pith. sign in

arxiv: 1907.08345 · v2 · pith:QOBYMENGnew · submitted 2019-07-19 · 💻 cs.HC

Liger: Combining Interaction Paradigms for Visual Analysis

Pith reviewed 2026-05-24 19:26 UTC · model grok-4.3

classification 💻 cs.HC
keywords interaction paradigmsvisualization toolsuser studymanual view specificationvisualization by demonstrationmulti-paradigm interfaceexploratory study
0
0 comments X

The pith

Users of a combined visualization tool switch between manual view specification and visualization by demonstration interchangeably and mix them for single operations.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Visualization tools have long relied on one interaction paradigm at a time. This paper built Liger, a single mouse-based prototype that unites manual view specification with visualization by demonstration. An exploratory study with the tool produced initial evidence that participants used both approaches interchangeably, switched based on the operation at hand, and completed some operations by blending the two. The work matters because it moves beyond comparing isolated paradigms to showing how their combination can be used in practice.

Core claim

By creating the Liger prototype that merges manual view specification and visualization by demonstration and then running an exploratory study, the authors show that people use both paradigms interchangeably, switch seamlessly depending on the operation, and choose to complete single operations successfully through a combination of both.

What carries the argument

Liger, the multi-paradigm prototype that integrates manual view specification and visualization by demonstration into one unified mouse-based interface.

Load-bearing premise

The Liger prototype combines the two paradigms without introducing implementation-specific artifacts that change how users behave, and the study participants and tasks represent broader user populations.

What would settle it

A follow-up study with the same or equivalent tool in which participants never switch paradigms or never mix them for any operation would contradict the central claim.

Figures

Figures reproduced from arXiv: 1907.08345 by Alex Endert, Bahador Saket, Charles Perin, Lei Jiang.

Figure 1
Figure 1. Figure 1: The processes for constructing visualizations using Manual View [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: A possible implementation of VbD. Here, a user directly manipu [PITH_FULL_IMAGE:figures/full_fig_p002_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Liger consists of the following elements. The Show Me Menu shows the types of visualizations the tool supports. The Attribute Panel shows the data schema, listing all attributes in the dataset. The Filter Panel shows user-specified filters. Filters are created through drag and drop of data attributes or data points into the panel. The Recommendation Panel shows suggestions made by the system in response to… view at source ↗
Figure 6
Figure 6. Figure 6: Amy colors a few 4-cylinder cars red and a few 8-cylinder cars blue [PITH_FULL_IMAGE:figures/full_fig_p004_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Amy creates a filter to filter out European and American cars [PITH_FULL_IMAGE:figures/full_fig_p004_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Amy draws a rubber-band rectangle to select cars with low [PITH_FULL_IMAGE:figures/full_fig_p004_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The operations participants performed during the [PITH_FULL_IMAGE:figures/full_fig_p007_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: The number of times participants performed each operation [PITH_FULL_IMAGE:figures/full_fig_p008_10.png] view at source ↗
read the original abstract

Visualization tools usually leverage a single interaction paradigm (e.g., manual view specification, visualization by demonstration, etc.), which fosters the process of visualization construction. A large body of work has investigated the effectiveness of individual interaction paradigms, building an understanding of advantages and disadvantages of each in isolation. However, how can we leverage the benefits of multiple interaction paradigms by combining them into a single tool? We currently lack a holistic view of how interaction paradigms that use the same input modality (e.g., mouse) can be combined into a single tool and how people use such tools. To investigate opportunities and challenges in combining paradigms, we first created a multi-paradigm prototype (Liger) that combines two mouse-based interaction paradigms (manual view specification and visualization by demonstration) in a unified tool. We then conducted an exploratory study with Liger, providing initial evidence that people 1) use both paradigms interchangeably, 2) seamlessly switch between paradigms based on the operation at hand, and 3) choose to successfully complete a single operation using a combination of both paradigms.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The paper introduces Liger, a prototype tool that combines two mouse-based interaction paradigms—manual view specification and visualization by demonstration—into a single visualization interface. It reports results from an exploratory study providing initial evidence that users (1) employ both paradigms interchangeably, (2) switch seamlessly between them depending on the operation, and (3) combine both paradigms to complete individual operations.

Significance. If the reported behaviors are shown to generalize beyond the specific prototype and tasks, the work could inform the design of more flexible visualization systems that integrate multiple interaction paradigms to leverage their respective strengths.

major comments (2)
  1. [Exploratory Study section] Exploratory Study section: the abstract claims 'initial evidence' for the three usage behaviors but reports no details on participant count, task set, coding scheme for identifying seamless switches, analysis methods, or any single-paradigm baseline conditions. These omissions are load-bearing for the central claims, as the behaviors cannot be assessed for validity or generalizability without this information.
  2. [Liger Prototype section] Liger Prototype section: the manuscript does not address or test whether observed behaviors arise from the paradigm combination itself or from implementation-specific artifacts in Liger (e.g., UI layout, feedback mechanisms), which is required to support the interpretation that the behaviors reflect multi-paradigm use rather than prototype idiosyncrasies.

Simulated Author's Rebuttal

2 responses · 0 unresolved

Thank you for the constructive feedback. We address each major comment below, proposing revisions to improve clarity and transparency around the exploratory nature of the study.

read point-by-point responses
  1. Referee: [Exploratory Study section] Exploratory Study section: the abstract claims 'initial evidence' for the three usage behaviors but reports no details on participant count, task set, coding scheme for identifying seamless switches, analysis methods, or any single-paradigm baseline conditions. These omissions are load-bearing for the central claims, as the behaviors cannot be assessed for validity or generalizability without this information.

    Authors: We agree that the current manuscript under-reports key study details needed to evaluate the strength of the initial evidence. In revision we will expand the Exploratory Study section with participant count, full task descriptions, the coding scheme for switches, and analysis methods. The study was not designed with single-paradigm baseline conditions; we will explicitly state this design choice and its implications as a limitation. revision: yes

  2. Referee: [Liger Prototype section] Liger Prototype section: the manuscript does not address or test whether observed behaviors arise from the paradigm combination itself or from implementation-specific artifacts in Liger (e.g., UI layout, feedback mechanisms), which is required to support the interpretation that the behaviors reflect multi-paradigm use rather than prototype idiosyncrasies.

    Authors: We acknowledge the point: without controls or comparisons the source of the behaviors cannot be isolated. As an exploratory study our intent was to observe usage in a combined interface rather than attribute causality. We will add explicit discussion of this limitation in the Prototype and Discussion sections and frame the results as observations that motivate future controlled experiments. revision: partial

Circularity Check

0 steps flagged

No significant circularity: empirical exploratory study with no derivations or self-referential constructions

full rationale

The paper presents an exploratory user study of a prototype tool (Liger) that combines two interaction paradigms. Its central claims rest on observed participant behaviors during the study rather than any mathematical derivation, fitted parameters, equations, or load-bearing self-citations. No section invokes uniqueness theorems, renames known results, or treats a fitted input as a prediction. The study description is self-contained against external benchmarks because it reports direct observations without reducing claims to prior author work by construction. This is the expected outcome for an empirical HCI paper whose evidence is participant data, not a closed logical chain.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 1 invented entities

As an HCI prototype and user study paper, there are no free parameters, mathematical axioms, or new physical entities. The main addition is the integrated tool and observational data from the study.

invented entities (1)
  • Liger no independent evidence
    purpose: A unified prototype tool combining manual view specification and visualization by demonstration
    Liger is the central artifact introduced to enable the study, but its design choices and effectiveness rest only on the reported exploratory observations with no independent evidence outside the paper.

pith-pipeline@v0.9.0 · 5716 in / 1224 out tokens · 29994 ms · 2026-05-24T19:26:57.050618+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

50 extracted references · 50 canonical work pages

  1. [1]

    Tableau Software, http://www.tableau.com/, 2018

  2. [2]

    C. Ahlberg. Spotfire: an information exploration environment. ACM SIGMOD Record, 25(4):25–29, 1996

  3. [3]

    Analytics

    W. Analytics. https://www.ibm.com/watson-analytics

  4. [4]

    Beaudouin-Lafon

    M. Beaudouin-Lafon. Instrumental interaction: an interaction model for designing post-wimp user interfaces. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems, pp. 446–453. ACM, 2000

  5. [5]

    Bostock, V

    M. Bostock, V . Ogievetsky, and J. Heer. D 3: Data-driven documents. IEEE Trans. Visualization & Comp. Graphics, 17(12):2301–2309, 2011

  6. [6]

    S. K. Card, J. D. Mackinlay, and B. Shneiderman, eds. Readings in Information Visualization: Using Vision to Think . Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1999

  7. [7]

    M. S. T. Carpendale. A Framework for Elastic Presentation Space. PhD thesis, Burnaby, BC, Canada, Canada, 1999. AAINQ51848

  8. [8]

    E. H.-h. Chi and J. Riedl. An operator interaction framework for visualiza- tion systems. In Proceedings of the 1998 IEEE Symposium on Information Visualization, INFOVIS ’98, pp. 63–70. IEEE Computer Society, Wash- ington, DC, USA, 1998

  9. [9]

    Cypher and D

    A. Cypher and D. C. Halbert. Watch what I do: programming by demon- stration. MIT press, 1993

  10. [10]

    Datasets

    T. Datasets. https://public.tableau.com/s/resources, 2015

  11. [11]

    Dix and G

    A. Dix and G. Ellis. Starting simple: Adding value to static visualisation through simple interaction. In Proceedings of the Working Conference on Advanced Visual Interfaces, A VI ’98, pp. 124–134. ACM, New York, NY , USA, 1998. doi: 10.1145/948496.948514

  12. [12]

    Grammel, C

    L. Grammel, C. Bennett, M. Tory, and M.-A. Storey. A survey of visu- alization construction user interfaces. EuroVis-Short Papers, pp. 19–23, 2013

  13. [13]

    Grammel, M

    L. Grammel, M. Tory, and M.-A. Storey. How information visualization novices construct visualizations. IEEE Transactions on Visualization and Computer Graphics, 16(6):943–952, Nov 2010

  14. [14]

    J. Grudin. The case against user interface consistency. Commun. ACM, 32(10):1164–1173, Oct. 1989. doi: 10.1145/67933.67934

  15. [15]

    H. V . Henderson and P. F. Velleman. Building multiple regression models interactively. Biometrics, pp. 391–411, 1981

  16. [16]

    Hinrichs and S

    U. Hinrichs and S. Forlini. In defense of sandcastles: Research thinking through visualization in dh. In Proceedings of the conference on Digital Humanities, 2017

  17. [17]

    Huron, S

    S. Huron, S. Carpendale, A. Thudt, A. Tang, and M. Mauerer. Constructive visualization. In Proceedings of the Conference on Designing Interactive Systems, DIS ’14, pp. 433–442. ACM, New York, NY , USA, 2014

  18. [18]

    Igarashi and J

    T. Igarashi and J. F. Hughes. A suggestive interface for 3d drawing. In Proceedings of the Symposium on User Interface Software and Technology, UIST ’01, pp. 173–181. ACM, New York, NY , USA, 2001

  19. [19]

    Kahneman

    D. Kahneman. Thinking, fast and slow. Farrar, Straus and Giroux, New York, 2011

  20. [20]

    N. W. Kim, E. Schweickart, Z. Liu, M. Dontcheva, W. Li, J. Popovic, and H. Pfister. Data-driven guides: Supporting expressive design for information graphics. IEEE Transactions on Visualization and Computer Graphics, 23(1):491–500, Jan 2017. doi: 10.1109/TVCG.2016.2598620

  21. [21]

    H. Lam. A framework of interaction costs in information visualization. IEEE transactions on visualization and computer graphics, 14(6), 2008

  22. [22]

    J. Lin, J. Wong, J. Nichols, A. Cypher, and T. A. Lau. End-user pro- gramming of mashups with vegemite. In Proceedings of the International Conference on Intelligent User Interfaces , IUI ’09, pp. 97–106. ACM, New York, NY , USA, 2009

  23. [23]

    Z. Liu, J. Thompson, A. Wilson, M. Dontcheva, J. Delorey, S. Grigg, B. Kerr, and J. Stasko. Data Illustrator: Augmenting Vector Design Tools with Lazy Data Binding for Expressive Visualization Authoring. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, CHI ’18, pp. 123:1–123:13. ACM, New York, NY , USA, 2018

  24. [24]

    G. G. M´endez, U. Hinrichs, and M. A. Nacenta. Bottom-up vs. top-down: Trade-offs in efficiency, understanding, freedom and creativity with infovis tools. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI ’17, pp. 841–852. ACM, New York, USA, 2017

  25. [25]

    G. G. M´endez, M. A. Nacenta, and U. Hinrichs. Considering agency and data granularity in the design of visualization tools. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, CHI ’18, pp. 638:1–638:14. ACM, New York, NY , USA, 2018

  26. [26]

    Nissen and J

    B. Nissen and J. Bowers. Data-things: Digital fabrication situated within participatory data translation activities. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI ’15, pp. 2467–2476. ACM, New York, NY , USA, 2015

  27. [27]

    D. A. Norman. Things that make us smart: defending human attributes in the age of the machine. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1993

  28. [28]

    D. A. Norman. The design of everyday things: Revised and expanded edition. Basic books, 2013

  29. [29]

    Perin, P

    C. Perin, P. Dragicevic, and J. D. Fekete. Revisiting bertin matrices: New interactions for crafting tabular visualizations. IEEE Transactions on Visualization and Computer Graphics, 20(12):2082–2091, Dec 2014

  30. [30]

    Polestart, http://vega.github.io/polestar/, 2016

    PoleStar. Polestart, http://vega.github.io/polestar/, 2016

  31. [31]

    E. D. Ragan, A. Endert, D. A. Bowman, and F. Quek. The effects of spatial layout and view control on cognitive processing. In CHI ’11 Extended Abstracts on Human Factors in Computing Systems , CHI EA ’11, pp. 2005–2010. ACM, New York, NY , USA, 2011

  32. [32]

    D. Ren, B. Lee, and M. Brehmer. Charticulator: Interactive construction of bespoke chart layouts. IEEE Transactions on Visualization and Computer Graphics, 25(1):789–799, Jan 2019. doi: 10.1109/TVCG.2018.2865158

  33. [33]

    L. Ren, J. Cui, Y . Du, and G. Dai. Multilevel interaction model for hierarchical tasks in information visualization. In Proceedings of the 6th International Symposium on Visual Information Communication and Interaction, VINCI ’13, pp. 11–16. ACM, New York, NY , USA, 2013

  34. [34]

    Saket and A

    B. Saket and A. Endert. Demonstrational interaction for data visualization. IEEE Computer Graphics and Applications, 39(3):67–72, May 2019. doi: 10.1109/MCG.2019.2903711

  35. [35]

    Saket and A

    B. Saket and A. Endert. Evaluation of visualization by demonstration and manual view specification. Computer Graphics Forum (Proc. EuroVis), 2019, To Appear

  36. [36]

    Saket, S

    B. Saket, S. Huron, C. Perin, and A. Endert. Investigating direct manip- ulation of graphical encodings as a method for user interaction. IEEE Transactions on Visualization and Computer Graphics, To Appear, 2019

  37. [37]

    Saket, H

    B. Saket, H. Kim, E. T. Brown, and A. Endert. Visualization by demon- stration: An interaction paradigm for visual data exploration. IEEE Trans- actions on Visualization and Computer Graphics , 23(1):331–340, Jan 2017

  38. [38]

    Saket, A

    B. Saket, A. Srinivasan, E. D. Ragan, and A. Endert. Evaluating inter- active graphical encodings for data visualization. IEEE Transactions on Visualization and Computer Graphics, 24(3):1316–1330, 2018

  39. [39]

    Schwartz

    B. Schwartz. The paradox of choice: Why more is less , vol. 6. Harper- Collins New York, 2004

  40. [40]

    F. M. Shipman III and C. C. Marshall. Formality considered harmful: Experiences, emerging themes, and directions on the use of formal repre- sentations in interactive systems. Computer Supported Cooperative Work (CSCW), 8(4):333–352, 1999

  41. [41]

    Shneiderman

    B. Shneiderman. The eyes have it: A task by data type taxonomy for in- formation visualizations. In Proceedings of the 1996 IEEE Symposium on Visual Languages, VL ’96, pp. 336–. IEEE Computer Society, Washington, DC, USA, 1996

  42. [42]

    Srinivasan, M

    A. Srinivasan, M. Dontcheva, E. Adar, and S. Walker. Discovering natural language commands in multimodal interfaces. In Proceedings of the 24th International Conference on Intelligent User Interfaces, IUI ’19, pp. 661–672. ACM, New York, NY , USA, 2019

  43. [43]

    Stolte and P

    C. Stolte and P. Hanrahan. Polaris: A system for query, analysis and visualization of multi-dimensional relational databases. In Proceedings of the IEEE Symposium on Information Vizualization 2000, INFOVIS ’00, pp. 5–14. IEEE Computer Society, Washington, DC, USA, 2000

  44. [44]

    Tobiasz, P

    M. Tobiasz, P. Isenberg, and S. Carpendale. Lark: Coordinating co- located collaboration with information visualization. IEEE Transactions on Visualization and Computer Graphics, 15(6):1065–1072, Nov. 2009

  45. [45]

    M. Turk. Multimodal interaction: A review. Pattern Recognition Letters, 36:189–195, 2014

  46. [46]

    Vermeulen, K

    J. Vermeulen, K. Luyten, E. van den Hoven, and K. Coninx. Crossing the bridge over norman’s gulf of execution: Revealing feedforward’s true identity. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’13, pp. 1931–1940. ACM, NY , USA, 2013

  47. [47]

    F. B. Viegas, M. Wattenberg, F. Van Ham, J. Kriss, and M. McKeon. Manyeyes: a site for visualization at internet scale. Visualization and Computer Graphics, IEEE Transactions on, 13(6):1121–1128, 2007

  48. [48]

    Wongsuphasawat, Z

    K. Wongsuphasawat, Z. Qu, D. Moritz, R. Chang, F. Ouk, A. Anand, J. Mackinlay, B. Howe, and J. Heer. V oyager 2: Augmenting visual analysis with partial view specifications. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI ’17, pp. 2648–2659. ACM, New York, NY , USA, 2017

  49. [49]

    J. S. Yi, Y . A. Kang, and J. Stasko. Toward a deeper understanding of the role of interaction in information visualization. IEEE Transactions on Visualization and Computer Graphics, 13(6):1224–1231, Nov 2007

  50. [50]

    M. M. Zloof. Query by example. InAFIPS National Computer Conference, 1975