Enhancing the Interpretability of 3D City Model Validation Through Web Visualization: The Case Study of the CHEK Validation Results Viewer


Akin A. T., Villar A., Diakite A., El Yamani S., Stoter J., Noardo F., ...Daha Fazla

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, cilt.15, sa.7, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 7
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3390/ijgi15070282
  • Dergi Adı: ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, INSPEC, Directory of Open Access Journals, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Earth, Atmospheric, & Aquatic Science Collection (ProQuest), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

3D city models (3DCMs) are increasingly used in urban simulations, cadastral workflows, and digital building permit processes, and automated validation of these models has become a routine requirement. Existing validation services typically produce dense, frequently generated by SHACL engines, text-based reports that are difficult for users without a semantic-web background to interpret. This paper describes the CHEK Validation Results Viewer (CHEK VRV), a Flask-based web application that couples the OGC Data Completeness Validator with an interactive Three.js 3D viewer of the CityJSON input. SHACL violations and geometric invalidities are spatially explorable on a visual representation of the model, and the tool supports both predefined CHEK Building Block Profiles and user-uploaded custom profiles. We report a formative usability study with twelve domain experts (urban planners, data vendors, academics) and use it to identify the tool's current strengths, its limitations, and a prioritized development roadmap. As reported by the participant experts, such a presentation is easier to interpret than the raw JSON-LD report.