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Our monthly webinars highlight examples of gateways, tools, and best practices.

SGX3 hosts a webinar series each month (1 hour long). We feature a rotating selection of topics including tool and technology demos, best practices, and gateway showcases. These webinars are recorded for future viewing on our YouTube channel

We announce each webinar several weeks ahead through our newsletter and on this website.


Upcoming Webinars

SGX3 Webinar: Reproducibility of Computational Research – A Community of Practice

September 28, 2023, 2-3 pm EDT | 11 am - 12 pm PDT

Zoom Registration

Computational science is increasingly becoming the cornerstone of groundbreaking research across disciplines. However, the issue of reproducibility remains a major concern that calls for a collaborative, community-driven approach.

During the SC22 BOF, PEARC22 BOF and PEARC23 BOF on the reproducibility of computational research, there was a strong interest towards democratizing reproducibility in research by working as a community. Building on those discussions, we are starting a series of monthly webinars with three main goals: first to create a forum for sharing information, best practices and what has been accomplished so far related to reproducibility of computational research; second, to create an active community that focuses on facilitating reproducibility practices as part of the research lifecycle; third, to review together the catalog of existing reproducibility tools, discuss how we can use them, share success stories, discuss experiences of existing reproducibility efforts aiming at defining what needs to be captured to assure reproducibility of scientific research. We will aim to develop support services at our institutions, to lower barriers for capturing artifacts while doing research, to work together to increase the training of our researchers, and ultimately to work towards a concerted effort to build an ecosystem of tools and services to support reproducibility. Attendees will gain insights into both the opportunities and roadblocks in advancing reproducibility, and are encouraged to contribute to a community-led initiative aimed at enhancing the reliability and integrity of computational science.