Reason over a Climate Policy Knowledge Graph for an EU Think Tank
Overview
What this challenge is about.
Design a knowledge graph schema covering regulations, member states, sectors, transposition dates, and source-document citations. Ingest a curated dataset of around 200 nodes the think tank provides (a CSV is fine). Implement a small rules engine (Datalog-style or RDFLib + SPARQL) supporting compositional queries with explicit derivation traces. Ship a CLI that accepts a natural-language-style question template, runs it, and returns the answer plus the derivation chain. Demonstrate on 10 sample questions in a Jupyter notebook. Write a 2-page schema-and-reasoning rationale.
The Brief
What you'll do, and what you'll demonstrate.
Build a knowledge-graph reasoner over EU climate-policy data with explicit derivation traces.
Earning criteria — what you'll demonstrate
- Design a knowledge-graph schema for a real policy domain
- Implement compositional rule-based reasoning with derivation traces
- Translate user questions into structured queries
- Communicate the design choices behind a knowledge representation
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
AI Engineer
Designing and shipping a working knowledge-graph reasoner with provenance is the AI engineer's craft in any policy- or research-tech org.
This challenge sharpens
- knowledge-graphs
- rule-based-reasoning
- python
AI Solutions Architect
Translating a domain into a reasonable knowledge representation is exactly the bridge a solutions architect builds between subject experts and code.
This challenge sharpens
- knowledge-representation
- data-modeling
- rdf-sparql