Collaborative Research: CyberTraining: CIC: Framework for Integrated Research Software Training in High Energy Physics (FIRST-HEP)

University Of Puerto Rico Mayaguez, Mayaguez PR

Investigators

Abstract

High-energy physics (HEP) aims to understand the fundamental building blocks of nature and their interactions by using large facilities such as the Large Hadron Collider (LHC) at the European Laboratory for Particle Physics (CERN) in Switzerland and the Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) planned for the 2020s at Fermilab, in Illinois, as well as many smaller experiments. These experiments generate ever increasing amounts of data and rely on a sophisticated software ecosystem consisting of tens of millions of lines of code that is critical to mine this data and produce physics results. People are the key to developing, maintaining, and evolving this software ecosystem for HEP experiments over many decades. Building the necessary software requires a workforce with a mix of HEP domain knowledge and advanced software skills. The Framework for Integrated Research Software Training in High Energy Physics (FIRST-HEP) project provides a training path from a researcher's first steps through active contribution to software training and workforce development. The project serves the national interest as stated by NSF's mission to promote the progress of science by preparing a workforce trained in cyberinfrastructure and impacts STEM disciplines in terms of much needed and sought after software training. The FIRST-HEP project directly organizes training activities and works with partners to leverage and bring synergy to disparate existing efforts in order to maximize their collective impact. It brings together an extended set of partners from the community to build not only missing basic training elements like introductory programming skills in Python, git and Unix but also use of HEP data formats like ROOT and advanced topics including parallel programming, performance tuning, machine learning and data science for Ph.D. students. It works to build a community of instructors and experiments around the software training material and transforms the approach for research software training in HEP. It builds the workforce required for the cyberinfrastructure challenges of running and planned HEP facilities and experiments in the coming years.The FIRST-HEP education and training activities include specific goals to educate minorities in HEP, K- 12 educators and the broader STEM workforce. The K-12 teachers learn very basic skills of Unix including file management, programming languages, such as C+ and shell scripting. FIRST-HEP harnesses the potential of the underrepresented groups and works to ensure that the pool meets or exceeds the diversity in the larger HEP graduate student population when selecting both training participants and instructors for the HEP fundamental training sessions and the advanced computing schools. FIRST-HEP includes a dedicated outreach activity on cybertraining to the local Puerto Rico public. FIRST-HEP leverages engagement with the Software Carpentries to host training of K-12 teachers at UPRM in basic Software Carpentry skills and who in turn train their students. This encourages the teachers and school authorities to consider incorporating the basic carpentries into the high school curriculum. The training and cyber skills gained during the FIRST-HEP fundamental training courses directly contribute to the broader STEM workforce and trains students to pursue data science careers and other research areas besides HEP, such as Astronomy, where similar software skills are required. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.