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 archive your research data so that it is secure and discoverable. DMS plans are becoming 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, including the new NIH Data Management and Sharing Plan which went into effect January 25, 2023. 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.  

The Library Search is easy to use but incredibly powerful, and this session will help you get the most out of the tools available to you. It will cover basics such as using the search box, using limiters to refine your searches, and using the Advanced Search screen to drill down to find exactly what you need. The session will also go in-depth with the Folder tool to help you organize your research, and use Publication Finder to locate specific books and journals. 

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. 

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 for comprehensive backward and forward citation searching
• Explore the recommendations and visualizations of Research Rabbit
• Map research landscapes with LitMaps
• 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 influencers 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 may 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. 

 

This session focuses on creating a virtual server by assigning hardware resources to host applications on the cloud, assigning IP addresses, and installing basic system software. Presented by Nikhil Motwani, Research Professional in Digital Resources and Discovery Services at the OSU Libraries. 

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. 

In this hands-on tutorial, we will discuss decision tree-based machine learning models by first providing a basic understanding of the algorithm for determining a decision tree. We will then show how decision-tree models can be improved through random forest models, which combine outputs of multiple decision trees. Workshop participants will have the opportunity to work on developing a decision-tree model using the Python library scikit-learn and Google Colab as the Python interface.

This workshop is co-sponsored by the Chemical Engineering Graduate Student Association (ChEGSA). 

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. 

Open access data and data sets published by U.S. government agencies are available to researchers in Data.gov and Science.gov, also 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. 

Explore cutting-edge AI tools to revolutionize your research discovery process! This workshop introduces powerful AI-driven platforms that can help you navigate vast amounts of scholarly literature with unprecedented efficiency and insight.

What you'll learn:

• Explore Elicit for AI-assisted literature discovery and question answering
• Leverage Consensus for rapid research synthesis and gap analysis
• Streamline your literature management with SciSpace
• Craft more effective search queries using AI chatbots like Claude and ChatGPT
• Apply AI-generated search strategies in Scopus and other library databases
• Explore additional AI tools that support various aspects of the research process

Why it matters:
For researchers at all levels, AI-powered discovery tools offer significant advantages:

• Dramatically reduce time spent on initial literature searches
• Quickly identify key papers and emerging trends in your field
• Generate more precise and comprehensive search queries
• Uncover insights that might be missed through traditional keyword searches
• Enhance the quality and relevance of your database search results

Note on AI Tools and Accessibility:
We will focus on the currently available free versions of these AI tools. However, it's important to note that many AI-powered platforms operate on freemium models or may transition to paid services. We'll discuss how to effectively use these tools while being mindful of potential changes in accessibility and pricing. Please also note that with AI tools, additional care should be taken when entering data and evaluating the results.  

 

Description coming soon!