Complex infrastructures such as railway networks face increasing challenges related to resource allocation, external events, constraints, and demands. Therefore, it is crucial to optimize the Asset Management (AM) phase to ensure the value and functionality of the assets. The integration of Building Information Modelling (BIM) and Geographic Information Systems (GIS) can support this phase, but it can only yield benefits with a comprehensive approach that considers and addresses the specific needs and resources of the assets and their AM organization. The main benefits include improved data management, manipulation, information visualization and optimized resource allocation. This study describes an intermediate step towards developing a BIM/GIS integration framework for AM that can guide both researchers and practitioners. The framework aims to bridge theory and practice by incorporating insights from literature reviews and case studies. Its main objectives are to provide a comprehensive multi-stakeholder view and methods for effectively integrating BIM and GIS in this context. To develop the framework, the study employed focus groups, interviews, and practical BIM/GIS tests, which provided insights reported in this article. Furthermore, the study provides research directions for effective BIM/GIS integration in infrastructure AM
University of Salento, Italy - ORCID: 0000-0001-7479-1464
University of Salento, Italy - ORCID: 0000-0002-6659-2171
Chalmers University of Technology, Sweden - ORCID: 0000-0002-3706-8485
Chapter Title
Towards a Framework for Railway Network Assets Management Based on BIM/GIS Integration
Authors
Mattia Mangia, Carla Di Biccari, Mattias Roupé
DOI
10.36253/979-12-215-0289-3.42
Peer Reviewed
Publication Year
2023
Copyright Information
© 2023 Author(s)
Content License
Metadata License
Book Title
CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality
Book Subtitle
Managing the Digital Transformation of Construction Industry
Editors
Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi
Peer Reviewed
Publication Year
2023
Copyright Information
© 2023 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press
DOI
10.36253/979-12-215-0289-3
eISBN (pdf)
979-12-215-0289-3
eISBN (xml)
979-12-215-0257-2
Series Title
Proceedings e report
Series ISSN
2704-601X
Series E-ISSN
2704-5846