Session Details

Modified

May 12, 2026

About

This page provides additional information about the workshop sessions and links to presenter notes.

Note

Some sessions are part of a thematic series, but each session stands on its own. You’re welcome to attend any session, even if you haven’t attended earlier ones.

Day 1 • Mon May 11

Research Data Stewardship Program

Penn State has recently approved and the Provost endorsed a training program in Research Data Stewardship. Hear more about this exciting new program and learning opportunity from one of its creators.

Presenter: Briana Wham

Prerequisites: None

Skill level: Novice

Location: Dewey Room

Open @ Penn State

What initiatives and resources are available at Penn State related to open scholarship?

Location: Dewey Room

Workshop Session 1

Getting credit (Part I): Good enough data practices

Effective data management is key to research integrity, reproducibility, and making your data useful beyond your own project. Since most researchers have limited time to perfect their workflows, this workshop introduces ‘good enough’ data practices; simple, time-efficient strategies that lay the groundwork for sharing, publishing, and reusing data. You’ll learn how to organize your files using logical directory structures and naming conventions, keep your data tidy and consistent, track changes with version control, and create basic metadata to describe your dataset. By the end of the session, you’ll be equipped with practical tools to make your data easier to manage now and far easier to share later. This is the first of three workshops on Getting Credit for Sharing Your Data.

Presenter: Alaina Pearce

Prerequisites: None

Skill level: Novice

Location: Dewey Room

Resources:

A gentle introduction to Git: A graphical overview of version control for computational workflows

Version control with Git is a foundational skill for modern software development and collaborative research, yet it is often perceived as difficult to learn due to its command-driven interface and abstract conceptual model. This one-hour workshop provides a gentle, visually driven introduction designed to lower that barrier to entry.

Rather than focusing on commands or terminal usage, this session emphasizes a high-level, graphical understanding of how Git works. Participants will explore key concepts such as commits, branches, merges, and repositories through intuitive diagrams and workflow illustrations. The goal is to build mental models of how changes are tracked, shared, and integrated over time, making the structure of Git more accessible and less intimidating.

This workshop is intentionally designed as a conceptual on-ramp with no prior Git experience required. Additional resources and learning opportunities will be announced so attendees can build further skills.

Presenter: Carrie Brown

Prerequisites: If you do not already have a GitHub account, this is a good time to create one.

Skill level: All

Location: W211A Pattee

Workshop Session 2

Quarto (Part I): A tool for open scholarship

Quarto is an open-source scientific and technical publishing system. As the Quarto site suggests, if you have a story to tell with data, you can tell it with Quarto. This workshop will introduce Quarto and show how it can be a powerful tool for implementing open scholarship practices. This is the first of two workshops on Quarto. The second workshop is here.

Presenter: Rick Gilmore

Prerequisites: None, but if you plan to bring a laptop, please follow the instructions here to install R, RStudio, and Quarto.

Skill level: Novice

Resources:

Location: W211A Pattee

Getting credit (Part II): Making your data make sense

Just as important as sharing your data is how you document it. Metadata provides the essential context—the who, what, when, where, why, and how—that enables others to interpret and build upon your work. We will focus on two essential tools, regardless of data type: README files and data dictionaries. Additionally, we learn about 2 domain general data standards that can help guide the creation of these tools: Frictionless’s Data Package and Psych-DS. By the end of the session, you will have the knowledge and tools to document your data to support transparency, reproducibility, and meaningful reuse. This is the second of three workshops on Getting Credit for Sharing Your Data.

Presenter: Alaina Pearce

Prerequisites: None

Skill level: Novice

Location: Dewey Room

Resources: - Slides: | Keynote Link | pptx | - Sample data README: | md | txt | - Psych-DS dataset_description.json file: json | - Psych-DS R Demo: | psychds-demo - FAIR Checklist: | pdf |

Day 2 • Tue May 12

Workshop Session 3

Harnessing advanced cyberinfrastructure for research: An introduction to Roar and ICDS resources

Join us for a workshop exploring the powerful computational and data resources available through Penn State’s Institute for Computational and Data Sciences (ICDS). Learn how to leverage the Roar supercomputing system—featuring high-performance CPU and GPU capabilities, scalable storage, and support for data-intensive research. Whether you’re running complex simulations, processing large datasets, or developing sophisticated workflows, Roar provides flexible solutions tailored to researchers across all disciplines. This session will cover both interactive, user-friendly interfaces and batch computing workflows to help you get started, regardless of your technical background.

Presenter: Carrie Brown

Prerequisites: Attendees will need an active Roar account. To request Roar access, please complete the Account Request form by Tuesday, May 5, 2026. If you do not already have a GitHub account, this is a good time to create one.

Skill level: All

Location: W211A Pattee

Workshop Session 4

Quarto (Part II): Making useful things reproducibly

Rick Gilmore will show how to build useful scholarly products in a reproducible way using Quarto and GitHub.

Presenter: Rick Gilmore

Prerequisites: Quarto (Part I) or equivalent. If you plan to bring a laptop, please follow the instructions here to install R, RStudio, and Quarto. If you do not already have a GitHub account, this is a good time to create one. Please also consider completing this anonymous, silly, and short Qualtrics survey: https://pennstate.qualtrics.com/jfe/form/SV_3l7ZkwVhhLI9Re6

Skill level: Advanced beginner

Location: W211A Pattee

Resources:

Getting credit (Part III): Making your data citable

Sharing data openly is a growing expectation in research but getting formal recognition for the time and effort involved is still a challenge. To make data truly reusable, others must be able to find, access, and understand it. This workshop will guide participants through selecting an appropriate data repository and introduce data papers, where is one approach to increasing the visibility and citablity of your data. By the end of the session, you’ll have the knowledge to identify repository features that meet your needs, and a working knowledge of data papers. This is the third of three workshops on Getting Credit for Sharing Your Data.

Presenter: Alaina Pearce and Kyle Hallisky

Prerequisites: None

Skill level: Novice

Location: Dewey Room

Resources:

Lunch and Learn

Engaging with Social Media

Presenters: Courtney Witmer

Prerequisites: None

Location: Dewey Room

Workshop Session 5

From questionable to credible: Responsible and robust research in the age of AI

This session introduces participants to questionable research practices (QRPs) and the strategies researchers can use to conduct rigorous, transparent studies. Participants will explore how research integrity challenges are evolving in the age of AI, and review principles for responsibly incorporating AI into an open scholarship framework.

Presenters: Jennifer Valcin

Prerequisites: None

Skill level: Novice

Location: Dewey Room

Introduction to Python and Jupyter Notebooks

This one-hour, hands-on workshop offers an introduction to Python programming using the JupyterLab environment. Designed for participants with no prior coding experience, the session covers the foundational building blocks of Python, including variables, data types, arithmetic operations, strings, lists, conditional statements, and loops. Working through interactive example notebooks, attendees will gain practical experience navigating JupyterLab and executing live code in real time. The session concludes with a brief demonstration of data visualization to illustrate the broader capabilities of Python in research and analysis. Participants will leave with a set of curated notebooks for continued self-paced exploration. A laptop with internet access is required; no software installation is necessary, as all materials can be run in Google Colab.

Presenter: Kadir Cihan Duran