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Bradley Baker

Publications and source records attributed to Bradley Baker.

pyQuARC: Open Source Library for Earth Observation Metadata Quality Assessment

Metadata quality is essential to effective data discovery and has become increasingly vital as more Earth Science data sets become available. The Common Metadata Repository (CMR) hosts metadata describing NASA’s Earth Observation data products, which are archived across 12 Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, conducts metadata quality assessments to ensure that these data products are discoverable, accessible, and usable. To achieve these goals, the ARC team has developed a metadata quality assessment framework to evaluate metadata completeness, correctness, and consistency. ARC uses a combination of manual and automated methods to assess these three components and identify areas of improvement; the team then collaborates with the DAACs to resolve any findings. To streamline this process, ARC is currently developing a host of scripts, known as pyQuARC, to automate metadata quality assessments as much as possible. pyQuARC is an open source library for Earth Observation Metadata Quality Assessment, and the tool utilizes ARC’s metadata quality assessment framework to make basic validation checks, pinpoint inconsistencies between dataset-level (i.e. collection) and file-level (i.e. granule) metadata, and identify opportunities for more descriptive and robust information. Since pyQuARC is also customizable, other users can make modifications as needed, and future metadata standards can also be implemented. Once pyQuARC is fully developed, it will support multiple schema types to serve the broader EOSDIS metadata community. This presentation will provide an overview of pyQuARC and its process of development while showcasing the tool’s valuable features and uses.

Jenny Wood

Enhancing accessibility and usability of Algorithm Theoretical Basis Documents through the Algorithm Publication Tool

Effective communication of scientific theories is crucial for transforming raw instrument data into valuable Earth observation products. The NASA Earth science data community disseminates this knowledge through Algorithm Theoretical Basis Documents (ATBDs). Historically, these documents lacked a standardized format, were designed for human readability rather than machine interpretation, and were challenging to locate due to the absence of a centralized repository. The Algorithm Publication Tool (APT) transforms how ATBD content is presented, simplifying the processes of creating, updating, and locating these documents. APT offers authors the option to use its user-friendly cloud-based interface or standardized templates for ATBD development. The primary advantage of the interface is its capability to manage the entire ATBD creation process within a single environment, ensuring comprehensive tracking of all activities and facilitating user tasks. Conversely, the use of standardized ATBD templates allows users to create documents using familiar tools like Google Docs, Microsoft Word, or Overleaf for LaTeX. APT also provides a centralized repository, enabling easy search and discovery of published ATBDs. This presentation showcases APT's functionalities, illustrates its contributions to advancing open science, and highlights potential benefits for broader community adoption.

Bradley Baker