cambridge-cares/TheWorldAvatar
Nov 2025 – Dec 2025
2 Months active
Languages Used
JSONRDFSPARQLSQLTurtle
Technical Skills
API integrationRDFSPARQLSQL scriptingdata engineeringdata integration
mqlim
PROFILE
Mqlim
Mei Qi Lim enhanced data integration and semantic modeling in the cambridge-cares/TheWorldAvatar repository over a two-month period. She developed and refined SQL and JSON artifacts to streamline ACRA entity ingestion, updated OBDA mappings to align with ontologies, and improved maintainability by removing external references. Using SPARQL and SQL scripting, she enabled precise retrieval of company data and optimized building identification logic for sea level rise analysis by tightening spatial matching criteria. Her work included targeted code cleanup and documentation updates, resulting in more reliable data pipelines, improved ontology consistency, and reduced maintenance complexity across backend and data engineering workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
4
Lines of code
7,627,190
Activity Months2
Your Network
23 peopleSame Organization
@cares.cam.ac.uk2
Work History
December 2025
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for cambridge-cares/TheWorldAvatar focusing on delivering robust data integration and precision improvements that advance FIA data pipelines and sea level rise analyses. Key outcomes include SPARQL-based ACRA entity retrieval for Singapore entities, precision enhancements in building identification, and targeted code cleanup to reduce maintenance burden while preserving data accuracy and reproducibility.
4 Commits • 2 Features
Dec 1, 2025December 2025 monthly summary for cambridge-cares/TheWorldAvatar focusing on delivering robust data integration and precision improvements that advance FIA data pipelines and sea level rise analyses. Key outcomes include SPARQL-based ACRA entity retrieval for Singapore entities, precision enhancements in building identification, and targeted code cleanup to reduce maintenance burden while preserving data accuracy and reproducibility.
December 2025
November 2025
7 Commits • 2 Features
Nov 1, 2025November 2025: Delivered critical enhancements to ACRA data integration and OBDA mappings in cambridge-cares/TheWorldAvatar, delivering measurable improvements in data ingestion speed, accuracy, and maintainability. Key outcomes include adding SQL/JSON artifacts and end-user documentation for the ACRA data uploader, and refining OBDA mappings for ACRA and Company entities to remove external references, align with ontologies, and extend RDF typing.
November 2025
7 Commits • 2 Features
Nov 1, 2025November 2025: Delivered critical enhancements to ACRA data integration and OBDA mappings in cambridge-cares/TheWorldAvatar, delivering measurable improvements in data ingestion speed, accuracy, and maintainability. Key outcomes include adding SQL/JSON artifacts and end-user documentation for the ACRA data uploader, and refining OBDA mappings for ACRA and Company entities to remove external references, align with ontologies, and extend RDF typing.
Activity
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Quality Metrics
Correctness96.4%
Maintainability91.0%
Architecture91.0%
Performance91.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONRDFSPARQLSQLTurtle
Technical Skills
API developmentAPI integrationRDFSPARQLSQL scriptingbackend developmentdata engineeringdata integrationdata mappingdata modelingdata queryingdata uploadingdatabase managementontology designsemantic web
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