrastructure BALTO (Brokered Alignment of Long-Tail Observations) provides streamlined access to both long-tail and big data using Web Services. BALTO consists of several distinct brokering mechanisms that we have developed since the project’s inception in 2016. First, we created an extension for the OPeNDAP framework Hyrax, which is software that serves big data from USGS, NASA, and numerous other sources. The BALTO-Hyrax extension makes the big data findable and searchable through Google Dataset Search and EarthCube GeoCODES by automatically tagging dataset landing pages with JSON-LD encoding. Second, we implemented a Web Service brokering capability into the NSF mantle convection code ASPECT such that geodynamic modelers can remotely access initial condition datasets with URLs. Third, also in ASPECT, we developed a brokering mechanism for accessing and transforming NetCDF seismic tomography data so users can perform global mantle convection simulations with a wide range of input data. Fourth, we develop methods to allow any career or citizen scientist to make their in-situ IoT based sensor data collection efforts available to the world, and extend the access of these data for IA/ML analysis. Finally, we developed a Jupyter Notebook with a GUI that allows for users to search Hyrax servers for big datasets and long-tail data. These developments comprise the entire EarthCube brokering cyberinfrastructure BALTO.