Managing Research Data: Data Bytes Workshops

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. 

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. Planning for data management is also a critical part of developing a written data management plan, or DMP, for funding proposals. Please join us and learn these important skills in order to get your research project off to a great start. 

One of the major functions of the patent system is the dissemination of technical information. “Patent information is a valuable and comprehensive source of technical, commercial and legal information that can be used directly for scientific and experimental purposes…” Patents are primary source documents and can supplement the traditional literature searches in your disciplines: they 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. 

Data Management and Sharing Plans (DMSPs) 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. DMSPs 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 DMSP 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.org to help find templates for specific agencies. Participants are encouraged to bring DMSPs that they have used or are preparing for questions or group discussion . 

You know what Wikipedia is, but what about Wikidata? Find out more about this collaborative data source, how to contribute data, and how to access existing data for research and visualization. Presented by Megan Macken, Assistant Head of Digital Resources and Discovery Services . 

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.  

Open Science Framework (OSF) is a free, open source web application developed to help researchers of all disciplines (not just science) manage their workflows. OSF provides a highly customizable interface, allowing users to create modules for housing data, research materials, communication, analysis files, and more. The system has automatic, built-in version control for all files and integrates with tools researchers already use such as Dropbox, Google Drive and GitHub. It also gives you the means to add contributors with various levels of read/write permissions. This interactive workshop will take you through the process of creating an OSF project, connecting to external services, adding contributors, and will demonstrate several use cases and examples. OSF meets the NIH and NSTC’s designation as a data repository, and has recently added functionality such as the ability to link to funders and awards in order to meet funder data and materials sharing requirements . 

For many research projects across a variety of disciplines, visualizing spatial data is a frequent requirement. Geographic Information Systems (GIS) can be used not only to create basic maps, but can uncover patterns and raise new questions about your data. In this session you will learn the basics of digital mapmaking and spatial analysis using Esri’s ArcGIS Pro software. 

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. 

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. 

Come and join us to learn about the machine learning work that we do in the University Archives. We will demonstrate how we use facial recognition to improve the accessibility of OSU archival collections. Presented by Dr. Max Prud’homme, Director of Digital Curation at the Edmon Low Library, and Lokesh Peta and Arundeep Bandaru, Graduate Research Assistants. 

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.  

During this session, we will look at how to develop content for VR and 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.