Supporting Expert Close Analysis of Historical Scientific Writings: A Case Study for Near-by Reading

McNutt, Andrew; Kim, Agatha; Elahi, Sergio; Takahashi, Kazutaka

doi:10.1109/vis4dh51463.2020.00005

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Bridging these introspective and automatic methods, McNutt and Kim [240] describe a method based on the humanistic practice of close reading, augmented by computational measurement (in the manner of digital humanities-style distant reading). They go on to apply [172] this method to as a way to comparison of the writings of 19th century naturalists in France.…”

Section: Existing Visual Analytics Testing Toolsmentioning

confidence: 99%

“…Throughout this work, we utilized Cognitive Dimensions of Notation [114] (as do many other works) to consider our designs-which aligns with the growing trend [31,316,418] of using them as an aspect of evaluation. However, this is not the original intent of this methodology, so a formal treatment through the lens of close (or nearby [240]) reading would likely raise the quality and rigor of many works in this stream.…”

Section: Future Workmentioning

confidence: 99%

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Understanding and Enhancing JSON-based DSL Interfaces for Visualization

McNutt¹

2023

Preprint

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Domain-specific languages represented in data serialization formats (such as Javascript Object Notation or JSON) are an increasingly common means to control numerous systems.These range from database queries to application configuration, narrative generation, Twitter bots, data visualization, and many other areas.These languages allow potentially unsophisticated human users to concisely specify their intent through logic and notation that is relevant to task domain.Further, they provide a means for computational agents to easily manipulate that form, allowing for powerful recommendation engines and systems of automated analyses.In this thesis, we consider how end-user agency might be enhanced and maintained through the design of tools that support these domain-specific languages, as well as through the study of the design of the languages themselves.In support of this goal, we conducted four interconnected projects which variously study how JSON-based 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.Through these projects, we demonstrate that giving primacy to these textual interfaces as design elements can be valuable for end users.We find that this style of interventions are useful for helping end users learn, use, and re-use programs written in these languages.We primarily consider languages focused on 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.

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Section: Existing Visual Analytics Testing Toolsmentioning

confidence: 99%