ReConstructor: A Scalable Constructive Visualization Tool

Constructive approaches to visualization authoring have been shown to offer advantages such as providing options for flexible outputs, scaffolding and ideation of new data mappings, personalized exploration of data, as well as supporting data understanding and literacy. However, visualization authoring tools based on a constructive approach do not scale well to larger datasets. As construction often involves manipulating small pieces of data and visuals, it requires a significant amount of time, effort, and repetitive steps. We present ReConstructor, an authoring tool in which a visualization is constructed by instantiating its structural and functional components through four interaction elements (objects, modifiers, activators, and tools). This design preserves most of the benefits of a constructive process while avoiding scalability issues by allowing designers to propagate individual mapping steps to all the elements of a visualization. We also discuss the perceived benefits of our approach and propose avenues for future research in this area.

[1]  Uta Hinrichs,et al.  Considering Agency and Data Granularity in the Design of Visualization Tools , 2018, CHI.

[2]  G. Stiny Kindergarten Grammars: Designing with Froebel's Building Gifts , 1980 .

[3]  M. Sheelagh T. Carpendale,et al.  Comparing Bar Chart Authoring with Microsoft Excel and Tangible Tiles , 2016, Comput. Graph. Forum.

[4]  Ramesh Sharda,et al.  Business Intelligence and Analytics , 2015 .

[5]  Jean Piaget,et al.  Child's Conception of Space: Selected Works vol 4 , 1998 .

[6]  M. Sheelagh T. Carpendale,et al.  Constructive visualization , 2014, Conference on Designing Interactive Systems.

[7]  Jakob Nielsen,et al.  Gestural interfaces: a step backward in usability , 2010, INTR.

[8]  E. Ackermann Piaget ’ s Constructivism , Papert ’ s Constructionism : What ’ s the difference ? , 2001 .

[9]  Mitchel Resnick,et al.  All I really need to know (about creative thinking) I learned (by studying how children learn) in kindergarten , 2007, C&C '07.

[10]  W. Cleveland,et al.  Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods , 1984 .

[11]  Jean-Daniel Fekete,et al.  Using VisKit: A Manual for Running a Constructive Visualization Workshop , 2016 .

[12]  Robert McGill,et al.  Graphical Perception: The Visual Decoding of Quantitative Information on Graphical Displays of Data , 1987 .

[13]  W. Hays Semiology of Graphics: Diagrams Networks Maps. , 1985 .

[14]  Bongshin Lee,et al.  ActiveInk: (Th)Inking with Data , 2019, CHI.

[15]  Mitchel Resnick,et al.  Extending Scratch: New pathways into programming , 2015, 2015 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC).

[16]  Michel Beaudouin-Lafon,et al.  Instrumental interaction: an interaction model for designing post-WIMP user interfaces , 2000, CHI.

[17]  John Maloney,et al.  The Scratch Programming Language and Environment , 2010, TOCE.

[18]  Uta Hinrichs,et al.  Bottom-up vs. Top-down: Trade-offs in Efficiency, Understanding, Freedom and Creativity with InfoVis Tools , 2017, CHI.

[19]  Eric Rosenbaum,et al.  Scratch: programming for all , 2009, Commun. ACM.

[20]  S. Greenberg,et al.  The Psychology of Everyday Things , 2012 .

[21]  Tovi Grossman,et al.  Object-Oriented Drawing , 2016, CHI.

[22]  M. Sheelagh T. Carpendale,et al.  Constructing Visual Representations: Investigating the Use of Tangible Tokens , 2014, IEEE Transactions on Visualization and Computer Graphics.

[23]  Ben Shneiderman,et al.  Direct Manipulation: A Step Beyond Programming Languages , 1983, Computer.

[24]  Seymour Papert,et al.  Mindstorms: Children, Computers, and Powerful Ideas , 1981 .

[25]  Miguel A. Nacenta,et al.  iVoLVER: Interactive Visual Language for Visualization Extraction and Reconstruction , 2016, CHI.

[26]  Jacques Bertin,et al.  Graphics and graphic information-processing , 1981 .