Executive Profile
Bridging Unstructured Enterprise Information with Connected Intelligence
As a Knowledge Engineer with an academic foundation in Data Science & Analytics, my expertise lies in transforming fragmented multi-source information into structured knowledge models, taxonomies, and Knowledge Graphs.
By designing semantic ontologies in RDF/OWL and implementing enterprise graphs using Neo4j & Cypher, I establish the relational blueprint required for seamless data governance, automated knowledge discovery, and AI-ready semantic search systems.
Executive Contact
- Lubna.bintalib@gmail.com
- +966 50 011 8148
- LinkedIn Profile
- github.com/lubnaTalib
- Riyadh, Saudi Arabia
Knowledge Network Metrics & Schema
Select a core knowledge domain below to inspect connected node structures and operational metrics.
Ontology & Knowledge Schema Modeling
Structuring domain entities, attributes, and relationships into machine-readable ontology schemas using RDF, RDFS, and OWL standards for organizational knowledge discovery.
Enables automated data validation, cross-departmental entity resolution, and semantic search integration.
Professional Experience
Knowledge Engineer
Specialized in Knowledge Engineering through the AI & Data Co-op, expanding scope into Tamheer professional practice.
Data Scientist
Focused on Data Analytics, Business Intelligence dashboards, and Data Engineering workflows.
Featured Projects
Connected Intelligence for Large-Scale Program
Structured and integrated information from diverse organizational sources into interconnected knowledge models. Contributed to entity mapping, ontology schemas, and Knowledge Graph implementation to enhance governance and discovery.
Mohkem | AI Legal Warning System
Developed a hybrid AI decision-support system combining XGBoost predictive models, Arabic NLP via AraBERT, legal risk scoring analytics, and historical case retrieval for proactive risk evaluation.
StockFlow Analytics
Built an automated ELT pipeline to extract, transform, and prepare stock-market data for statistical analysis using Python scripts and SQL transformations.
Diabetes Patients Analysis
Constructed analytical dashboard suites in Power BI displaying patient risk factors, disease trends, and clinical health markers to facilitate medical decision support.
Technical Skill Matrix
Knowledge Engineering
- Knowledge Graphs
- Ontology Design
- Semantic Modeling
- Data Modeling
- Taxonomies & SKOS
Tools & Standards
- Neo4j & Cypher
- RDF, RDFS, OWL
- SPARQL & SHACL
- Turtle (TTL)
- Power BI & Power Query
ML & Arabic NLP
- XGBoost Algorithms
- TF-IDF Feature Extraction
- AraBERT Language Models
- Arabic Text Processing
- Legal Risk Modeling
Languages & Pipeline
- Python
- SQL Database Querying
- Cypher Querying
- ELT / ETL Pipelines
- Data Cleansing & Prep