GIFIS: A Generalized Immersive Flood Information System Specification

Abstract

This study introduces Generalized Immersive Flood Information Specification (GIFIS), a vendor-agnostic, JSON Schema–based framework for encoding, validating, and exchanging hydrologic and environmental data for reproducible and interoperable virtual and augmented reality applications. By defining standardized semantics for entities such as sensor datasets, hydrological model outputs, warnings and

Summary

This research introduces GIFIS, a novel framework designed to standardize how flood information systems encode, validate, and exchange data, particularly for virtual and augmented reality applications. By using a JSON Schema-based specification and a built-in validator, GIFIS aims to ensure interoperability and verifiable data quality across different platforms and agencies.

Key Insights

• •GIFIS uses a JSON Schema-based specification and a built-in validator to ensure that flood-related data is encoded, validated, and exchanged in a standardized and verifiable manner, paving the way for true interoperability.
• •The framework's hierarchical structure, comprising a Core Schema, Domain Profiles, and Portable Document Types, allows for flexibility and extensibility, enabling the addition of new domains and applications without affecting existing ones.
• •GIFIS aligns with existing standards like GeoJSON, EPSG, OASIS CAP, and OGC SOSA/SSN, promoting compatibility and integration with established geospatial and sensor data formats.
• •The validator provides specific error messages, pinpointing the location and nature of data inconsistencies, thereby simplifying debugging and correction processes.

Practical Implications

• •GIFIS can be used to create digital twins of flood-prone areas, enabling real-time monitoring and simulation of flood events, leading to improved flood forecasting and risk assessment.
• •The framework can improve communication and collaboration between different agencies and stakeholders involved in flood management by providing a common language for data exchange.
• •Future research should focus on developing more comprehensive domain profiles, integrating GIFIS with existing flood forecasting models, and evaluating its impact on decision-making during flood events.
• •The open governance and extensible design of GIFIS should foster community adoption and ensure long-term sustainability, making it a valuable tool for flood management and environmental science.

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