[Colloquium] Andrew McNutt Candidacy Exam/Feb 10, 2022

[Megan Woodward]

This is an announcement of Andrew McNutt's Candidacy Exam.
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Candidate: Andrew McNutt

Date: Thursday, February 10, 2022

Time: 11 am CST

Remote Location: https://uchicago.zoom.us/j/96086631958?pwd=Y1RIc0hXZU1mU2NwNCtFMHFrZVhuQT09<https://urldefense.com/v3/__https://uchicago.zoom.us/j/96086631958?pwd=Y1RIc0hXZU1mU2NwNCtFMHFrZVhuQT09__;!!BpyFHLRN4TMTrA!vxnraiS4Lq1nwk_jC9CIQc21yCF5EyOfDPtjLLJmVTJr3EG6LB24tU5woMo6DTtalDRHLloy$>

Title: Understanding and Enhancing JSON-based DSLs for Visualization

Abstract: Static declarative domain specific languages represented by JSON are an increasingly common means by which to control a wide variety of types of systems. These range from database queries to application configuration to narrative generation to twitter bots to data visualization and to many other areas. These languages allow human users to concisely specify their intent through logic—and sometimes notation—that is relevant and matched to their task domain, as well as provide a means for computational agents to easily manipulate that form, allowing for powerful recommendation engines and automated analyses.

In this thesis we explore the design space of this form of textual interfaces and describe a suite of tools that improve the end user experience of these powerful tools. In particular, we investigate this space through four projects which variously consider how JSON DSLs are designed, how abstraction can be integrated into those languages, how interfaces can be designed to specifically facilitate their manipulation, as well as how those programs might be automatically validated. The through line of these projects is the assertion that treating these textual interfaces as first-class elements of visualization interface design is a valuable choice for end users. We primarily consider languages focused on various data visualization tasks, as there has been substantial work in the visualization research community on this form of interface—although the lessons learned could be applied to any relevant domain. Our initial findings suggest that there is substantial useful work that can be done through this lens and that interventions of the forms described are useful for helping end users learn, use, and re-use programs written in these languages.



Advisors: Ravi Chugh

Committee Members: Ravi Chugh, Blase Ur, and Arvind Satyanarayan
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