Class Type: Data Science

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RCR Session: NIH Data Management & Sharing Plans: Where to Share Data

This is a presentation on NIH's new Policy for Data Management and Sharing (DMS Policy) that went into effect January 25, 2023. This Policy requires NIH-funded researchers to prospectively submit a plan outlining how scientific data from their research will be managed and shared. The Policy includes an expectation that researchers will maximize their data sharing within ethical, legal, or technical constraints, and explicitly encourages researchers to incorporate data sharing via deposit into a public repository into their standard research process. This session will focus on selecting a repository appropriate to their research discipline and data type for sharing data in compliance with the policy.

All of Us Researcher Workbench - EHR and Survey Data Analysis

In this workshop, you will learn how to create a project using concept sets, datasets, and workbooks, and discover how to use code snippets to accomplish more advanced tasks. You'll explore the full potential of the All of Us Researcher Workbench, gain practical skills in creating a project from start to finish, and learn how to use code snippets to enhance your research capabilities. Whether you're a new user of the All of Us Researcher Workbench or an experienced one, this workshop will provide valuable insights into leveraging the platform to meet your research needs.

All of Us Researcher Workbench - Terminology and Data Models Training

In this workshop, we will introduce the notion of concept sets and their role in observational research with Electronic Health Record (EHR) data. Whether you're a new user of the All of Us Researcher Workbench or an experienced one, this workshop will provide valuable insights into leveraging the platform to meet your research needs.

Agenda:

  • Introductory materials
  • Preliminary test of access
  • Health research use case of interest
  • Getting the featured workspaces working in your environment
  • The basic workflow for cohort and dataset creation
  • What happens next - "the usability cliff!"
  • Understanding the data model that holds AoU data
  • Workbooks to help you learn
  • A tour of the common data model, vocabulary, and workflow
  • Saving artifacts and reloading them

Introduction to All of Us Researcher Workbench

Join us for a class on the All of Us Researchers Workbench - a cloud-based platform that provides researchers with access to data generated by the All of Us Research Program (AoURP). Led by the National Institutes of Health, AoURP is a longitudinal cohort study to advance precision medicine and improve human health by partnering with one million or more diverse participants across the United States. Whether you're new to the platform or an experienced user, this class will provide valuable insights into leveraging the All of Us Researcher Workbench for your research needs.

When Seeing Isn’t Believing: Identifying Visual Health Misinformation

Discussion of health literacy and the fight against health misinformation often centers around fact-checking or debunking written materials. However, identifying misleading visualizations and imagery is also a vital skill for navigating the current health information landscape. This interactive session will give you a variety of skills to analyze visual information. Deceptive imagery types covered will include graphs and charts, manipulated images in scientific publications, out-of-context images, and AI-generated imagery.

Data Wrangling in R

This is a flipped class covering the more advanced topics in R programming for data analysis and the second part of a three-part series: Introduction to R; Data Wrangling in R, and Data Visualization in R. Upon registration, you will receive links to workshop materials (PowerPoint slides, lecture videos, and practice exercises) that you can view on your own schedule. During the hands-on in-person session, you will learn how to solve the exercise problems. 

If you need a refresher, please complete the lessons covered in the first part available via the workshop guide

Introduction to R

This workshop adopts a flipped classroom model, providing you with access to PowerPoint slides, lecture videos, and practice exercises in the workshop guide for self-paced learning. During the class, you will have the opportunity to solve exercise problems with guidance from the instructor. This is the first part of a three-part series: Introduction to R; Data Management in R, and Data Visualization in R.

Target Audience:

Novice R users or anyone seeking to learn how to use R for data analysis and graphics. Neither programming experience nor familiarity with R is required.

The NIH Policy for Data Management & Sharing: Catalog vs. Repository for Restricted Datasets

NIH's new Policy for Data Management and Sharing (DMS Policy) went into effect January 25, 2023, and requires NIH-funded researchers to prospectively submit a plan outlining how scientific data from their research will be managed and shared.

While broad sharing may not feasible for all datasets, steps can still be taken to share information about the dataset including a description and instructions for restricted access.

Audience: Any researcher interested in preparing for the NIH Data Management & Sharing Plan requirements.

NIH Data Management & Sharing Plans: Documentation, Metadata, and the "How" of Deposit

This is a presentation on NIH's new Policy for Data Management and Sharing (DMS Policy) that went into effect January 25, 2023. This Policy requires NIH-funded researchers to prospectively submit a plan outlining how scientific data from their research will be managed and shared. The Policy includes an expectation that researchers will maximize their data sharing within ethical, legal, or technical constraints, and explicitly encourages researchers to incorporate data sharing via deposit into a public repository into their standard research process. This session will focus on the pieces of information that will help other researchers find and reuse your data: metadata and documentation like READMEs, data dictionaries, and user manuals.

NIH Data Management & Sharing Plans: Where to Share Data

This is a presentation on NIH's new Policy for Data Management and Sharing (DMS Policy) that went into effect January 25, 2023. This Policy requires NIH-funded researchers to prospectively submit a plan outlining how scientific data from their research will be managed and shared. The Policy includes an expectation that researchers will maximize their data sharing within ethical, legal, or technical constraints, and explicitly encourages researchers to incorporate data sharing via deposit into a public repository into their standard research process. This session will focus on selecting a repository appropriate to their research discipline and data type for sharing data in compliance with the policy.