Folders: ROOT > ScienceBase Catalog > Community for Data Integration (CDI) > CDI Projects Fiscal Year 2016 > Developing a USGS Legacy Data Inventory to Preserve and Release Historical USGS Data > Magnetotelluric Data from the San Andreas Fault, Parkfield CA, 1990 ( Show all descendants )
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ROOT _ScienceBase Catalog __Community for Data Integration (CDI) ___CDI Projects Fiscal Year 2016 ____Developing a USGS Legacy Data Inventory to Preserve and Release Historical USGS Data _____Magnetotelluric Data from the San Andreas Fault, Parkfield CA, 1990 Filters
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The original time series and cross power data were stored in Binary format on 3.5" disks until further conversion was needed. To convert the time series and cross power data to a format that can be used for modeling, the original binary files were converted to ASCII format using Basic 4.0 code and associated subroutines (see Magnetotelluric_Original-Code_Binary-to-Ascii.txt and Magnetotelluric_Original-Code_Binary-to-Ascii-Subroutines.txt attached to the binary data ScienceBase item). The DaR project used these converted ASCII format files to create the EDI format files included in this data release. The binary data are considered the original data for the magnetotelluric survey, therefore, they are provided with...
The EDI time series and cross power data were converted from ASCII format using Python-based software developed for this preservation project. The data in EDI format can use magnetotelluric interpretation software to produce models of the resistivity of the measured environment. The metadata in the Info section of the EDI files can be used to convert data to SPUD format, another format used for modelling (Wight, 1988).
The ASCII data included in this data release are the intermediary files between the original binary and final EDI formatted files. These ASCII formatted time series and cross power files are what the DaR project acquired and converted into EDI format for this data release using open-source software developed by the DaR project team (Wight, D.E., 1988). The Python code, supplemental resources, and associated readme are available as a USGS software release (https://doi.org/10.5066/F71Z43P9).
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