National Center for Data Services Webinar Series

NNLM National Center for Data Services.

Objectives
  1. Explain different types (e.g., data curation, data preservation) and levels (e.g., linking to resources, consulting, and collaborative) of research data management services
  2. Describe tools, resources, and workflows to facilitate reproducibility and replicability
  3. Advise researchers in best practices for data management planning
  4. Explain how to effectively document and describe research data
  5. Advise how to safely store, protect, and share medical research data

Continuing Education

Class Owner(s)

Contact the NNLM Training Office for more information.

Class Instructor(s)

Contact the NNLM Training Office for more information.

Classes

Event Title Event Start Date Summary Continuing Education Credits CE Categories Is Online Registration
From Data to Knowledge to Equitable Health Transformation in the Age of AI As we consider “Whose data is it, anyway?”, it is also critical to discuss what becomes of the knowledge generated from related data analyses and how that might promote health equity in today’s healthcare landscape. Recent revolutions in AI render such a discussion even more timely and imperative. 1.00 MLA, Data Services Specialization (DSS) Level 1 On
Greatest Crimes in Statistics Participants will learn about common pitfalls in statistics to look out for when reading scientific articles. Using a mix of lecture, discussion, and practice activities, participants will learn to identify misleading aspects of data visualizations, evidence of p-hacking, problems with pseudoreplication, and omissions in reporting of results. 1.00 MLA, Data Services Specialization (DSS) Level 1 On
Event Title Event Start Date Summary Continuing Education Credits CE Categories Is Online Registration
Love Data Week: All's FAIR in Love and ...Software This session will discuss the importance of biomedical research software, why they should be made reusable, and how this can be achieved by developers and managers of biomedical research software. We will cover the FAIR Principles for Research Software [Findability, Accessibility, Interoperability, and Reuse of digital assets]. 1.00 MLA On
Community Discussion: Addressing the NIH Data Management and Sharing Policy Session 2 The NNLM National Center for Data Services will be holding a series of interactive "Community Discussions'' about the upcoming NIH Data Management and Sharing Plan Requirements (effective January 25, 2023).

In these discussions, medical librarians and information professionals working in research data management will discuss challenges in addressing the National Institutes of Health Policy for Data Management and Sharing at their institutions. 		0.00 On
Cancelled. Analyzing Health on the Local Level: Accessing State and Regional Substance Use Data This workshop is part of National Recovery Month 2022.

National Recovery Month celebrates the gains made by those in recovery from substance use and mental health, just as we celebrate improvements made by individuals who are recovering from other health issues such as hypertension, diabetes, asthma, and heart disease are celebrated.

In this workshop, the presenter will provide information about how local and regional health departments share health data and how to make use of the data to see trends, inform practice, and develop or assess initiatives.

It is recommended that you make use of Microsoft Excel during the workshop; however, it is not required, and you can still participate without completing the hands-on activities. 		1.50 Certified Health Education Specialists (CHES), Data Services Specialization (DSS) Level 1 On
Community Discussion: Addressing the NIH Data Management and Sharing Policy Medical librarians and information professionals working in research data management will discuss challenges in addressing the National Institutes of Health Policy for Data Management and Sharing at their institutions.

This policy will go into effect January 25, 2023, and will impact research funded or conducted by NIH that results in the generation of scientific data. 		0.00 On