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Expand Up @@ -14,7 +14,7 @@ Given the importance of high quality metadata, it is necessary that metadata be

pyQuARC was specifically designed to assess metadata in NASA’s [Common Metadata Repository (CMR)](https://earthdata.nasa.gov/eosdis/science-system-description/eosdis-components), which is a centralized metadata repository for all of NASA’s Earth observation data products. In addition to NASA’s ~9,000 data products, the CMR also holds metadata for over 40,000 additional Earth observation data products submitted by external data partners. The CMR serves as the backend for NASA’s Earthdata Search (search.earthdata.nasa.gov) and is also the authoritative metadata source for NASA’s [Earth Observing System Data and Information System (EOSDIS).](https://earthdata.nasa.gov/eosdis)

pyQuARC was developed by a group called the [Analysis and Review of the CMR (ARC)](https://earthdata.nasa.gov/esds/impact/arc) team. The ARC team conducts quality assessments of NASA’s metadata records in the CMR, identifies opportunities for improvement in the metadata records, and collaborates with the data archive centers to resolve any identified issues. ARC has developed a [metadata quality assessment framework](http://doi.org/10.5334/dsj-2021-017) which specifies a common set of assessment criteria. These criteria focus on correctness, completeness, and consistency with the goal of making data more discoverable, accessible, and usable. The ARC metadata quality assessment framework is the basis for the metadata checks that have been incorporated into pyQuARC base package. Specific quality criteria for each CMR metadata element is documented in the following wiki:
pyQuARC was developed by a group called the [Analysis and Review of the CMR (ARC)](https://earthdata.nasa.gov/esds/impact/arc) team. The ARC team conducted quality assessments of NASA’s metadata records in the CMR, identified opportunities for improvement in the metadata records, and collaborated with the data archive centers to resolve any identified issues. ARC developed a [metadata quality assessment framework](http://doi.org/10.5334/dsj-2021-017) which specifies a common set of assessment criteria. These criteria focus on correctness, completeness, and consistency with the goal of making data more discoverable, accessible, and usable. The ARC metadata quality assessment framework is the basis for the metadata checks that have been incorporated into pyQuARC base package. Specific quality criteria for each CMR metadata element is documented in the following wiki:
[https://wiki.earthdata.nasa.gov/display/CMR/CMR+Metadata+Best+Practices%3A+Landing+Page](https://wiki.earthdata.nasa.gov/display/CMR/CMR+Metadata+Best+Practices%3A+Landing+Page)

There is an “ARC Metadata QA/QC” section on the wiki page for each metadata element that lists quality criteria categorized by level of [priority. Priority categories](https://wiki.earthdata.nasa.gov/display/CMR/ARC+Priority+Matrix) are designated as high (red), medium (yellow), or low (blue), and are intended to communicate the importance of meeting the specified criteria.
Expand All @@ -30,9 +30,9 @@ The CMR is designed around its own metadata standard called the [Unified Metadat
* UMM-T (Tool metadata)


pyQuARC supports DIF10 (collection only), ECHO10 (collection and granule), UMM-C, and UMM-G standards. At this time, there are no plans to add ISO 19115 or UMM-S/T specific checks. **Note that pyQuARC development is still underway, so further enhancements and revisions are planned.**
pyQuARC supports DIF10 (collection only), ECHO10 (collection and granule), UMM-C, and UMM-G standards.

**For inquiries, please email: sheyenne.kirkland@uah.edu**
**For inquiries, please email: ESDIS POC**

## pyQuARC as a Service (QuARC)

Expand Down Expand Up @@ -62,7 +62,6 @@ pyQuARC is designed to be customizable. Output messages can be modified using th

There is also the opportunity for more sophisticated customization. New QA rules can be added and existing QA rules can be edited or removed. Support for new metadata standards can be added as well. Further details on how to customize pyQuARC will be provided in the technical user’s guide below.

While the pyQuARC base package is currently managed by the ARC team, the long term goal is for it to be owned and governed by the broader EOSDIS metadata community.

## Install/User’s Guide
### Running the program
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