February 2026 focused on delivering two core enhancements in Giswater_dbmodel to strengthen data organization and role-based UI, driving data integrity, security, and user productivity. No major bugs fixed this month; the team concentrated on feature delivery with clear, commit-level traceability. The work aligns with product goals for governance, maintainability, and streamlined workflows by improving form data relationships and UI visibility controls.

January 2026 (Month: 2026-01) - Giswater/giswater_dbmodel This month delivered core data integrity and lifecycle improvements across the giswater_dbmodel domain, focusing on automated IDs, robust campaign management, and automated state transitions. Highlights include: - Key features delivered: - Database automatic ID generation via sequences: replaced manual ID inserts with database-managed sequences, improving data integrity and simplifying inserts. Commit: 81a5d2e23ea18941db79d559723ea71d5588da39. - Campaign management enhancements: added conflict handling on insert and status management during updates to ensure robust campaigns. Commits: 05e72d20e3f129e5fc90c2b206572d4a5dad0dc3; c07c3aa85e3dd32e4a0d91ab80add1da4a3908dd; 51c61fd06e7e66d51f76830ca833284aae0bee6f. - Foreign key constraints with cascading delete for flow regulator: constrained delete to prevent orphaned records. Commit: cbc85b68bc3061be481b7810417651c3b8a3e7cf. - Auto-update lot status to ON GOING on first object review: automates lot lifecycle transition. Commit: eb439ceea2790275f2aae8da3a6be894b50ad9a6. - Mincut feature: add changestatus field to v_om_mincut_valve and update style: enhances mincut functionality. Commit: d78aafe81ba10fcb80de14efbad052d7d0b167ed. - Major bugs fixed: - Restrict action-setting logic to role_cm_field to prevent errors when a user has multiple CM roles. Commit: 0e1db2708a215103d7998c2414a04023b190754d. Overall impact and accomplishments: - Strengthened data integrity and consistency through DB-level automation, safer cascades, and clearer lifecycle tracking. - Improved campaign reliability and data presentation for decision-makers. - Reduced manual intervention and potential user errors through automation and role-aware safeguards. Technologies/skills demonstrated: - PostgreSQL features: sequences, triggers, on-conflict guidance, cascading foreign keys. - Data modeling enhancements: new view fields (changestatus), status-driven workflows, and UI-friendly views. - SQL maintenance, refactoring, and role-based access considerations.

In 2025-12, Giswater/giswater_dbmodel delivered key data governance, access-control enhancements, and a critical data retrieval fix, driving better auditability, user provisioning automation, and data accuracy.

In 2025-11, delivered three prioritized improvements in Giswater/giswater_dbmodel: a reliability fix for the node rotation SQL query; a governance enhancement adding default created_by/created_at auditing for features inserted into cm; and visualization improvements for GIS styling of mincut valves, nodes, and flow regulators. These changes collectively increase data reliability, traceability, and UI clarity for operators and developers.

October 2025 monthly summary for Giswater/giswater_qgis_plugin focusing on UI polish and visual consistency enhancements in Plan Mode.

September 2025: Focused delivery in Giswater/giswater_dbmodel includes translation quality improvements for Costa Rica Spanish, hardening data integrity across SQL and triggers, and an enhanced QGIS symbology for UD projects. These changes deliver clearer user-facing strings for Costa Rican users, more reliable data processing with explicit SQL constraints and correct state handling, and richer, rule-based visualization for UD project layers, driving better decision-making and reduced support overhead.

Monthly summary for 2025-08 — Giswater/giswater_dbmodel Key features delivered: - Database schema cleanup and data quality improvements: standardizing naming conventions, removing team-based joins for admins, correct trigger key extraction, view renames, and sample catalog data corrections. Commits include 9e0bbafc9c5e804694d2a9b30e481c13a8c30370; c506a0ae536716cbcb83a1ee2573e13d57136d7f; 0ecb849f5ee6d47b6203464a7f523fce07d6b8b6; fdf2b39358c6086249fef838757e9c4815677649; f7551bfc8a209b591b9c1d3b471aab99f31a8c29. - Arc repair mode enhancement: gw_fct_setnodefromarc updated to honor previousSelection during arc repairs, preventing repair of all network arcs; includes MODE 2 example and mode-based conditional logic. Commit: 67a552388ea3f2155a073c02cd6a50bb536b7a09. - QGIS styling updates for arcs, connections, and Giswater layers: dynamic styling with width and labels; alignment with new geometry properties. Commits: ec7ae33256c174b9b238e6765c16d866a5533c15; fb64492f90fb9cae63c0b88312aaca737c190f0b. Major bugs fixed: - fix: set proper names for Elements and set lowercase for dwfzone y drainzone - fix(cm): drop join using team to not hide them for admins when the team doesn't match - fix(cm): change offset to 2 because the first two columns are id and campaing id. We need lot_id and feature_id - fix(element_x_relation_views): recover v_element_x_* views (similar to old vu views) and use them in gw_fct_featurechanges - fix(sample): set geom2 to 0 instead of 100 Overall impact and accomplishments: - Strengthened data governance, admin visibility, and data integrity across the Giswater DB model. - Reduced risk of unintended network-wide repairs and improved reliability of feature changes. - Improved map styling consistency and analyst usability, enabling faster decision-making and onboarding. Technologies/skills demonstrated: - SQL/database schema refactoring, data quality engineering, and view maintenance. - Arc repair logic with mode-based conditional workflows in GIS tooling. - QGIS styling and symbolization, integration with Giswater layers, and adherence to coding standards and version control.

July 2025: Implemented core data integrity and schema maintenance, introduced user-centric data access, refined node configuration UX, and enhanced campaign geometry workflows in Giswater/giswater_dbmodel. The work focused on data quality, targeted data retrieval, reliable spatial updates, and improved operational UX, delivering measurable improvements in data reliability, decision speed, and GIS-driven workflows.

Review for 2025-06: Giswater/giswater_dbmodel delivered a set of high-impact features, resolved critical data-consistency bugs, and advanced the maintainability and scalability of the data model and associated workflows. Key features delivered include a config-driven search enhancement, data modeling and element type improvements, geospatial styling for flow regulators, campaign/lot UX improvements with robust access control, and dynamic campaign integration. Major bugs fixed encompassed mincut selector ordering and configuration correctness, TG_OP handling in trigger logic, localization fix for Catalan exit_id, and document access control permission fixes. The month yielded measurable business value through more reliable search, improved data integrity, better role-based access, and easier multi-campaign deployments. Technologies demonstrated include PostgreSQL triggers and SQL fixes, data modeling refinements, configuration-driven design, i18n localization, and QGIS styling integration.

Month: 2025-05 — Giswater/giswater_dbmodel delivered key features and stability fixes to improve GIS visualization, data integrity, and access control. Major outcomes include enhanced flow visualization styling, a new geometry extent retrieval function, DQA ID support for arc/node operations, and configurable mincuts deletion permissions. Supporting bug fixes ensure correct layer identification and reliable municipality updates, reducing visual and data inconsistencies. Demonstrated strong SQL/PostGIS development, GIS styling, trigger customization, and governance-focused configurations with clear business value in data quality, user experience, and security controls.

April 2025 — Giswater/giswater_qgis_plugin: Delivered a contributors documentation update to the CONTRIBUTORS.md to reflect current team composition, including BGEO OPEN GIS and freelance contributors. This change strengthens governance, onboarding, and transparency, ensuring the project accurately represents who contributes and in what capacity. Implemented via a metadata authors/contributors refresh (commit ab16c249f1d3ea7fb8b837fda00a38bc436c730b).

March 2025 monthly summary for Giswater/giswater_dbmodel focusing on delivering business value through robust data modeling and visit-management enhancements. The work strengthens data governance, categorization, and analytics readiness while preserving system integrity and scalability.

February 2025 — Giswater/giswater_dbmodel: Delivered key schema enhancements and trigger hardening to improve data quality, governance, and deployment reliability. Focus areas: (1) Om Streetaxis table enhancements and schema corrections (new columns: road_type, surface, max_speed, number of lanes, one-way, pedestrian_access, access_info; fixed boolean data-type typo; moved DDL to correct workspace script). (2) GISWater trigger and validation bug fixes (corrected missing parentheses in ud_gw_trg_edit_gully; added triggers for ve_pol_connec and ve_pol_node; ensured fluid_type is derived when autoupdate is disabled; validated catalog IDs; fixed typo referencing conneccat_id).

January 2025, Giswater/giswater_dbmodel: Delivered UI correctness fixes, traceability enhancement, and a cross-schema SRID migration workflow. Result: improved data accuracy and presentation, richer audit trails, and a repeatable migration process with clear guidance. Focused on business value through reliable data presentation, robust schema changes, and maintainable runbooks for migrations.

December 2024 delivered focused reliability and data integrity improvements in Giswater/giswater_dbmodel, with regionalization support and enhanced maintenance over the DB schema. The work centers on feature delivery, bug fixes, and data quality improvements that reduce data inconsistencies, improve testing fidelity, and enable faster QA and regional projects.

Month: 2024-11 — Giswater/giswater_dbmodel: Delivered key features, fixed critical issues, and improved data integrity, performance, and user experience. The work focused on inventory traceability, schema resilience, and maintainability, driving business value through more accurate data, faster checks, and clearer configurations.

2024-10 monthly summary for Giswater/giswater_dbmodel highlighting stability, performance, and documentation improvements. Delivered data integrity fixes in inventory deletion, clarified in-database documentation, refined feature boundaries and error messaging for map zoning, and improved query performance for data checks. These changes reduce data inconsistencies, enhance maintainability, and speed up critical data operations.