This course will be offered online only. It will not be recorded as there are in-class activities. This course will begin at 10am—those who need assistance prior to the course can arrive or log on at 9am for an accessory hour.

Description: This is a full-day, intensive, online interactive course focused on using the Dataverse Application Programming Interface (API) to interact with data archived in a Dataverse-based repository. The session will be broken into to two segments over the course of the day: 1) we will cover the basics of what an API is, how it works, and what it is used for, all set in terms of the Dataverse platform; and 2) will cover practical examples for programming with the Dataverse API using R, Python, and JavaScript (Node).

Participants will have the opportunity to work hands-on with writing simple code that they will be able to build on. The goal of the course is to give participants the basic tools needed to begin to automate self-deposit to a Dataverse data repository, but also for retrieving data for secondary analysis and other reuse.

Learning Objectives

• Understand Application Programming Interfaces (APIs), routes, and endpoints as part of a data archiving and reuse/secondary analysis workflow.
• Become familiar with some of the methods available through the Dataverse API that are analogous to functions that can be performed using the web interface, as well as some that are ONLY available using the API.
• Understand how to read API documentation and make requests against endpoints.
• Understand how to incorporate API calls into your data cleaning and analysis code and help you better prepare data packages for deposit in a public data repository.
• Be regarded as a data wizard by your colleagues.

Take-away: Working through an API allows your code to interact directly with a system or platform to perform import, export, and other functions without having to manually download or upload information through the web-based user interface. This allows for more secure data transfer, decreased possibility for human error in data analysis, organization, management, archiving, etc., and better overall replicability through your data workflow.

NB: For one hour before the advertised start time, we will hold an open session for you to join us and get assistance with setting up your system, installing the software you need, etc. Details and software requirements will be sent by the instructor to registered participants one week before the course date.

Instructor

John D. Martin III is the Research Data Systems Archivist at the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. He works with both the Data Archive and the Research Data Information Systems teams to support and develop technical data management infrastructure and envision its future at UNC. He has a background in system administration and programming in addition to archives, research development, and pedagogy.

John's research is in critical research methodology and focuses on trust and credibility in interfaces, systems, and other intermediaries that facilitate information exchange and transfer between people. He received his PhD from UNC's School of Information and Library Science and his MA in Arabic and Islamic Studies from the American University in Cairo.

Registration

UNC Chapel Hill Students: $0, with a $35 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
UNC Chapel Hill Faculty/Staff/Postdoc/Resident/Visiting Scholars: $80
Non-UNC Chapel Hill University Student/Employee (must have active university email): $105
Government/Non-Profit/Corporate: $130

Registration will close at 12:01am 11/14/2023. No late registrations will be accepted.

Zoom link will be sent prior to the course. Registration must be made at least 3 days prior to the course date to receive the Zoom link.

register

Questions regarding these classes? Contact Jill Stevens at This email address is being protected from spambots. You need JavaScript enabled to view it..

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