lter/lterwg-caged
May 2025 – Mar 2026
3 Months active
Languages Used
RShell
Technical Skills
Climate DataClimate Data AnalysisData AcquisitionData AnalysisData ExplorationData Processing
nicomatamej
PROFILE
Nicomatamej
Nicolás Matamé developed an end-to-end climate and ecological data workflow for the lter/lterwg-caged repository, focusing on scalable data acquisition, integration, and analysis. He set up the R environment and implemented pipelines to ingest, harmonize, and visualize datasets from sources such as WorldClim, Net Primary Production, and TerraClimate, incorporating Google Drive integration for external data access. His work included data wrangling, coordinate corrections, and site-level aggregation, enabling reproducible exploratory and statistical analyses. By automating quality control and mapping for multiple sites, Nicolás improved research reproducibility and accelerated ecological insights, demonstrating depth in R programming, data processing, and spatial analysis.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
4
Lines of code
10,980
Activity Months3
Your Network
13 peopleShared Repositories
13
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered an end-to-end ecological data processing and analytics workflow in lter/lterwg-caged (harmonization, filtering, site-specific analyses) with scripts for data wrangling, quality control, and statistical analysis. Integrated 10/16 site location data to improve mapping and site-level insights. Strengthened reproducibility and scalability, accelerating data readiness and ecological insights across sites; no major bugs fixed this month.
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered an end-to-end ecological data processing and analytics workflow in lter/lterwg-caged (harmonization, filtering, site-specific analyses) with scripts for data wrangling, quality control, and statistical analysis. Integrated 10/16 site location data to improve mapping and site-level insights. Strengthened reproducibility and scalability, accelerating data readiness and ecological insights across sites; no major bugs fixed this month.
March 2026
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly performance summary for lter/lterwg-caged: Delivered TerraClimate data integration and visualization to enhance ecological analysis workflows. Implemented data extraction, coordinate corrections, and aggregation of climate variables (temperature, precipitation), with visuals showing TerraClimate data in relation to site locations and existing WorldClim data. This work enables more accurate, location-aware ecological insights and faster scenario evaluation, directly supporting site-level decision making and research reproducibility.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly performance summary for lter/lterwg-caged: Delivered TerraClimate data integration and visualization to enhance ecological analysis workflows. Implemented data extraction, coordinate corrections, and aggregation of climate variables (temperature, precipitation), with visuals showing TerraClimate data in relation to site locations and existing WorldClim data. This work enables more accurate, location-aware ecological insights and faster scenario evaluation, directly supporting site-level decision making and research reproducibility.
May 2025
6 Commits • 2 Features
May 1, 2025May 2025 monthly summary for lter/lterwg-caged: Delivered an end-to-end terrestrial climate data workflow and foundational exploratory analytics framework. Key features: Exploratory Analysis Groundwork (R environment setup, libraries, initial data handling) and End-to-End Terrestrial Climate Data Acquisition, Integration, and Visualization (core pipeline for WorldClim, NPP, TerraClimate including data retrieval, metadata handling, and mapping). Bugs: No critical bugs detected; resolved minor issues in data loading and environment configuration to enhance robustness. Impact: Establishes a reproducible, scalable data workflow enabling ingestion and visualization of climate datasets, accelerating analysis readiness and downstream decision-support. Technologies/skills: R, data ingestion pipelines, metadata management, GIS mapping, Google Drive data access, data validation, and version-controlled development.
6 Commits • 2 Features
May 1, 2025May 2025 monthly summary for lter/lterwg-caged: Delivered an end-to-end terrestrial climate data workflow and foundational exploratory analytics framework. Key features: Exploratory Analysis Groundwork (R environment setup, libraries, initial data handling) and End-to-End Terrestrial Climate Data Acquisition, Integration, and Visualization (core pipeline for WorldClim, NPP, TerraClimate including data retrieval, metadata handling, and mapping). Bugs: No critical bugs detected; resolved minor issues in data loading and environment configuration to enhance robustness. Impact: Establishes a reproducible, scalable data workflow enabling ingestion and visualization of climate datasets, accelerating analysis readiness and downstream decision-support. Technologies/skills: R, data ingestion pipelines, metadata management, GIS mapping, Google Drive data access, data validation, and version-controlled development.
May 2025
Activity
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Quality Metrics
Correctness67.6%
Maintainability67.6%
Architecture62.4%
Performance55.0%
AI Usage22.6%
Skills & Technologies
Programming Languages
RShell
Technical Skills
Climate DataClimate Data AnalysisClimate Data ProcessingData AcquisitionData AnalysisData ExplorationData ProcessingData VisualizationEnvironment SetupExploratory Data AnalysisGit ConfigurationGoogle Drive APIGoogle Drive IntegrationMetadata ProcessingNet Primary Production (NPP)
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