Enhancing Data Education with Datathons: an Experience with Open Data on Renewable Energy Systems Antonella Longo antonella.longo@unisalento.it SyDa Lab, Department of Engineering for Innovation, University of Salento Lecce, Italy Marco Zappatore marcosalvatore.zappatore@unisalento.it SyDa Lab, Department of Engineering for Innovation, University of Salento Lecce, Italy Angelo Martella angelo.martella@unisalento.it SyDa Lab, Department of Engineering for Innovation, University of Salento Lecce, Italy Chiara Rucco chiara.rucco@unisalento.it SyDaLab, Department of Engineering for Innovation, University of Salento Lecce, Italy ABSTRACT Data literacy and the fundamentals of big data management are becoming interdisciplinary in Higher Education curricula, also due to the widespread need of data science skills. This casts the need for presenting novel (and more engaging) learning activities to students. Data hackathons (also known as datathons) represent a viable option to allow students practicing with real use cases and datasets, as well as addressing their learning experiences collabo- ratively. Moreover, datathons promise to improve soft skills and ofer hands-on learning opportunities. Therefore, we present in this paper a datathon on a publicly available dataset about renewable energy systems. The datathon involved students from three data- focused courses of three diferent M.S. degrees at the University of Salento (Italy). A detailed analysis of the design, implementation and evaluation choices is proposed, along with a series of gath- ered insights and lessons learned that might help systematizing the introduction and use of datathons in data education. CCS CONCEPTS · Applied computing → Collaborative learning; · Informa- tion systems → Data management systems; Data cleaning; Ex- traction, transformation and loading. KEYWORDS datathon, open data, data education curricula, renewable energy systems ACM Reference Format: Antonella Longo, Marco Zappatore, Angelo Martella, and Chiara Rucco. 2022. Enhancing Data Education with Datathons: an Experience with Open Data on Renewable Energy Systems. In 1st International Workshop on Data Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specifc permission and/or a fee. Request permissions from permissions@acm.org. DataEd’22, June 17, 2022, Philadelphia, PA, USA © 2022 Association for Computing Machinery. ACM ISBN 978-1-4503-9350-8/22/06. . . $15.00 https://doi.org/10.1145/3531072.3535322 Systems Education (DataEd’22), June 17, 2022, Philadelphia, PA, USA. ACM, New York, NY, USA, 6 pages. https://doi.org/10.1145/3531072.3535322 1 INTRODUCTION In 1999, the frst ofcial coding event was held in Calgary, Canada: a group of 10 volunteer programmers joined a 1-week-long meet- ing of collaborative software development on OpenBSD, an open- source operating system. Soon after, the term hack(ing mara)thon, or hackathon for brevity, was coined to identify a collaborative coding event where programmers develop software prototypes ac- cording to a common goal or interest [13]. Since then, diferent typologies of coding events have been branched out (each one under a specifc name) while the original defnition of hackathon assumed a slightly diferent meaning in order to entail a broader perspective. Nowadays, if the focus is more on developing software prototypes in a competitive manner, either online or in presence, the term coding competition or coding hackathon is used. The term data hackathon or datathon is used when a specifc data-driven category of coding hackathon is considered, aimed at examining datasets, also by applying to them specifc data science approaches. When the event is not exactly software-driven and focuses on other skills, like hardware prototype implementation and demonstration, presentation capabilities, cross-disciplinary contributions, and so on, the original term hackathon is preferred. Therefore, datathons are quite a recent variant in the feld of coding hackathons: they ofer students and practitioners the op- portunity to join a peer competition on a previously-agreed data analysis/management set of tasks, which lasts for a predefned time window, addresses a real-world data-driven problem [2], and requires to present the outcomes to a specifc audience. The need for datathons rises from several driving factors. First, the requirement to enrich and update traditional data education curricula discloses new opportunity to pave the way for more sys- tematic introduction of datathons in higher-education programmes. Second, acquiring an adequate data literacy is nowadays requested at a cross-disciplinary level: being able to practice directly on real data wrangling challenges may beneft not only students from Com- puter Engineering and Data Science courses but also those coming from a broader spectrum of STEM disciplines. 26