Managing Research Data: Data Bytes Workshops

Data Management and Sharing (DMS) Plans are an often-overlooked tool for effectively planning how and where to store, describe, and share your research data so that it is secure and discoverable. DMS plans are a required component of many federal agency grants, but they can be helpful planning tools for any research project. In this workshop we will look at the components of a DMS plan required by federal funding agencies. We will also review tools such as DMPTool to help find templates for specific agencies. Participants are encouraged to bring DMS plans that they have used or are preparing for questions or group discussion. 

This series guides participants through each phase of the research process, focusing on a few AI tools per session. The aim is to equip researchers with practical, ethical, and efficient strategies for brainstorming, literature searching, synthesis, and citation.

Session 1 Focus: Defining and refining research ideas.

Includes a 10–15 minute discussion of the ethical use of AI and the importance of checking departmental policies before using AI tools in academic work.

Tools covered (subject to change):

• MirrorTalk.ai - An AI reflection assistant to help articulate early ideas, brainstorm topics, and identify key search terms.
• Consensus - Searches peer-reviewed literature to deliver evidence-based answers and highlight agreement or debate in the field.
• 2D Search - Allows visualizing and manipulation of research queries in a two-dimensional space to optimize search strategies.

Session Two is on September 18 and Session Three is on September 25.  

The Library Catalog was updated in Summer 2025 with a new visual interface, and a more robust set of tools to help locate, manage, and work with scholarly research. This interactive session will help attendees understand how to use the Library Catalog to search for scholarly materials, use filters to refine search results, and use the Account tools to organize and manage citations for journal articles, books, and other resources. 

Inconsistent formatting, cryptic file naming, and poor folder organization can add unnecessary time and labor to a project, and it can be challenging (but not impossible!) to fix these issues once a project has already started. Using descriptive names and following a standardized organizational process will make your data and materials easier to understand, share, archive, and will help to meet FAIR guidelines. These guidelines seek to improve the Findability, Accessibility, Interoperability, and Reuse of data and are being increasingly promoted and required by funding agencies, publishers, and government agencies. This workshop will provide practical suggestions for naming and organizing files and folders as well as recommend better practices to comply with FAIR data principles. 

This series guides participants through each phase of the research process, focusing on a few AI tools per session. The aim is to equip researchers with practical, ethical, and efficient strategies for brainstorming, literature searching, synthesis, and citation.

Session 2 Focus: Efficiently finding relevant scholarly sources.

Tools covered (subject to change):

• Perplexity.ai - Combines web and academic sources to provide cited, summarized responses to research questions.
• Elicit.com - AI-curated literature summaries with methodological insights and paper comparisons, turning broad questions into focused research tasks.

Session Three is on September 25.  

We are leveraging facial recognition in university digital archives to identify individuals in historical photographs, enhance metadata quality, and uncover richer insights into archival materials. By contextualizing thousands of digital records, AI—especially facial recognition—helps reconstruct narratives that might otherwise remain hidden. These tools provide alumni, researchers, and communities with powerful new ways to engage with archival content. 

This series guides participants through each phase of the research process, focusing on a few AI tools per session. The aim is to equip researchers with practical, ethical, and efficient strategies for brainstorming, literature searching, synthesis, and citation.

Session 3 Focus: Understanding, comparing, synthesizing sources, and managing citations.

Tools covered (subject to change):

• NotebookLM - Upload PDFs or notes, ask targeted questions, summarize content, and identify thematic links.
• Rayyan - AI-assisted screening tool for organizing and filtering studies based on inclusion/exclusion criteria.
• Recite -Checks references for correct formatting and completeness.

Note that Zotero sessions are offered separately.  

Open access data and data sets published by U.S. government agencies are available to researchers in Data.gov and Science.gov, as well as the data catalogs that many agencies maintain. Data can be cleaned and standardized using OpenRefine and other software packages. Learn the key access points to federal data and how to improve data usability with OpenRefine.

Individuals interested in this session may also be interested in attending a hands-on workshop series on November 5th and 12th that provides an introduction to OpenRefine - register for that workshop series here! 

Can AI-powered tools offer supplementary capabilities that enhance your literature discovery and topic development process? This hands-on workshop will introduce you to four AI research tools (Elicit, Undermind, AI2, and Consensus) while emphasizing their role as complements to, not replacements for, established database searches.

What You'll Learn:

• Hands-on Experience: Work directly with free and limited versions of Elicit, Undermind, AI2, and Consensus to understand their unique strengths and applications
• Technical Foundations: Explore how these tools work beyond basic GenAI, including Retrieval-Augmented Generation (RAG), Deep Search, and emerging Deep Research methodologies
• Strategic Integration: Develop approaches for incorporating AI tools into existing research workflows while maintaining rigorous academic standards
• Critical Evaluation: Learn to assess when and how these tools can enhance your research process without compromising thoroughness or accuracy

 

Research data is a valuable resource. Careful management practices reduce mistakes, improve research reproducibility and facilitate publishing and sharing data. Better practices for different phases of the research data cycle will be discussed including planning for data collection, file management, data security, options for data storage during the project and long term storage of data for sharing after the project is complete. Data management and sharing are also one part of a broader movement toward more open research practices. Please join us and learn these important skills in order to get your research project off to a great start. 

Tremendous increase in the computational power has enabled a phenomenal growth in the use of machine learning models over the past decade or so. Jupyter notebooks offer a convenient interactive computing environment for data, code, and text. Despite its popularity, installation of Jupyter environment, in a classroom setting, can be challenging due to the use of personal computers with different operating systems. Google Colab, a web-based computing environment, offers a convenient platform-independent solution for rapid prototyping of Python codes. In this hands-on tutorial, I will demonstrate basic features of Google Colab and show how it can be used for teaching and research. 

This workshop will explore the use of the R package ggplot2 to create effective, professional data visualizations. Participants will explore various data visualizations and aesthetic modifications to graphs through some hands-on exercises. This will expand on the ggplot2 lesson from the R Carpentries workshop series. Attendees are expected to have some prior experience coding in R (e.g., creating objects, importing data, writing and executing basic functions) but do not need prior experience with the ggplot2 package itself. 

Discover the power of citation chaining to elevate your research process! This hands-on workshop introduces advanced techniques for tracking scholarly conversations using both traditional library databases and innovative visualization tools.

What you'll learn:

• Harness Scopus (requires okey login) for comprehensive backward and forward citation searching
• Explore the recommendations and visualizations of Research Rabbit
• Map research landscapes with LitMaps and Connected Papers
• Uncover hidden connections in academic literature using Inciteful

Why it matters:
For graduate students and faculty alike, citation chaining is an invaluable skill that can:

• Ensure comprehensive literature reviews
• Identify emerging trends and key papers in your field
• Save time by efficiently mapping scholarly discourse
• Discover unexpected connections between research areas

Note on Tool Accessibility:
We will primarily cover the free versions of these tools during the workshop. However, some tools offer paid versions with additional features. Given the evolving nature of these technologies, the pricing models and availability of free versions may change. We'll discuss strategies for making the most of these tools regardless of their pricing structure. 

LaTeX is a typesetting system for producing technical documents and is an important document standard in a number of disciplines. LaTeX gives authors more flexibility and control than other word processing software, but is less intuitive for first time users. This workshop will cover basic use of the text editor and introduce the markup language of LaTeX. Participants will gain a basic understanding of how to use LaTeX to create documents, how to write and format text, formatting equations, inserting figures, and creating a bibliography. We will use the Overleaf LaTeX text editor, which is a cloud-based LaTeX authoring software and does not require installing any software ahead of time. This workshop will also cover collaborative authoring and connecting your Overleaf project to GitHub. 

As artificial intelligence transforms research workflows across disciplines, the fundamental literacies that researchers need are evolving rapidly. This interactive workshop introduces metaliteracy—a comprehensive framework for critically evaluating, creating, sharing, and reflecting on information in collaborative digital environments—as the foundation for developing AI literacy in research contexts.

Drawing from recent scholarship on AI integration in libraries and higher education, participants will explore how the metaliteracy framework's four domains (cognitive, metacognitive, behavioral, and affective) provide essential scaffolding for ethical and effective AI engagement. Rather than focusing on specific tools, this session emphasizes developing transferable competencies that remain relevant as AI technologies continue to evolve.

Through hands-on activities and collaborative discussion, participants will examine how traditional research skills translate into AI-enhanced workflows, explore frameworks for evaluating AI tools, and develop strategies for maintaining human agency in technological collaboration. This workshop positions researchers not as passive consumers of AI outputs but as active partners in human-AI collaboration that amplifies rather than replaces critical thinking.

Perfect for researchers across disciplines who want to thoughtfully integrate AI into their work while maintaining rigorous academic standards and ethical practices.

Workshop Structure

• Opening & Context Setting: AI as arrival technology, libraries as centers of gravity
• Metaliteracy Framework Overview: Four domains and AI literacy connections
• Hands-on Tool Evaluation: Using the framework to assess AI research tools
• Collaborative Application: Developing personal AI integration strategies
• Reflection & Next Steps: Resources and continued learning pathways

Prerequisites: No prior AI experience required. Participants should bring a research project or question they're currently working on to use as a case study during activities. 

Description coming soon! 

This 90 minute hands-on workshop teaches systematic skills and approaches for those who decide to use generative AI chatbots. Through guided exercises using your own project, you'll practice providing context, breaking down complex tasks, iterating on prompts, and applying responsible use principles. You'll develop practical competencies in strategic delegation, effective prompting, and critical evaluation of results while developing a framework for intentional and transparent integration into academic or professional work.

Key skills:

• Strategic delegation: Analyzing projects to decide which tasks benefit from human expertise, AI capabilities, or collaboration, including when not to use AI
• Effective prompting: Communicating clearly with generative AI tools through context, examples, constraints, and structured approaches
• Critical evaluation and transparency: Assessing AI outputs for quality and accuracy while maintaining responsibility and communication for final decisions

This workshop assumes some basic familiarity with AI chatbots. Bring a project idea and a device (please let the instructor know if you need a laptop or check out a device at the Library Circulation desk). Note that you may use any available AI tools including Microsoft Copilot (available to OSU community members) but remember that free tools will likely have usage limits.

This workshop is built on the AI fluency framework developed by Rick Dakan and Joseph Feller. See their "Framework for AI Fluency (Practical Summary Document)" 

One of the major functions of the patent system is invention identification, protection, and dissemination of technical information. “Patent information is a valuable and comprehensive source of technical, commercial, and legal information that can be used for invention identification and directly for scientific and experimental purposes.” Patents are primary source documents and can be used to discover new areas of research, for ideas to improve existing research, or to see if a product has already been developed. Learn about:

1. General Prior Art Search Methods for Cursory Prior Art Reporting – Overview of intellectual property and how to provide the OSU Office of Technology Commercialization or IP attorney with helpful results and how (Identify innovation, Google Patents search methods, what to record)
2. Using the Patent Public Search at the U.S. Patent and Trademark Office to identify classifications for more comprehensive patent search results
3. Literature and prior art review using Library databases

 

 

We all value the work art and museum curators perform to preserve valuable information, items, and works so that they exist far into the future. Research data should be treated with much of the same care and meticulousness so that it can be properly archived and available to other researchers as well as the general public many years from now. As more funding agencies and journals require or encourage data sharing as a condition of funding or publication, researchers find themselves navigating metadata schemas, data documentation, and data repository selection which may all be completely new to them.

This workshop will suggest some small research workflow alterations to improve the quality of your data and streamline the process from data collection to archiving. It will also cover common metadata schemas and resources, data documentation templates, and an overview of data repositories and how to go about selecting one that is appropriate for your research. 

This workshop explores the legal and scholarly implications of authorship and generative AI for faculty and students, using major lawsuits—such as Authors Guild v. OpenAI, Bartz v. Anthropic, Getty Images v. Stability AI, and New York Times v. OpenAI—as case studies to examine differing perspectives on fair use and infringement. AI developers argue that training is transformative: outputs are new works created for learning and research, not direct copies. Copyright holders and authors counter that their works were used without permission, sometimes sourced from pirated copies, replicating their style or even reproducing content verbatim. We will discuss the implications of these cases for academia; for example, what happens when scholars use AI outputs that reproduce copyrighted passages or images without citation or permission? What tools and best practices are emerging for managing text corpora, including in academic data mining? What ethical questions arise around style appropriation and attribution? Participants will leave with a clear understanding of these landmark cases, their relevance to scholarly authorship, and practical approaches for responsibly integrating AI into research and teaching. 

During this interactive session, we will look at how to develop content for Virtual Reality (VR) and Augmented Reality (AR) as well as how we can use some of these tools for academic research focusing on projects that the Mixed Reality Lab at Oklahoma State University is working on.