Data informs decisions throughout our lives, and its importance keeps growing in a data-centric society and future. Scientists, educators, students, and the workforce at large require advanced skills to learn how to manage and process massive amounts of data efficiently and accurately. The nation’s future as a global leader of innovations depends on having a large, versatile, and adaptable data-proficient workforce.

Training this workforce, however, is challenging and requires significant hands-on skills in data systems where the constantly evolving hardware architectures, networking technologies, or changing price-performance ratios create unprecedented opportunities but also an urgent need for thorough and ongoing education in topics ranging from data acquisition, computer networking, storage systems, machine learning and data analytics, and visualization.

This project develops a FOUNT of scaffolded, educational modules, or courselets, in the rapidly developing field of data systems, that provide shared educational content executable on Chameleon and other open clouds and testbeds. The courselets are based on the concept of literate programming and enable students to explore concepts and methods taught in the classroom via hands-on exercises – and then modify and extend those exercises in various ways to deepen their understanding and explore new ideas. Students can find relevant courselets through a content hub, integrated with open clouds and testbeds, so that they can deploy them “with one click”, making exploration-based learning readily available. Ultimately, the project aims to translate its experience of creating, teaching, supporting, and improving courselets into a set of best practices, and build a vibrant community of students, teachers – and contributors across all types of academic institutions, and thereby create a model of digital sharing that will improve availability of digital educational content to all members of our society.