atviriduomenys/manifest
Oct 2024 – Feb 2026
13 Months active
Languages Used
CSVTextShellN/AConfiguration
Technical Skills
Data CleaningData CurationData EngineeringData ManagementDataset CreationDataset Management
AdrianMoroz
PROFILE
Adrianmoroz
Adrian Moroz developed and maintained a suite of data engineering assets for the atviriduomenys/manifest repository, focusing on robust CSV dataset creation, schema normalization, and ingestion pipeline reliability. Over 13 months, Adrian delivered new datasets, standardized data models, and improved data quality through careful data cleaning, validation, and metadata management. Using Shell scripting and configuration files, he streamlined batch-driven updates and ensured traceable, version-controlled changes. His work addressed data integrity issues, reduced redundancy, and enabled analytics readiness for government and public sector datasets. Adrian’s technical approach emphasized reproducibility, maintainability, and clear documentation, resulting in reliable, analytics-ready data infrastructure.
Overall Statistics
Feature vs Bugs
84%Features
Repository Contributions
126Total
Bugs
7
Commits
126
Features
36
Lines of code
1,341
Activity Months13
Your Network
12 peopleWork History
February 2026
6 Commits • 1 Features
Feb 1, 2026February 2026 performance summary for atviriduomenys/manifest: Delivered comprehensive Pedagogai.csv dataset metadata and data quality enhancements, enabling more accurate analytics and improved usability for education indicators. Implemented a dedicated metadata CSV, updated data and added statistics-focused columns, integrated the dataset into data sources, refreshed data sources, and refined the dataset title for clarity and accuracy. This lays the groundwork for reliable reporting and data-driven decision making across stakeholder teams.
6 Commits • 1 Features
Feb 1, 2026February 2026 performance summary for atviriduomenys/manifest: Delivered comprehensive Pedagogai.csv dataset metadata and data quality enhancements, enabling more accurate analytics and improved usability for education indicators. Implemented a dedicated metadata CSV, updated data and added statistics-focused columns, integrated the dataset into data sources, refreshed data sources, and refined the dataset title for clarity and accuracy. This lays the groundwork for reliable reporting and data-driven decision making across stakeholder teams.
February 2026
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for atviriduomenys/manifest. Focused on data quality and pipeline reliability through CSV data type normalization.
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for atviriduomenys/manifest. Focused on data quality and pipeline reliability through CSV data type normalization.
November 2025
5 Commits • 1 Features
Nov 1, 2025November 2025 performance summary for atviriduomenys/manifest: Delivered a Medical Equipment CSV Data Model and Usability Refresh, standardizing and updating multiple CSVs to improve data accuracy, clarity, and usability for analytics and governance. The work enhances data ingestion reliability, analytics readiness, and onboarding for new datasets.
5 Commits • 1 Features
Nov 1, 2025November 2025 performance summary for atviriduomenys/manifest: Delivered a Medical Equipment CSV Data Model and Usability Refresh, standardizing and updating multiple CSVs to improve data accuracy, clarity, and usability for analytics and governance. The work enhances data ingestion reliability, analytics readiness, and onboarding for new datasets.
November 2025
October 2025
8 Commits • 1 Features
Oct 1, 2025Month 2025-10: Consolidated delivery of new building datasets and ingestion configuration for gov/datalab, plus data model cleanup and integrity fixes to improve data quality and reliability. This work expands dataset coverage, standardizes naming, and strengthens validation indicators, enabling faster analytics and more accurate reporting.
October 2025
8 Commits • 1 Features
Oct 1, 2025Month 2025-10: Consolidated delivery of new building datasets and ingestion configuration for gov/datalab, plus data model cleanup and integrity fixes to improve data quality and reliability. This work expands dataset coverage, standardizes naming, and strengthens validation indicators, enabling faster analytics and more accurate reporting.
September 2025
3 Commits • 2 Features
Sep 1, 2025September 2025 performance: Focused on expanding and simplifying the building attributes data model in the manifest dataset to enable richer analytics while improving maintainability. Delivered two targeted dataset changes and reduced attribute duplication to streamline downstream workflows.
3 Commits • 2 Features
Sep 1, 2025September 2025 performance: Focused on expanding and simplifying the building attributes data model in the manifest dataset to enable richer analytics while improving maintainability. Delivered two targeted dataset changes and reduced attribute duplication to streamline downstream workflows.
September 2025
August 2025
21 Commits • 7 Features
Aug 1, 2025Month: 2025-08 Concise monthly summary focusing on the developer's work on atviriduomenys/manifest: Key features delivered - Delivered three dataset files as part of the August batch: ntr_pastatu_atributai.csv, asmenys_su_negalia.csv, and priedangu_kas_poreikis.csv. Each file was created, renamed to a standardized CSV format, and updated to reflect the latest batch data, enabling downstream analytics and reporting. - Implemented data refresh for ntr_pastatu_atributai.csv with batch-2 updates, ensuring current attributes align with August 2025 changes. - Updated ingestion/configuration to support new datasets and batch-driven updates (get_data_gov_lt.in). Major bugs fixed / data quality improvements - Fixed file naming and format inconsistencies by renaming datasets to their standardized CSV names (e.g., asmenys_su_negalia.csv, priedangu_kas_poreikis.csv). - Improved data freshness and consistency across all three datasets through batch-2 updates and content refinements. Overall impact and accomplishments - Enabled reliable, up-to-date data feeds for analytics, reporting, and compliance with August 2025 batch changes. - Reduced manual maintenance by consolidating dataset creation, renaming, and updates into a clear, versioned process with visible Git commits. - Strengthened data integrity and traceability with a structured series of commits per feature. Technologies / skills demonstrated - Dataset management and CSV file conventions, batch processing, and configuration management (get_data_gov_lt.in). - Version control discipline: incremental data updates with clear commits mapping to features. - Data quality, data modeling, and operational data workflows for batch-driven data projects.
August 2025
21 Commits • 7 Features
Aug 1, 2025Month: 2025-08 Concise monthly summary focusing on the developer's work on atviriduomenys/manifest: Key features delivered - Delivered three dataset files as part of the August batch: ntr_pastatu_atributai.csv, asmenys_su_negalia.csv, and priedangu_kas_poreikis.csv. Each file was created, renamed to a standardized CSV format, and updated to reflect the latest batch data, enabling downstream analytics and reporting. - Implemented data refresh for ntr_pastatu_atributai.csv with batch-2 updates, ensuring current attributes align with August 2025 changes. - Updated ingestion/configuration to support new datasets and batch-driven updates (get_data_gov_lt.in). Major bugs fixed / data quality improvements - Fixed file naming and format inconsistencies by renaming datasets to their standardized CSV names (e.g., asmenys_su_negalia.csv, priedangu_kas_poreikis.csv). - Improved data freshness and consistency across all three datasets through batch-2 updates and content refinements. Overall impact and accomplishments - Enabled reliable, up-to-date data feeds for analytics, reporting, and compliance with August 2025 batch changes. - Reduced manual maintenance by consolidating dataset creation, renaming, and updates into a clear, versioned process with visible Git commits. - Strengthened data integrity and traceability with a structured series of commits per feature. Technologies / skills demonstrated - Dataset management and CSV file conventions, batch processing, and configuration management (get_data_gov_lt.in). - Version control discipline: incremental data updates with clear commits mapping to features. - Data quality, data modeling, and operational data workflows for batch-driven data projects.
May 2025
6 Commits • 3 Features
May 1, 2025May 2025: Focused on data-quality improvements and schema normalization across dataset assets in atviriduomenys/manifest. Delivered robust normalization for license data, corrected radiology data sourcing, and progressed VRK ADSA migration alignment for balsu_skaiciavimo_isvykos.csv. These changes enhance data consistency, reduce downstream errors, and improve readiness for VRK Spinta deployment.
6 Commits • 3 Features
May 1, 2025May 2025: Focused on data-quality improvements and schema normalization across dataset assets in atviriduomenys/manifest. Delivered robust normalization for license data, corrected radiology data sourcing, and progressed VRK ADSA migration alignment for balsu_skaiciavimo_isvykos.csv. These changes enhance data consistency, reduce downstream errors, and improve readiness for VRK Spinta deployment.
May 2025
April 2025
6 Commits • 3 Features
Apr 1, 2025April 2025 performance summary for atviriduomenys/manifest: three dataset enhancements and one bug fix delivered to improve data integrity, schema consistency, and analytics readiness. Demonstrated strong data modeling and version-control discipline, with clear traceability via commit history.
April 2025
6 Commits • 3 Features
Apr 1, 2025April 2025 performance summary for atviriduomenys/manifest: three dataset enhancements and one bug fix delivered to improve data integrity, schema consistency, and analytics readiness. Demonstrated strong data modeling and version-control discipline, with clear traceability via commit history.
March 2025
35 Commits • 10 Features
Mar 1, 2025March 2025 monthly summary for atviriduomenys/manifest. Focused on delivering foundational data artifacts, refining dataset quality, and stabilizing ingestion inputs to support downstream analytics. Key work spanned artifact creation, file naming standardization, dataset updates across reklamos_leidimas.csv, kulturos_objektai.csv, pranesimai.csv, and get_data_gov_lt.in, plus ingestion configuration improvements.
35 Commits • 10 Features
Mar 1, 2025March 2025 monthly summary for atviriduomenys/manifest. Focused on delivering foundational data artifacts, refining dataset quality, and stabilizing ingestion inputs to support downstream analytics. Key work spanned artifact creation, file naming standardization, dataset updates across reklamos_leidimas.csv, kulturos_objektai.csv, pranesimai.csv, and get_data_gov_lt.in, plus ingestion configuration improvements.
March 2025
February 2025
1 Commits
Feb 1, 2025February 2025 performance summary for atviriduomenys/manifest: Implemented a targeted data quality improvement by normalizing kapo_id data type in velionys.csv from ref to string to standardize the dataset. This fixes inconsistencies and strengthens downstream processing and analytics. Change applied via commit 57294b808f631a6f2e97ff735e0ba91146d61266 (Update velionys.csv). No new user-facing features; primary achievements center on data governance, reliability, and reproducibility across ETL pipelines.
February 2025
1 Commits
Feb 1, 2025February 2025 performance summary for atviriduomenys/manifest: Implemented a targeted data quality improvement by normalizing kapo_id data type in velionys.csv from ref to string to standardize the dataset. This fixes inconsistencies and strengthens downstream processing and analytics. Change applied via commit 57294b808f631a6f2e97ff735e0ba91146d61266 (Update velionys.csv). No new user-facing features; primary achievements center on data governance, reliability, and reproducibility across ETL pipelines.
January 2025
11 Commits • 4 Features
Jan 1, 2025January 2025 (Month: 2025-01) focused on data standardization, schema refinement, and dataset integration within atviriduomenys/manifest. Key features delivered include standardized lab/clinical datasets, refined data schemas for reliability, removal of nonessential fields to simplify pipelines, fixed data integrity issues, and onboarding of a new dataset to broaden analytics coverage and governance. Key features delivered: - Lab tyrimai dataset schema and data standardization: updated lab_tyrimai.csv with vda_prime_key metadata (value 4 and 'open') and aligned tyrimo_meginio_tipas. - Anr.csv data schema refinement (KetPazeidejas): refined KetPazeidejas column in anr.csv to improve data integrity. - Cvpp.csv data cleanup: removed unused 'sequence' column to simplify the dataset. - Patarles_priezodziai.csv integrity fix (tipo_id_nuoroda): corrected the reference to ensure data integrity. - Add maitinimo_paraiskos dataset and enrich/refine schema: added maitinimo_paraiskos.csv with metadata, integrated into manifest, removed deprecated columns, adjusted norma and formatting to align with existing datasets. Overall impact and accomplishments: - Improved data quality, consistency, and downstream usability across multiple datasets, enabling more reliable analytics and reporting. - Strengthened data governance through standardized metadata and schema refinements, reducing ETL errors and onboarding time for new analyses. - Demonstrated end-to-end data curation—from schema design and cleanup to dataset integration and manifest updates—within a single monthly cycle. Technologies/skills demonstrated: - Data modeling and schema design for CSV-based datasets - Metadata management and standardization across multiple datasets - dataset integration into a manifest with schema alignment - Data cleaning, integrity checks, and de-duplication of deprecated fields - Git-based collaboration and multi-commit iteration across datasets
11 Commits • 4 Features
Jan 1, 2025January 2025 (Month: 2025-01) focused on data standardization, schema refinement, and dataset integration within atviriduomenys/manifest. Key features delivered include standardized lab/clinical datasets, refined data schemas for reliability, removal of nonessential fields to simplify pipelines, fixed data integrity issues, and onboarding of a new dataset to broaden analytics coverage and governance. Key features delivered: - Lab tyrimai dataset schema and data standardization: updated lab_tyrimai.csv with vda_prime_key metadata (value 4 and 'open') and aligned tyrimo_meginio_tipas. - Anr.csv data schema refinement (KetPazeidejas): refined KetPazeidejas column in anr.csv to improve data integrity. - Cvpp.csv data cleanup: removed unused 'sequence' column to simplify the dataset. - Patarles_priezodziai.csv integrity fix (tipo_id_nuoroda): corrected the reference to ensure data integrity. - Add maitinimo_paraiskos dataset and enrich/refine schema: added maitinimo_paraiskos.csv with metadata, integrated into manifest, removed deprecated columns, adjusted norma and formatting to align with existing datasets. Overall impact and accomplishments: - Improved data quality, consistency, and downstream usability across multiple datasets, enabling more reliable analytics and reporting. - Strengthened data governance through standardized metadata and schema refinements, reducing ETL errors and onboarding time for new analyses. - Demonstrated end-to-end data curation—from schema design and cleanup to dataset integration and manifest updates—within a single monthly cycle. Technologies/skills demonstrated: - Data modeling and schema design for CSV-based datasets - Metadata management and standardization across multiple datasets - dataset integration into a manifest with schema alignment - Data cleaning, integrity checks, and de-duplication of deprecated fields - Git-based collaboration and multi-commit iteration across datasets
January 2025
November 2024
13 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for atviriduomenys/manifest: Expanded data ingestion coverage by scaffolding the finmin_sis data source, launched and continuously improved the finmin.csv dataset, and fixed open access level for teises aktai. These changes enabled broader data availability, improved data quality, and a foundation for more reliable analytics and reporting across government datasets.
November 2024
13 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for atviriduomenys/manifest: Expanded data ingestion coverage by scaffolding the finmin_sis data source, launched and continuously improved the finmin.csv dataset, and fixed open access level for teises aktai. These changes enabled broader data availability, improved data quality, and a foundation for more reliable analytics and reporting across government datasets.
October 2024
10 Commits • 1 Features
Oct 1, 2024October 2024 monthly summary for atviriduomenys/manifest focusing on delivering the Galiojantys_projektai dataset integration with VTPSI data sourcing, improving data quality, and validating schema alignment. The work enabled end-to-end data onboarding and improved reliability of the ETL pipeline for new datasets, with targeted fixes improving downstream analytics readiness.
10 Commits • 1 Features
Oct 1, 2024October 2024 monthly summary for atviriduomenys/manifest focusing on delivering the Galiojantys_projektai dataset integration with VTPSI data sourcing, improving data quality, and validating schema alignment. The work enabled end-to-end data onboarding and improved reliability of the ETL pipeline for new datasets, with targeted fixes improving downstream analytics readiness.
October 2024
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Quality Metrics
Correctness95.8%
Maintainability96.0%
Architecture94.6%
Performance95.8%
AI Usage20.6%
Skills & Technologies
Programming Languages
CSVConfigurationN/AShellText
Technical Skills
Data CatalogingData CleaningData CurationData EngineeringData ManagementData MigrationData ModelingDataset CreationDataset Managementdata accuracydata analysisdata cleaningdata managementdata processingdata sourcing
Repositories Contributed To
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