Group A, Poster #311, Applied Science Implementation (ASI)
Making CyberShake Friendly to General Users: CyberShake Data Access GUI
Poster Image:
Poster Presentation
2025 SCEC Annual Meeting, Poster #311, SCEC Contribution #14456 VIEW PDF
l aims to be more accessible and usable for a broader community.
My research project involves the development of a desktop-based graphical user interface (GUI) using Tkinter, which is a Python library designed to wrap and automate the CyberShake data access tool’s core functions, such as model selection, filtering, query generation, and seismogram retrieval. To further enhance usability, the CyberShake GUI incorporates a Large Language Model (LLM) interface powered by Gemini AI API. This allows users to ask basic questions about the CyberShake data access tool (e.g., “What are the models?”) and receive intelligent, context-aware responses directly within the application.
The resulting application significantly improves the user experience of accessing CyberShake data. GUI testing showed users were able to complete tasks more quickly and with fewer errors compared to the command-line version. The integrated LLM further enhanced accessibility by guiding users through unfamiliar steps, answering questions about the tool's features, and helping interpret results.
It brings seismic hazard tools within reach of more professionals by making them more user-friendly and responsive to user input. Future work will include the expansion of the LLM's learning, such as the exploration of web-based applications to provide remote access and additional collaboration, making it cross-platform, and filtering within the interactive map.
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My research project involves the development of a desktop-based graphical user interface (GUI) using Tkinter, which is a Python library designed to wrap and automate the CyberShake data access tool’s core functions, such as model selection, filtering, query generation, and seismogram retrieval. To further enhance usability, the CyberShake GUI incorporates a Large Language Model (LLM) interface powered by Gemini AI API. This allows users to ask basic questions about the CyberShake data access tool (e.g., “What are the models?”) and receive intelligent, context-aware responses directly within the application.
The resulting application significantly improves the user experience of accessing CyberShake data. GUI testing showed users were able to complete tasks more quickly and with fewer errors compared to the command-line version. The integrated LLM further enhanced accessibility by guiding users through unfamiliar steps, answering questions about the tool's features, and helping interpret results.
It brings seismic hazard tools within reach of more professionals by making them more user-friendly and responsive to user input. Future work will include the expansion of the LLM's learning, such as the exploration of web-based applications to provide remote access and additional collaboration, making it cross-platform, and filtering within the interactive map.
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Citation: Chong Loo, M., Tiwari, N., Wang, Y., & Callaghan, S. (2025, 09). Making CyberShake Friendly to General Users: CyberShake Data Access GUI. Poster Presentation at 2025 SCEC Annual Meeting.
Keywords: GUI, CyberShake, LLM, Map
Relevant SCEC Themes:
Applied Science Implementation
Research Computing & Cyberinfrastructure
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