Biomedical Research Data Management: The Basics

Course description

Managing research data is the cornerstone of any successful research project in the health sciences. This course will explore the landscape of biomedical data management to facilitate better understanding and organization of data planning, collection, analysis, and preservation. To make data findable, accessible, interoperable, and reusable (FAIR), we focus on best practices in data management and sharing to aid in scientific discovery.   

This curriculum is designed as an online learning experience geared toward preparing working professionals to design, organize, and implement data management. The NU Advance course delivery will involve remote, self-paced learning, reflection activities, and online quizzes. The instructors will be available for additional one-on-one discussion. 

Perk: The First five UNMC students to enroll will receive a UNMC-branded swag item.

Learning Objectives 

1.                  Identify types of biomedical data  

2.                  Create a data management and sharing plan (DMSP) 

3.                  Organize data for analysis  

4.                  Make decisions based on collected and analyzed data  

5.                  Integrate the FAIR (findable, accessible, interoperable, reusable) Principles in data management planning and implementation 

For this course, we’ll explore the biomedical data management lifecycle’s central areas: 

·                     Storage (throughout each unit)  

·                     Planning and designing   

·                     Collection and creation  

·                     Analysis, sharing, and reuse  

·                     Preservation 

Target Audience
Anyone in the health sciences field interested in learning about data management. 

Course Modules 

Module 1: Planning and Designing (105 minutes) 

We will start with Data Management Plans, what they are, and how they can help guide data storage, collection, analysis, and evaluation. We will then turn to security, sharing, and retention policies.   

Module 2: Collection and Creation (85 minutes)

We will examine various ways of gathering data through online tools, like Electronic Lab Notebooks, REDCap, and Open Science Framework. We will turn to data types and formats, focusing on what, how much, and the data access level. Next, we’ll look at the metadata that helps organize collected data. Finally, we will discuss data organization such as file naming conventions and structures, versioning, and record management. 

Module 3: Analysis (57 minutes) 

We will discuss software and tools to prepare datasets for analysis. Then, we’ll discuss techniques for organizing data to find patterns. We’ll then move on to discuss sharing and reusing data, focusing on movements in open science, open access, and open data. 

Module 4: Preservation (65 minutes) 

We’ll discuss how data will be preserved and accessed for long-term use, including how retention requirements might differ depending on a funders’ policy. Within this framework, we’ll discuss intellectual property, copyright, and data ownership. Finally, we’ll discuss how to choose data for archiving. 

Wrap-Up Mini Module (20 minutes) 

In this mini module, we discuss HIPAA (Health Insurance Portability & Accountability Act), private health information (PHI), and techniques for ethical use of health information through de-identification of PHI. 

Refund Policy: Please note that the course price does not include Credit card processing fees. Users shall submit refund requests via email to noncredit@unmc.edu within 48 hours of the Course start date.