SCOTT PECKHAM

and 5 more

This repository creates a GUI (graphical user interface) for the BALTO (Brokered Alignment of Long-Tail Observations) project. BALTO is funded by the NSF EarthCube program. The GUI aims to provide a simplified and customizable method for users to access data sets of interest on servers that support the OpenDAP data access protocol. This interactive GUI runs within a Jupyter notebook and uses the Python packages: ipywidgets (for widget controls), ipyleaflet (for interactive maps) and pydap (an OpenDAP client). The Python source code to create the GUI and to process events is in a module called balto_gui.py that must be found in the same directory as this Jupyter notebook. Python source code for visualization of downloaded data is given in a module called balto_plot.py. This GUI consists of mulitiple panels, and supports both a tab-style and an accordion-style, which allows you to switch between GUI panels without scrolling in the notebook. You can run the notebook in a browser window without installing anything on your computer, using something called Binder. Look for the Binder icon below and a link labeled “Launch Binder”. This sets up a server in the cloud that has all the required dependencies and lets you run the notebook on that server. (Sometimes this takes a while, however.) To run this Jupyter notebook without Binder, it is recommended to install Python 3.7 from an Anaconda distribution and to then create a conda environment called balto. Simple instructions for how to create a conda environment and install the software are given in Appendix 1 of version 2 (v2) of the notebook.

D. Sarah Stamps

and 10 more

The EarthCube BALTO broker (Brokered Alignment of Long-Tail Observations) provides streamlined access to both long-tail and big data using Web Services through several distinct mechanisms. First, we updated the OPeNDAP framework Hyrax, software that serves big data from USGS, NASA, and other sources, with a BALTO extension that tags dataset landing pages with JSON-LD encoding automatically. Therefore, the big data made available through Hyrax are now searchable via EarthCube GeoCODES (formerly P418) and Google Dataset Search. The BALTO broker extension to Hyrax makes thousands of datasets easily searchable and accessible. Second, we focused our efforts on a geodynamics use-case aimed at advancing our understanding of continental rifting processes through the use of an NSF mantle convection code called ASPECT. By addressing this use-case, we implemented a web services brokering capability in ASPECT that allows for remotely accessing datasets via a URL defined in an ASPECT parameter file. Third, through another use-case in ASPECT aimed at testing hypotheses involving global mantle flow, we developed a brokering mechanism for a “plug-in” that accesses NetCDF seismic tomography data from the NSF seismology facility IRIS, then transforms it into the format needed by ASPECT to run global mantle flow models constrained by seismic tomography. Fourth, we demonstrate methods to allow any scientist or citizen scientist to make their in-situ IoT based sensor data collection efforts available to the world. Finally, we are developing a Jupyter Notebook with a GUI that allows for users to search Hyrax servers for big datasets and long-tail data. These cyberinfrastructure developments comprise the entire EarthCube BALTO brokering capabilities.