Advancing the Geophysical Survey (GS) data standard and GSPy toolbox
Improve geophysical data management through advancing GS standardization by worked examples, improved functionality and engagement
Geophysical surveys are widely used across Earth Science disciplines to measure variations in belowground physical properties (for example, rock, sediment, water). There exist numerous types of geophysical methods, commercial instruments, modes of collection, and system configurations leading to an abundance of data types and file formats. Without a common data standard, the usability of geophysical data is critically weakened, hindering cooperation and long-term impact. Therefore, we have developed a new open community standard for geophysical data and metadata: the Geophysical Survey (GS) data standard, along with a supporting Python package (GSPy). Usage of the GS standard is growing; however, more work is needed to obtain widespread adoption. Here, we propose to improve accessibility by publishing worked examples, building a catalog to support future web tools, and promoting awareness through conferences and user-support. This work strengthens the USGS capacity for open-science, promotes skills- building, and benefits both producers and consumers of geophysical data.
GSPy: A new toolbox and data standard for Geophysical Datasets GSPy: A new toolbox and data standard for Geophysical Datasets
GSpy: Geophysical Data Standard in Python GSpy: Geophysical Data Standard in Python
Improve geophysical data management through advancing GS standardization by worked examples, improved functionality and engagement
Geophysical surveys are widely used across Earth Science disciplines to measure variations in belowground physical properties (for example, rock, sediment, water). There exist numerous types of geophysical methods, commercial instruments, modes of collection, and system configurations leading to an abundance of data types and file formats. Without a common data standard, the usability of geophysical data is critically weakened, hindering cooperation and long-term impact. Therefore, we have developed a new open community standard for geophysical data and metadata: the Geophysical Survey (GS) data standard, along with a supporting Python package (GSPy). Usage of the GS standard is growing; however, more work is needed to obtain widespread adoption. Here, we propose to improve accessibility by publishing worked examples, building a catalog to support future web tools, and promoting awareness through conferences and user-support. This work strengthens the USGS capacity for open-science, promotes skills- building, and benefits both producers and consumers of geophysical data.