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CANCELED: Finding, Reusing, and Citing Data in Harvard Dataverse

CANCELED: Finding, Reusing, and Citing Data in Harvard Dataverse Online

 
Unfortunately, this class has been canceled. Please look for a rescheduled date.

 

Happy Love Data Week 2023 "Data: Agent of Change"

Finding data to reuse for your own research is often challenging because it can be widely distributed across a large number of different repositories and websites, it may not be described very well, and it can be difficult to evaluate whether data you have found is suitable for your research needs. In this session, we will explore Harvard Dataverse to learn more about searching in a data repository and reusing secondary data, including how to read metadata to better understand datasets and appropriately citing and resharing datasets you reuse in your own research.

Learning Objectives:

  • Apply general and Harvard Dataverse-specific data-finding principles to research strategies
  • Evaluate data on Harvard Dataverse suitable for reuse
  • Cite data according to best practices

Instructor: Katie Mika, Data Services Librarian, Harvard Library

Date:
Tuesday, February 14, 2023
Time:
12:00pm - 1:00pm
Time Zone:
Eastern Time - US & Canada (change)
Online:
This is an online event. Event URL will be sent via registration email.
Categories:
  Classes     Data Management  
Registration has closed.

 

Happy Love Data Week 2023 "Data: Agent of Change" February 13-17! 

Love Data Week is dedicated to spreading awareness of the importance of research data management, sharing, preservation, and reuse. We share practical tips, resources, and stories to help researchers use good data practices at any stage in their careers. Research data are the foundation of the scholarly record and crucial for advancing our knowledge of the world around us. If you care about research data, please join us!

Event Organizer

Profile photo of Julie Goldman
Julie Goldman

 

Need help with data management? Feel free to book a 30 minute meeting slot with me.

Happy to help with data organization, cleaning, and sharing for fostering reproducible workflows and open science!

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