Expansion of the Geophysical Survey (GS) data standard and open-source tools
Advancement of GS standard and GSPy software for improved functionality and interoperability of geophysical datasets
Geophysical methods are widely used in Earth Science studies to detect differences in below ground physical properties (e.g., rock, sediment, water) in both space and time. Methods vary considerably, leading to an abundance of data types and file formats which can hinder cooperation with the broader science community and long-term usability of data. Geophysical datasets also often require critical auxiliary information (metadata) that describe equipment and data collection details for accurate processing and interpretation. To address these pressing needs, we developed the Geophysical Survey (GS) data standard, based on the NetCDF file format and well-established metadata conventions, and accompanying Python software called GSPy. Here, we propose to expand on the GSPy software to increase the functionality and accessibility of complex geophysical datasets. Advancement of the features and user experience of the GSPy toolbox will expedite adoption of the GS standard and thereby strengthen the USGS capacity for open science.
Advancement of GS standard and GSPy software for improved functionality and interoperability of geophysical datasets
Geophysical methods are widely used in Earth Science studies to detect differences in below ground physical properties (e.g., rock, sediment, water) in both space and time. Methods vary considerably, leading to an abundance of data types and file formats which can hinder cooperation with the broader science community and long-term usability of data. Geophysical datasets also often require critical auxiliary information (metadata) that describe equipment and data collection details for accurate processing and interpretation. To address these pressing needs, we developed the Geophysical Survey (GS) data standard, based on the NetCDF file format and well-established metadata conventions, and accompanying Python software called GSPy. Here, we propose to expand on the GSPy software to increase the functionality and accessibility of complex geophysical datasets. Advancement of the features and user experience of the GSPy toolbox will expedite adoption of the GS standard and thereby strengthen the USGS capacity for open science.