Status: early development — no stable code or releases yet. Structure and APIs will change.
VeloNEMO v2 is the scaled successor of VeloNEMO, a formal ontology for harmonizing bike network evaluation metrics (Grisiute et al., 2024). Where v1 was a proof of concept built from a manually curated corpus of 25 papers, v2 extends the knowledge model and populates it automatically from a large heterogeneous document corpus using a schema-constrained LLM extraction pipeline.
The knowledge model grows along three axes:
- Evaluation perspective: explicit modeling of objective vs. perceived evaluations, replacing v1's
Perceivedname-prefix. - Decision structure: an index's modelling commitments (metric orientation, normalization, weighting, compensation, spatial interdependence) as queryable entities.
- Provenance: geographic and temporal context of each evaluation, so commitments can be analyzed as spatio-temporally situated choices.
The model is designed in two layers: a generic mid-level model for composite urban indices, and a cycling-domain specialization. The same structure is intended to extend to walkability, liveability, and related index families.
ontology/ VeloNEMO v2 (OWL) + validation shapes
extraction/ schema-constrained LLM extraction pipeline
resolution/ entity resolution and canonicalization
validation/ agreement scoring against the v1 ground truth
analysis/ queries and corpus-scale analyses
conda env create -f environment.yml
conda activate velonemo2- Grisiute, A., Wiedemann, N., Herthogs, P., & Raubal, M. (2024). An ontology-based approach for harmonizing metrics in bike network evaluations. CEUS, 113, 102178. https://doi.org/10.1016/j.compenvurbsys.2024.102178
Ayda Grisiute — Institute of Cartography and Geoinformation, ETH Zurich