Pre-study of data governance and integration for climate-resilient decision support in transport infrastructure (Aggregera)
Improving the capabilities necessary for decision-making and climate change adaptation regarding road and rail infrastructure maintenance and planning.
Facts
Researchers: Amir Garmabaki (PL), Ahmad Kasraei, From RISE: Alexander Gösta, Abdulrahman Kanaa
Project Sponsor: Trafikverket
Project Period: 2024-2025
Goal
The goal of this project is to improve the capabilities necessary for decision-making and climate change adaptation regarding road and rail infrastructure maintenance and planning. This involves fostering integrated data management, advanced analytics, and stakeholder collaboration to support proactive infrastructure planning, risk management, and climate adaptation.
Objectives
- Assessing Feasibility: Evaluate the feasibility of developing an integrated decision-support tool by analyzing existing data ecosystems, identifying governance frameworks, and addressing gaps or challenges.
- Existing Resources and Integration Potential: Create an inventory of available data, tools, and frameworks to determine their current state, accessibility, and relevance. Identify opportunities for integration and improvement to optimize the tool's functionality.
- Preliminary Stakeholder Analysis: Identify and analyze the roles, data needs, and contributions of key stakeholders and authorities. Explore how an improved decision-support tool can enhance their work in infrastructure planning, climate adaptation, and risk mitigation.
Project status and results
The following figure summarizes the core components of the digital support tool. The hypothesis that integrated datasets can significantly improve decision support for climate adaptation has been confirmed through stakeholder feedback and project insights.
The project's findings have generated interest beyond Trafikverket. Other stakeholders, such as SGI, are willing to leverage such systems for broader applications, including urban planning, risk assessments, and insurance modeling. The introduction of advanced technologies, such as drone monitoring, IoT sensors, and machine learning models, has expanded the possibilities for real-time, actionable insights. Furthermore, the geospatial standardization driven by EU directives, including Lantmäteriet's open data initiatives, has created new opportunities for broader data access and integration.
The final report of the pre-study is accessible.
Contact
Amir Garmabaki
- Associate Professor
- 0920-493429
- amir.garmabaki@ltu.se
- Amir Garmabaki
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