This project addresses semantic challenges in spatially-informed transdisciplinary research using semantic technology.

• A knowledge-based approach for sharing and outreaching geospatial data and knowledge for transdisciplinary research using semantic technology.
• We complement ontologies with semantic constraints (SHACL) for handling subtle and complex semantic relations raised by the multiple representations of geospatial data.
• We complement ontologies with semantic rules (SPIN) for formalising the knowledge of geospatial data visualisation.
• The approach is showcased in a traffic spatially-informed study – visualising urban bicycling level-of-traffic-stress

There are four main folders in this project:

Ontologies: contains all the ontologies designed and used in this study

Semantic constraints: Contains the SHACL constraints defined for integrating geospatial data with field-collected data

Semantic rules: contains all example rules used for the case study of level-of-traffic-stress visualisation in Lund, Sweden

Web visualisation app: a Python Django-based web framework including both backend and frontend implementation for data visualisation and exploration based on the knowledge-based approach

Contact:
Weiming Huang
GIS Centre, Lund University, Sweden