UNIVERSITY PARK, Pa. — The Research Data Stewardship department at Penn State University Libraries will offer 20 workshops beginning Sept. 16 on data topics including Data Management and Sharing, ScholarSphere and Data Analysis tools such as RStudio. The goal of these sessions is to introduce resources and research support areas available through the University Libraries.
All workshop sessions will be held online via Zoom. Sessions are free and open to all Penn State faculty, staff and students except where indicated. Advance registration with a PSU email address is required; registration and additional information are provided at the link for each session below.
For more information, contact ul-rds@lists.psu.edu.
Provost Endorsed Program in Research Data Stewardship
What Researchers Need to Know About Data Management and Sharing Policies
Sept. 16, 1-2 p.m., register here for "What Researchers Need to Know About Data Management and Sharing Policies."
This workshop provides an overview of key institutional and federal policies related to research data management and sharing. Participants will gain familiarity with Penn State policies and major funder requirements, such NIH and NSF, with an emphasis on how these policies inform data management planning and implementation, storage and sharing practices across the research lifecycle.
“Good Enough” Practices that Build Better Research Data Management Habits
Sept. 17, 1-2:30 p.m., register here for “Good Enough” Practices that Build Better Research Data Management Habits
This workshop covers foundational principles and practical skills for research data management. Participants will learn how to design clear directory structures and apply file naming conventions. They will also be introduced to version control strategies and the basics of “tidy” data. Hands-on activities and take-home resources will support the development of a data management strategy tailored to their own data needs.
Creating Data Others Can Understand: Metadata and Documentation
Oct. 8, 1-2:30 p.m., register here for Creating Data Others Can Understand: Metadata and Documentation
This workshop covers best practices for documenting data to ensure it is understandable and re-usable. Hands-on activities and take-home resources will support the development of README files and data dictionaries, two types of documentation that can be applied regardless of field. This workshop also highlights examples of field-specific data standards and introduces more field-agnostic standards like Frictionless Data Package and PsychDS along with tools that can support their adoption.
RECR Credit Workshops
“Good Enough” Research Data Management
Oct. 1, 11 a.m.-noon, join session here for “Good Enough” Research Data Management
This workshop covers foundational principles and practical skills for research data management. Participants will learn how to design clear directory structures and apply file naming conventions. They will also be introduced to version control strategies and the basics of “tidy” data. Hands-on activities and take-home resources will support the development of a data management strategy tailored to their own data needs.
Layers of Reproducibility: Practical Skills for More Transparent Research
Oct. 8, 11 a.m.-noon, join session here for Layers of Reproducibility: Practical Skills for More Transparent Research
Research credibility depends on whether others can understand, verify and build on your work. This workshop explores practical skills and ideas for making participants’ research more transparent and reproducible, whether they are working with a simple folder structure or automated data pipelines. Participants will discover strategies that span the spectrum from low to high tech, with the flexibility to adopt what fits their workflow. Attendees will leave with concrete approaches they can apply at any stage of the research process.
Statistical Analysis
Data Analysis Planning: Why is it Essential?
Sept. 22, 2-4 p.m., register here for Data Analysis Planning: Why is it Essential?
This workshop will provide information on setting up a data analysis plan. Many researchers have a specific question they would like to ask concerning their data but do not have an idea of how they will answer this question with quantitative analysis until after their data is collected, leaving them fewer options. The goal of this session is to help them understand how to make sure they have an appropriate sample size, the different types of data, which statistical tests may be used in each case, and the assumptions of different statistical tests.
Quantitative Methods for Undergraduate Students
Oct. 7, 1–2:30 p.m., open to undergraduate students, register here for Quantitative Methods for Undergraduate Students
This workshop introduces concepts such as descriptive vs. inferential statistics, running exploratory data analysis, testing data for normality and parametric vs. non-parametric data analysis. Participants will learn about different statistical methods for exploring and analyzing their data.
Introduction to SPSS
Oct. 15, 2-4 p.m., register here for Introduction to SPSS
This session will provide introductory knowledge on how to use SPSS for quantitative statistical analysis, with demonstrations using a practice dataset. Participants will learn how to access SPSS and how to navigate the software interface, inputting different types of data, specifying variables and conducting exploratory data analysis and some basic statistical tests. No previous SPSS experience is required.
Introduction to Minitab
Oct. 22, 2-4 p.m., register here for Introduction to Minitab
This session will provide a general overview of using Minitab for quantitative statistical analysis, with demonstrations using a practice dataset. Participants will learn how to access Minitab and navigate the software interface, inputting different types of data, specifying and transforming variables and conducting exploratory data analysis and some basic statistical tests. No previous Minitab experience is required.
R Workshop Series
Open to all — register for the R Workshop Series here
Introduction to R and RStudio
Oct. 14, 1-3 p.m.
This session will introduce R and RStudio, walk through the platform interface and discuss the utility of using the software for reproducible research practices. Participants will learn how to set a working directory, load data and packages, and discover how to find resources to support general learning and answer specific questions.
Data Wrangling in R
Oct. 21, 1-3 p.m.
This session will introduce the use of the package data.table to manage, clean and transform data into “tidy” format, or create new variables in a reproducible manner. Additionally, participants will learn how to handle string and date/time data.
Data Management and Reproducibility in R and RStudio
Oct. 28, 1-3 p.m.
This workshop will focus on data management strategies that can be implemented in R and RStudio to develop a reproducible analysis and output workflow to facilitate transparent and reproducible research, as well as support open data sharing.
Data Visualization in R
Nov. 4, 1-3 p.m.
This workshop will provide an overview of how to use the R package ggplot2 to create meaningful data visualizations.
Functions and Reproducible Workflows in R
Nov. 11, 1-3 p.m. — prior R experience or the earlier sessions in this series recommended
This workshop will focus on writing and using functions to streamline code, reduce redundancy and improve clarity. The session also will explore best practices for structuring R scripts and projects to support reproducible workflows in data processing and visualization.
Repositories and Open Access
Open Access from Every Angle: Navigating Funder Requirements and Making the Most of Penn State’s OA Policy with the Researcher Metadata Database and ScholarSphere
Oct. 20, 1-2 p.m., register here for Open Access from Every Angle
This workshop will train participants to use Penn State’s Researcher Metadata Database and ScholarSphere. Attendees will learn about their ability to share their scholarly works under Penn State’s Open Access to Scholarly Articles policy, AC02, as well as how to comply with federal public access policies. Attendees will also learn how to enter and maintain accurate metadata, identify materials that need to be archived, and deposit eligible scholarly outputs in ScholarSphere to meet policy obligations and improve discoverability. The session also will cover workflow best practices, file preparation and how these tools support timely compliance with funder mandates, long-term preservation and broader access to research outputs.
Sharing Data in ScholarSphere
Oct. 29, 1-1:45 p.m., register here for Sharing Data in ScholarSphere
This workshop on ScholarSphere, a Penn State institutional repository, will demonstrate how to use it to share and preserve research. The session cover what kinds of content ScholarSphere can host, how it supports data sharing and open scholarship, and how to prepare files with clear documentation and metadata. The session also will include a step-by-step demonstration of the deposit process along with time for questions and answers.
Where Should Your Data Live? Selecting the Right Repository
Nov. 5, 1-1:45 p.m., register here for Where Should Your Data Live? Selecting the Right Repository
This workshop on data repositories will teach participants how to find the best place to share their research data. The session will cover the different types of repositories and discuss key policies and repository characteristics to consider before a deposit. The session also will highlight Penn State’s repository options, such as ScholarSphere, and use examples to help participants confidently select a repository that fits their data and sharing goals.