dhis2-chap/chap-core
Mar 2025 – Sep 2025
4 Months active
Languages Used
PythonMarkdownRSTrst
Technical Skills
Data ProcessingData StructuresLicensingModular DesignObject-Oriented ProgrammingSoftware Architecture
geirksa
PROFILE
Geirksa
Geir K. Sandve developed modular data and evaluation frameworks for the dhis2-chap/chap-core repository, focusing on multi-location disease observation and forecasting workflows. He designed extensible data structures and implemented component-based evaluators, enabling flexible, location-aware analytics. Using Python and Markdown, Geir refactored data transformation utilities to standardize and align time series forecasts with observed data, supporting scalable backtesting and improved forecast accuracy. He modernized documentation to streamline onboarding and model integration, restructuring guides and enhancing information architecture. His work demonstrated depth in software architecture, data processing, and technical writing, establishing a robust foundation for reusable analytics and maintainable, compliant codebases.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
5
Lines of code
3,094
Activity Months4
Your Network
26 people
Work History
September 2025
4 Commits • 1 Features
Sep 1, 2025September 2025 focused on elevating CHAP's developer onboarding and model integration experience through a documentation modernization effort in chap-core. The work centralized and clarified guidance for integrating external models, revamped the landing page, reorganized the external models section, removed redundant pages, and updated links to HTML format. These changes improve discoverability, reduce onboarding time for new contributors, and set a scalable documentation foundation for future model integrations.
4 Commits • 1 Features
Sep 1, 2025September 2025 focused on elevating CHAP's developer onboarding and model integration experience through a documentation modernization effort in chap-core. The work centralized and clarified guidance for integrating external models, revamped the landing page, reorganized the external models section, removed redundant pages, and updated links to HTML format. These changes improve discoverability, reduce onboarding time for new contributors, and set a scalable documentation foundation for future model integrations.
September 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Delivered a targeted Forecast Data Representation Refactor and Enhancements in dhis2-chap/chap-core to enable accurate, multi-location forecasting aligned with observations. Implementations include: refactoring data transformation for multi-location forecasts; grouping and sorting by last seen period for reliable trend analysis; a new function to convert single split-point forecasts; and time-period filtering to ensure forecasts reflect observed intervals. All work is evidenced by the commit history and testing scaffolding to bootstrap local validation using YAML configurations, enabling smoother future CI integration. This lays the groundwork for scalable forecasting, improved data quality, and faster, more reliable analytics for multi-location operations.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Delivered a targeted Forecast Data Representation Refactor and Enhancements in dhis2-chap/chap-core to enable accurate, multi-location forecasting aligned with observations. Implementations include: refactoring data transformation for multi-location forecasts; grouping and sorting by last seen period for reliable trend analysis; a new function to convert single split-point forecasts; and time-period filtering to ensure forecasts reflect observed intervals. All work is evidenced by the commit history and testing scaffolding to bootstrap local validation using YAML configurations, enabling smoother future CI integration. This lays the groundwork for scalable forecasting, improved data quality, and faster, more reliable analytics for multi-location operations.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for dhis2-chap/chap-core: Delivered a Forecast Evaluation Framework enabling multi-location time series representations and an MAE-based evaluator for backtest forecasts vs true values across locations and time periods. Implemented data representation and transformation utilities to standardize backtest data across multiple locales, and resolved a Knut length mismatch bug in the evaluation path to ensure correct alignment of series. This work enhances structured forecast accuracy analysis, supports data-driven decisions, and lays groundwork for location-specific diagnostics and scalable backtesting.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for dhis2-chap/chap-core: Delivered a Forecast Evaluation Framework enabling multi-location time series representations and an MAE-based evaluator for backtest forecasts vs true values across locations and time periods. Implemented data representation and transformation utilities to standardize backtest data across multiple locales, and resolved a Knut length mismatch bug in the evaluation path to ensure correct alignment of series. This work enhances structured forecast accuracy analysis, supports data-driven decisions, and lays groundwork for location-specific diagnostics and scalable backtesting.
May 2025
March 2025
6 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for dhis2-chap/chap-core. Key features delivered include the Modular Assessment Data and Evaluation Framework, with modular data structures for disease observations, time series, and multi-location data, along with an abstract base evaluator and a component-based evaluator to enable flexible, location-aware assessment workflows. Licensing updates were completed with a move to AGPLv3, including temporary license file removal to re-establish the license via GitHub wizard and subsequent license text update. A minor fix addressed a stability issue in the modularised evaluation representations. Overall impact includes a solid foundation for reusable analytics across locations, improved compliance posture, and enhanced maintainability. Technologies demonstrated include modular architecture design, abstraction layers, component-based evaluation, license management, and disciplined Git-based traceability.
March 2025
6 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for dhis2-chap/chap-core. Key features delivered include the Modular Assessment Data and Evaluation Framework, with modular data structures for disease observations, time series, and multi-location data, along with an abstract base evaluator and a component-based evaluator to enable flexible, location-aware assessment workflows. Licensing updates were completed with a move to AGPLv3, including temporary license file removal to re-establish the license via GitHub wizard and subsequent license text update. A minor fix addressed a stability issue in the modularised evaluation representations. Overall impact includes a solid foundation for reusable analytics across locations, improved compliance posture, and enhanced maintainability. Technologies demonstrated include modular architecture design, abstraction layers, component-based evaluation, license management, and disciplined Git-based traceability.
Activity
Loading activity data...
Quality Metrics
Correctness91.6%
Maintainability91.6%
Architecture91.6%
Performance83.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonRSTrst
Technical Skills
Data ProcessingData RepresentationData StructuresData TransformationDocumentationForecastingInformation ArchitectureLicensingModel EvaluationModular DesignObject-Oriented ProgrammingSoftware ArchitectureSoftware DevelopmentTechnical WritingTime Series Analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline