Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes
This interactive session covers overarching strategies for finding data sources. Instead of cycling through lists of data portals, sites, and sources, this class models inductive thinking about data itself: who provides it, who is responsible for gathering it, and who has an incentive to release it? Working with several prepared data searching questions, we will explore strategies for finding data available at NYU Libraries and beyond. Participants will be invited to submit their own data questions in advance of the session. Come prepared to converse with fellow data seekers about your process.
Software:

No software, although participants may want to create an account with ICPSR in advance
Duration: 60 min

Room description:

As our global pandemic continues, some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering
Prerequisites: None
Skills Taught / Learning Outcomes:
  • Identify data custodians and learn baseline strategies for finding data
  • Practice inductive reasoning skills in order to search for data effectively
  • Establish domain knowledge about the genres of data and industry standards for releasing data
  • Develop basic proficiency with locating codebooks and previewing data files
  • Cultivate the ability to identify measurable variables within a dataset and determine how they extend one's research question
Class Materials:
Related Classes:

Understanding Social Science Methods

Accessing U.S. Census Data
Additional Training Materials:

NYU Libraries Finding Data guide; Bobray Bordelon's data research guides (Princeton University); Reference Guide to Data Sources (2014)
Feedback: bit.ly/feedbackds

Upcoming sessions for this tutorial

Accessibility (opens in new window)