GeoCogent
Creators: name: Hou, Shuyang
Publisher: name: figshare
Year: 2024
Subjects: classificationCode: 370401
subject: Computational modelling and simulation in earth sciences
classificationCode: 370402
subject: Earth and space science informatics
classificationCode: 370403
subject: Geoscience data visualisation
classificationCode: 370499
subject: Geoinformatics not elsewhere classified

description: GeoCogent Prototype System and GeoCodes Dataset: Overview<b>Introduction:</b><br>The GeoCogent Prototype System and GeoCodes Dataset are two essential components developed to advance research and practical applications in the field of geospatial code generation. These resources aim to provide a robust, open-access platform and evaluation framework for researchers and developers, facilitating efficient and accurate geospatial code generation while addressing core challenges such as complex demand parsing, syntax adaptation, path retrieval, and code validation.<b>GeoCogent Prototype System:</b><br>The GeoCogent Prototype System is an interactive, user-friendly tool designed to automate geospatial code generation using a large language model (LLM)-driven agent framework. The system integrates three key mechanisms—planning, tools, and memory—to enable dynamic interaction with user inputs and external environments. Key features include:<b>Local Deployment:</b> Run the system locally by executing <code>app.py</code> for ease of use and flexibility.<b>Knowledge Integration:</b> Manage knowledge bases via JSON files and task data through TXT files for seamless operation.<b>LLM Integration:</b> Supports the connection and extension of various LLMs to enhance geospatial code generation tasks.<b>User Accessibility:</b> Offers an intuitive interface and detailed user manual, enabling researchers and developers from various fields to leverage geospatial code generation tools without extensive technical expertise.<b>GeoCodes Dataset:</b><br>GeoCodes is a comprehensive benchmark dataset specifically designed for evaluating the performance of geospatial code generation models. It consists of 50 diverse tasks across three demand types—explicit demands, incomplete demands, and open-ended demands—encompassing various platforms, programming languages, data sources, and output types. Key characteristics include:<b>Diverse Task Coverage:</b> Tasks range from straightforward geospatial analyses to more complex, context-specific operations.<b>Standardized Reference Materials:</b> Each task includes demand parsing documents, executable code, and reference outputs to ensure consistency in evaluation.<b>Open-Access:</b> GeoCodes is freely available to the research community, providing a standard framework for performance comparisons across geospatial code generation models.<b>Impact and Contribution:</b><br>Together, the GeoCogent Prototype System and GeoCodes Dataset aim to:Lower technical barriers for geospatial code development.Provide a standardized evaluation framework to measure the effectiveness of geospatial code generation models.Facilitate cross-disciplinary collaboration and innovation in geospatial analytics.Support researchers and practitioners with practical tools for real-world geospatial applications.