GSPY- A GEOPHYSICAL DATA STANDARD AND SOFTWARE STOOLS TO SUPPORT OPEN SCIENCE

Open science relies on data that are readily accessible by diverse end-users. The long-term usability and impact of high-value geophysical datasets, in particular airborne geophysical surveys, is limited by the lack of an open community data standard. Geophysical data are often stored in proprietary or structured ASCII formats with no widely adopted standards, and with critical metadata in separate files or reports. Here, we describe the Geophysical Survey (GS) data standard that builds on the established NetCDF Climate and Forecast conventions. Initially implemented for airborne geophysical surveys, including electromagnetic, magnetic, and radiometric data, the GS standard can also accommodate many other data types. The GS standard uses a hierarchical structure, with a root ‘Survey’ group containing basic metadata about the dataset and coordinate reference system information. Beneath the survey group, multiple datasets can be attached as two different group types: ‘Tabular’ data contain irregular samples in spreadsheet-style formats, with rows for different data locations and variables stored in columns. ‘Raster’ data contain data on regular grids such as two-dimensional maps or three-dimensional data volumes. All variables have dimensions, coordinates, and other metadata attributes attached in the NetCDF file.

We also developed GSPy, an open-source Python toolbox that implements the GS data standard and helps users import datasets into the GS data structure. Tabular and Raster input data are imported with companion JSON metadata files to create self-describing datasets within an Xarray structure, which can then be saved as NetCDF. GSPy can also be used to visualize or manipulate data and to export into different data formats. Recognizing that not all users are familiar with working directly in Python, we also developed GSExplore, a stand-alone Python executable. GSExplore reads a GS-structured NetCDF file and allows users to interrogate its contents through a graphical user interface, and export contents to more common data formats such as CSV or GeoTIFF. Future development will increase functionality for different types of geophysical surveys and file formats, add tools that enhance the visibility and usability of geophysical datasets, and improve interoperability with other software packages.