Literature DB >> 28866550

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization.

G Elisabeta Marai.   

Abstract

Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage-and its evaluation-of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature.

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Year:  2017        PMID: 28866550      PMCID: PMC5796424          DOI: 10.1109/TVCG.2017.2744459

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  20 in total

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Authors:  Jo Wood; Roger Beecham; Jason Dykes
Journal:  IEEE Trans Vis Comput Graph       Date:  2014-12       Impact factor: 4.579

2.  Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe.

Authors:  Timothy Basil Luciani; Brian Cherinka; Daniel Oliphant; Sean Myers; W Michael Wood-Vasey; Alexandros Labrinidis; G Elisabeta Marai
Journal:  IEEE Trans Vis Comput Graph       Date:  2014-07       Impact factor: 4.579

3.  A design space of visualization tasks.

Authors:  Hans-Jörg Schulz; Thomas Nocke; Magnus Heitzler; Heidrun Schumann
Journal:  IEEE Trans Vis Comput Graph       Date:  2013-12       Impact factor: 4.579

4.  Creative user-centered visualization design for energy analysts and modelers.

Authors:  Sarah Goodwin; Jason Dykes; Sara Jones; Iain Dillingham; Graham Dove; Alison Duffy; Alexander Kachkaev; Aidan Slingsby; Jo Wood
Journal:  IEEE Trans Vis Comput Graph       Date:  2013-12       Impact factor: 4.579

5.  RuleBender: a visual interface for rule-based modeling.

Authors:  Wen Xu; Adam M Smith; James R Faeder; G Elisabeta Marai
Journal:  Bioinformatics       Date:  2011-04-14       Impact factor: 6.937

6.  Visualization collaborations: what works and why.

Authors:  Robert M Kirby; Miriah Meyer
Journal:  IEEE Comput Graph Appl       Date:  2013 Nov-Dec       Impact factor: 2.088

7.  FixingTIM: interactive exploration of sequence and structural data to identify functional mutations in protein families.

Authors:  Timothy Luciani; John Wenskovitch; Koonwah Chen; David Koes; Timothy Travers; G Elisabeta Marai
Journal:  BMC Proc       Date:  2014-08-28

8.  Hierarchical model-based tracking of cervical vertebrae from dynamic biplane radiographs.

Authors:  Md Abedul Haque; William Anderst; Scott Tashman; G Elisabeta Marai
Journal:  Med Eng Phys       Date:  2012-10-31       Impact factor: 2.242

9.  MOSBIE: a tool for comparison and analysis of rule-based biochemical models.

Authors:  John E Wenskovitch; Leonard A Harris; Jose-Juan Tapia; James R Faeder; G Elisabeta Marai
Journal:  BMC Bioinformatics       Date:  2014-09-25       Impact factor: 3.169

10.  PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.

Authors:  Chihua Ma; Timothy Luciani; Anna Terebus; Jie Liang; G Elisabeta Marai
Journal:  BMC Bioinformatics       Date:  2017-02-15       Impact factor: 3.169

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  5 in total

1.  Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration.

Authors:  A Wentzel; P Hanula; T Luciani; B Elgohari; H Elhalawani; G Canahuate; D Vock; C D Fuller; G E Marai
Journal:  IEEE Trans Vis Comput Graph       Date:  2019-08-22       Impact factor: 4.579

2.  Details-First, Show Context, Overview Last: Supporting Exploration of Viscous Fingers in Large-Scale Ensemble Simulations.

Authors:  Timothy Luciani; Andrew Burks; Cassiano Sugiyama; Jonathan Komperda; G Elisabeta Marai
Journal:  IEEE Trans Vis Comput Graph       Date:  2018-08-20       Impact factor: 4.579

3.  THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy.

Authors:  Carla Floricel; Nafiul Nipu; Mikayla Biggs; Andrew Wentzel; Guadalupe Canahuate; Lisanne Van Dijk; Abdallah Mohamed; C David Fuller; G Elisabeta Marai
Journal:  IEEE Trans Vis Comput Graph       Date:  2021-12-24       Impact factor: 4.579

4.  A Tale of Two Centers: Visual Exploration of Health Disparities in Cancer Care.

Authors:  Sanjana Srabanti; Michael Tran; Virginie Achim; David Fuller; Guadalupe Canahuate; Fabio Miranda; G Elisabeta Marai
Journal:  IEEE Pac Vis Symp       Date:  2022-06-08

5.  Precision Risk Analysis of Cancer Therapy with Interactive Nomograms and Survival Plots.

Authors:  G Elisabeta Marai; Chihua Ma; Andrew Thomas Burks; Filippo Pellolio; Guadalupe Canahuate; David M Vock; Abdallah S R Mohamed; Clifton David Fuller
Journal:  IEEE Trans Vis Comput Graph       Date:  2018-03-20       Impact factor: 4.579

  5 in total

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