Merge pull request #275 from NASA-IMPACT/dev

pyQuARC DOI creation updates

CHANGELOG.md

@@ -3,6 +3,7 @@
 ## v1.2.5
 - Updated README
 - Updated umm-g schema file
+- Created citation file
 
 ## v1.2.4
 - Updated UMM-C schema file

CITATION.cff

@@ -0,0 +1,39 @@
+cff-version: 1.2.0
+title: "pyQuARC: Open Source Library for Earth Observation Metadata Quality Assessment"
+message: "If you use this software, please cite it as below"
+type: software
+authors:
+  - given-names: Slesa
+    family-names: Adhikari
+    email: slesa.adhikari@uah.edu
+  - given-names: Iksha
+    family-names: Gurung
+    email: iksha.gurung@uah.edu
+  - given-names: Jenny
+    family-names: Wood
+    email: jenny.wood@uah.edu
+  - given-names: Jeanné
+    family-names: le Roux
+    email: jeanne.leroux@uah.edu
+identifiers:
+  - type: doi
+    value: 10.5281/zenodo.10724717
+repository-code: 'https://github.com/NASA-IMPACT/pyQuARC/tree/v1.2.5'
+abstract: >-
+  pyQuARC is designed to read and evaluate Earth observation metadata records hosted within the Common Metadata Repository (CMR), which is a centralized metadata repository for all of NASA's Earth observation data products. The CMR serves as the backend for NASA's Earthdata Search meaning that high-quality metadata helps connect users to the existing data in Earthdata Search. pyQuARC implements the Analysis and Review of CMR (ARC) team's metadata quality assessment framework to provide prioritized recommendations for metadata improvement and optimized search results. pyQuARC makes basic validation checks, pinpoints inconsistencies between dataset-level (i.e. collection) and file-level (i.e. granule) metadata, and identifies opportunities for more descriptive and robust information. It currently supports DIF10 (collection), ECHO10 (collection and granule), UMM-C, and UMM-G metadata standards. As open source software, pyQuARC can be adapted to add customized checks, implement future metadata standards, or support other metadata types.
+keywords:
+  - Metadata
+  - Python
+  - Data Curation
+  - Earth Observation
+  - DAAC
+  - Collection
+  - Granule
+  - GCMD
+  - Quality Assessment
+  - DIF10
+  - ECHO10
+  - UMM-C
+license: Apache-2.0
+version: 1.2.5
+date-released: '2021-08-19'

README.md

@@ -1,7 +1,9 @@
-# pyQuARC
+# pyQuARC 
 
 ### Open Source Library for Earth Observation Metadata Quality Assessment
 
+[![DOI](https://zenodo.org/badge/153786129.svg)](https://zenodo.org/doi/10.5281/zenodo.10724716)
+
 ## Introduction
 
 The pyQuARC (*pronounced "pie-quark"*) library was designed to read and evaluate descriptive metadata used to catalog Earth observation data products and files. This type of metadata focuses and limits attention to important aspects of data, such as the spatial and temporal extent, in a structured manner that can be leveraged by data catalogs and other applications designed to connect users to data. Therefore, poor quality metadata (e.g. inaccurate, incomplete, improperly formatted, inconsistent) can yield subpar results when users search for data. Metadata that inaccurately represents the data it describes risks matching users with data that does not reflect their search criteria and, in the worst-case scenario, can make data impossible to find.