nasa/opera-sds
Jan 2025 – Sep 2025
6 Months active
Languages Used
PythonCSSHTMLJavaScriptYAMLMarkdown
Technical Skills
API IntegrationCode RefactoringCommand-line InterfaceData ProcessingData VisualizationGeospatial Data Handling
Aaron Roth
PROFILE
Aaron Roth
Aaron Roth developed a suite of data analysis and visualization tools for the nasa/opera-sds repository, focusing on geospatial product monitoring and latency metrics. He engineered Python scripts and JavaScript-based web visualizations to automate data retrieval, process large geospatial datasets, and generate interactive dashboards using technologies like Leaflet and GitHub Actions. His work included implementing outlier filtering for latency graphs, automating daily data queries, and refining CI/CD pipelines for reliable deployment. By integrating AWS S3, API querying, and robust documentation, Aaron improved monitoring accuracy and operational efficiency. The solutions demonstrated depth in data processing, automation, and maintainable front-end development.
Overall Statistics
Feature vs Bugs
73%Features
Repository Contributions
23Total
Bugs
4
Commits
23
Features
11
Lines of code
1,563
Activity Months6
Your Network
46 people
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 (nasa/opera-sds): Delivered Latency Graph Outlier Filtering to improve monitoring signal quality and reliability. Implemented an ignore_outliers flow that omits extreme latency values from graphs, with granular controls including limit_outliers in trigger_latency_graphs, an optional limit on parse_input_granules, and conditional display of max values in histogram plots. Change history centers on a focused commit that implements the ignore outliers path.
1 Commits • 1 Features
Sep 1, 2025September 2025 (nasa/opera-sds): Delivered Latency Graph Outlier Filtering to improve monitoring signal quality and reliability. Implemented an ignore_outliers flow that omits extreme latency values from graphs, with granular controls including limit_outliers in trigger_latency_graphs, an optional limit on parse_input_granules, and conditional display of max values in histogram plots. Change history centers on a focused commit that implements the ignore outliers path.
September 2025
June 2025
5 Commits • 3 Features
Jun 1, 2025June 2025 performance summary for nasa/opera-sds focusing on latency data analysis improvements, automation, and documentation enhancements to strengthen monitoring accuracy and operational efficiency. Key highlights: - Delivered latency data analysis improvements with a revised 3-month sensing window and 2-week revision window for OPERA SDS latency analysis, enabling more representative trend insights. - Implemented OPERA Daily Latency Query automation via a GitHub Actions workflow to run daily latency queries, generate a latency graph, and automatically commit/push the visualization back to the repo. - Enhanced latency visualization documentation by updating the README with the visualization image and fixing the image path to ensure documentation points to the correct monitoring visualization. - Fixed latency visualization y-axis baseline by starting at 0 for two plots to prevent misleading scales and improve readability. Business value and impact: - More reliable latency insights and dashboards with improved data coverage. - Reduced manual effort through automation and faster feedback loops. - Clearer documentation that reduces onboarding time and supports consistent interpretation of latency metrics. Technologies/skills demonstrated: - GitHub Actions and CI/CD automation - Data visualization and metrics interpretation - Version control, documentation maintenance, and commit hygiene - Data range configuration and visualization quality improvements
June 2025
5 Commits • 3 Features
Jun 1, 2025June 2025 performance summary for nasa/opera-sds focusing on latency data analysis improvements, automation, and documentation enhancements to strengthen monitoring accuracy and operational efficiency. Key highlights: - Delivered latency data analysis improvements with a revised 3-month sensing window and 2-week revision window for OPERA SDS latency analysis, enabling more representative trend insights. - Implemented OPERA Daily Latency Query automation via a GitHub Actions workflow to run daily latency queries, generate a latency graph, and automatically commit/push the visualization back to the repo. - Enhanced latency visualization documentation by updating the README with the visualization image and fixing the image path to ensure documentation points to the correct monitoring visualization. - Fixed latency visualization y-axis baseline by starting at 0 for two plots to prevent misleading scales and improve readability. Business value and impact: - More reliable latency insights and dashboards with improved data coverage. - Reduced manual effort through automation and faster feedback loops. - Clearer documentation that reduces onboarding time and supports consistent interpretation of latency metrics. Technologies/skills demonstrated: - GitHub Actions and CI/CD automation - Data visualization and metrics interpretation - Version control, documentation maintenance, and commit hygiene - Data range configuration and visualization quality improvements
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for nasa/opera-sds: Delivered a Python-based OPERA Data Latency Analysis and Visualization Script that queries CMR for granule metadata, computes key latency metrics, and generates histogram plots to visualize data timeliness. The implementation includes test scaffolding with hardcoded dates to validate metric calculations and visuals, with a plan to replace with dynamic date ranges. This work establishes measurable latency visibility, enabling data quality monitoring and informing operational decisions.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for nasa/opera-sds: Delivered a Python-based OPERA Data Latency Analysis and Visualization Script that queries CMR for granule metadata, computes key latency metrics, and generates histogram plots to visualize data timeliness. The implementation includes test scaffolding with hardcoded dates to validate metric calculations and visuals, with a plan to replace with dynamic date ranges. This work establishes measurable latency visibility, enabling data quality monitoring and informing operational decisions.
May 2025
April 2025
10 Commits • 3 Features
Apr 1, 2025April 2025: Key deliverables in nasa/opera-sds focused on interactive DISP S1 visualization, deployment infrastructure, and reliable access to historical status data. Included CI/CD simplifications and documentation updates.
April 2025
10 Commits • 3 Features
Apr 1, 2025April 2025: Key deliverables in nasa/opera-sds focused on interactive DISP S1 visualization, deployment infrastructure, and reliable access to historical status data. Included CI/CD simplifications and documentation updates.
March 2025
4 Commits • 2 Features
Mar 1, 20252025-03 monthly summary for nasa/opera-sds: Delivered automation for OPERA DISP S1 HTML retrieval and introduced a new status visualization, while stabilizing paths and fixing documentation issues. This period emphasizes business value through automation, improved visibility, and changed-relevant reliability across data workflows.
4 Commits • 2 Features
Mar 1, 20252025-03 monthly summary for nasa/opera-sds: Delivered automation for OPERA DISP S1 HTML retrieval and introduced a new status visualization, while stabilizing paths and fixing documentation issues. This period emphasizes business value through automation, improved visibility, and changed-relevant reliability across data workflows.
March 2025
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for nasa/opera-sds: Delivered a geographically-filtered visualization feature and cleaned up GeoJSON processing to streamline daily workflows, enhancing regional decision-making and maintainability.
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for nasa/opera-sds: Delivered a geographically-filtered visualization feature and cleaned up GeoJSON processing to streamline daily workflows, enhancing regional decision-making and maintainability.
Activity
Loading activity data...
Quality Metrics
Correctness88.6%
Maintainability89.6%
Architecture87.0%
Performance87.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptMarkdownPythonYAML
Technical Skills
API IntegrationAWS S3AWS SDKCI/CDCSSCode RefactoringCommand-line InterfaceData AnalysisData ProcessingData VisualizationDevOpsDocumentationFile ManagementFront-end DevelopmentFrontend Development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline