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CyberGIS—geographic information science and systems (GIS) based on advanced cyberinfrastructure—is becoming increasingly important to tackling a variety of socio-environmental problems like climate change, disaster management, and water security. While recent advances in high-performance computing (HPC) have the potential to help address these problems, the technical knowledge required to use HPC has posed challenges to many domain experts. In this paper, we present CyberGIS-Compute: a geospatial middleware tool designed to democratize HPC access for solving diverse socio-environmental problems. CyberGIS-Compute does this by providing a simple user interface in Jupyter, streamlining the process of integrating domain-specific models with HPC, and establishing a suite of APIs friendly to domain experts. 

This paper provides an overview of the Hour of Cyberinfrastructure (Hour of CI), a project creating a suite of self-paced, hour-long lessons aimed at helping learners in the areas of spatial, social, and environmental sciences take their first steps in the path toward cyberinfrastructure. Using collaboratively developed lessons written in Jupyter Notebooks, the Hour of CI aims to lower barriers to cyberinfrastructure for next-generation scientists and scholars from broad and diverse backgrounds. Early findings based on a pilot of four lessons suggest our approach has created engaging and appropriately challenging lessons for diverse learners. The project will continue developing lessons to help learners build cyber literacy for GIScience and prepare them to tackle global problems. 

Geospatial research and education have become increasingly dependent on cyberGIS to tackle computation and data challenges. However, the use of advanced cyberinfrastructure resources for geospatial research and education is extremely challenging due to both high learning curve for users and high software development and integration costs for developers, due to limited availability of middleware tools available to make such resources easily accessible. This tutorial describes CyberGIS-Compute as a middleware framework that addresses these challenges and provides access to high-performance resources through simple easy to use interfaces. The CyberGIS-Compute framework provides an easy to use application interface and a Python SDK to provide access to CyberGIS capabilities, allowing geospatial applications to easily scale and employ advanced cyberinfrastructure resources. In this tutorial, we will first start with the basics of CyberGISJupyter and CyberGIS-Compute, then introduce the Python SDK for CyberGIS-Compute with a simple Hello World example. Then, we will take multiple real-world geospatial applications use-cases like spatial accessibility and wildfire evacuation simulation using agent based modeling. We will also provide pointers on how to contribute applications to the CyberGIS-Compute framework.