Automating the design of graphical presentations of relational information

By Jock D. Mackinlay. 1986

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Citations in the corpus

Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization (2011, background): “An example in the spirit of Mackinlay’s seminal analysis [36] helps to clarify the problem: if the original data has dimensionality n = 10 (still a quite low number) and the number of available visual parameters is k = 4 (e.”
Rethinking Visualization: A High-Level Taxonomy (2004, methodology): “Mackinlay [9] describes an automated method based on similar ideas, in which the system chooses the “optimal” visualization techniques.”
Visualization Rhetoric: Framing Effects in Narrative Visualization (2011, background): “Early theory emphasizes the analytic nature of graphical displays (e.g. [8]), as well as automated methods that optimize constraints imposed by human perceptual and cognitive abilities (e.g. [27]).”
ManyEyes: a Site for Visualization at Internet Scale (2007, background): “The well-known work of [15], parameterized the different visual encodings in visualizations, using them to automatically choose a meaningful visual representation for a given dataset.”
Milestones in the history of thematic cartography, statistica l graphics, and data visualization (2008, methodology): “1986 Automatic design of graphical presentations of relational data using a computational extention of Bertin’s semiology of graphics— Jock Mackinlay, Palo Alto, USA [179, 180].”
DataTone: Managing Ambiguity in Natural Language Interfaces for Data Visualization (2015, methodology): “However, solutions such as those described in APT [15] may be beneficial for ranking based on expressiveness and effusiveness criteria.”
From Visual Data Exploration to Visual Data Mining: A Survey (2003, methodology): “approaches for generating scientific visualizations have been conducted as part of attempts to automate the process and have been strongly influenced by the early work on APT—A Presentation Tool [64].”
Animated Transitions in Statistical Data Graphics (2007, background): “The resulting syntactic elements are determined by encoding operators, which map the semantic description to visual objects with properties such as position, size, shape, transparency, color hue, and value [14].”
Voyager 2: Augmenting Visual Analysis with Partial View Specifications (2017, methodology): “APT then uses a logic program that codiﬁes a set of expressiveness and effectiveness criteria inspired by Bertin [3] and Cleveland [7] to prune and rank visualizations.”
ReVision: automated classification, analysis and redesign of chart images (2011, methodology): “For analysts working with their own data, automated design methods [20, 21] based on visual design principles [6, 11, 16, 28] can lead to more effective visualizations.”
Protovis: A Graphical Toolkit for Visualization (2009, methodology): “Compare this to a system such as Polaris or Mackinlay's APT [22], which intelligently suggest meaningful designs based on metadata.”
Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations (2016, unknown): “Compass applies prior work by Cleveland [8] and Mackinlay [24] to rank the effectiveness of each visual channel based on a variable’s data type (Table 1).”
Show Me: Automatic Presentation for Visual Analysis (2007, methodology): “Mackinlay’s APT system is the foundational work on the automatic design of graphical presentations of relational information [7].”
Shape-changing interfaces: a review of the design space and open research questions (2012, background): “As an analogy, studies of graphical perception have long investigated the expressivity and accuracy of graphical marks (e.g., [14,28]).”
SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics (2015, background): “Examples include aesthetics (as explored in prior work [35, 19]), the particular attributes of the data being presented (our interactive tool allows analysts to choose attributes of interest) or other kinds of trends in data (for example, in some cases, a lack of deviation may be interesting).”