27,310 research outputs found
On Regulatory and Organizational Constraints in Visualization Design and Evaluation
Problem-based visualization research provides explicit guidance toward
identifying and designing for the needs of users, but absent is more concrete
guidance toward factors external to a user's needs that also have implications
for visualization design and evaluation. This lack of more explicit guidance
can leave visualization researchers and practitioners vulnerable to unforeseen
constraints beyond the user's needs that can affect the validity of
evaluations, or even lead to the premature termination of a project. Here we
explore two types of external constraints in depth, regulatory and
organizational constraints, and describe how these constraints impact
visualization design and evaluation. By borrowing from techniques in software
development, project management, and visualization research we recommend
strategies for identifying, mitigating, and evaluating these external
constraints through a design study methodology. Finally, we present an
application of those recommendations in a healthcare case study. We argue that
by explicitly incorporating external constraints into visualization design and
evaluation, researchers and practitioners can improve the utility and validity
of their visualization solution and improve the likelihood of successful
collaborations with industries where external constraints are more present.Comment: 9 pages, 2 figures, presented at BELIV workshop associated with IEEE
VIS 201
Parallel Hierarchies: Interactive Visualization of Multidimensional Hierarchical Aggregates
Exploring multi-dimensional hierarchical data is a long-standing problem present in a wide range of fields such as bioinformatics, software systems, social sciences and business intelligence. While each hierarchical dimension within these data structures can be explored in isolation, critical information lies in the relationships between dimensions. Existing approaches can either simultaneously visualize multiple non-hierarchical dimensions, or only one or two hierarchical dimensions. Yet, the challenge of visualizing multi-dimensional hierarchical data remains open.
To address this problem, we developed a novel data visualization approach -- Parallel Hierarchies -- that we demonstrate on a real-life SAP SE product called SAP Product Lifecycle Costing. The starting point of the research is a thorough customer-driven requirement engineering phase including an iterative design process. To avoid restricting ourselves to a domain-specific solution, we abstract the data and tasks gathered from users, and demonstrate the approach generality by applying Parallel Hierarchies to datasets from bioinformatics and social sciences. Moreover, we report on a qualitative user study conducted in an industrial scenario with 15 experts from 9 different companies. As a result of this co-innovation experience, several SAP customers requested a product feature out of our solution. Moreover, Parallel Hierarchies integration as a standard diagram type into SAP Analytics Cloud platform is in progress.
This thesis further introduces different uncertainty representation methods applicable to Parallel Hierarchies and in general to flow diagrams. We also present a visual comparison taxonomy for time-series of hierarchically structured data with one or multiple dimensions. Moreover, we propose several visual solutions for comparing hierarchies employing flow diagrams.
Finally, after presenting two application examples of Parallel Hierarchies on industrial datasets, we detail two validation methods to examine the effectiveness of the visualization solution. Particularly, we introduce a novel design validation table to assess the perceptual aspects of eight different visualization solutions including Parallel Hierarchies.:1 Introduction
1.1 Motivation and Problem Statement
1.2 Research Goals
1.3 Outline and Contributions
2 Foundations of Visualization
2.1 Information Visualization
2.1.1 Terms and Definition
2.1.2 What: Data Structures
2.1.3 Why: Visualization Tasks
2.1.4 How: Visualization Techniques
2.1.5 How: Interaction Techniques
2.2 Visual Perception
2.2.1 Visual Variables
2.2.2 Attributes of Preattentive and Attentive Processing
2.2.3 Gestalt Principles
2.3 Flow Diagrams
2.3.1 Classifications of Flow Diagrams
2.3.2 Main Visual Features
2.4 Summary
3 Related Work
3.1 Cross-tabulating Hierarchical Categories
3.1.1 Visualizing Categorical Aggregates of Item Sets
3.1.2 Hierarchical Visualization of Categorical Aggregates
3.1.3 Visualizing Item Sets and Their Hierarchical Properties
3.1.4 Hierarchical Visualization of Categorical Set Aggregates
3.2 Uncertainty Visualization
3.2.1 Uncertainty Taxonomies
3.2.2 Uncertainty in Flow Diagrams
3.3 Time-Series Data Visualization
3.3.1 Time & Data
3.3.2 User Tasks
3.3.3 Visual Representation
3.4 Summary
ii Contents
4 Requirement Engineering Phase
4.1 Introduction
4.2 Environment
4.2.1 The Product
4.2.2 The Customers and Development Methodology
4.2.3 Lessons Learned
4.3 Visualization Requirements for Product Costing
4.3.1 Current Visualization Practice
4.3.2 Visualization Tasks
4.3.3 Data Structure and Size
4.3.4 Early Visualization Prototypes
4.3.5 Challenges and Lessons Learned
4.4 Data and Task Abstraction
4.4.1 Data Abstraction
4.4.2 Task Abstraction
4.5 Summary and Outlook
5 Parallel Hierarchies
5.1 Introduction
5.2 The Parallel Hierarchies Technique
5.2.1 The Individual Axis: Showing Hierarchical Categories
5.2.2 Two Interlinked Axes: Showing Pairwise Frequencies
5.2.3 Multiple Linked Axes: Propagating Frequencies
5.2.4 Fine-tuning Parallel Hierarchies through Reordering
5.3 Design Choices
5.4 Applying Parallel Hierarchies
5.4.1 US Census Data
5.4.2 Yeast Gene Ontology Annotations
5.5 Evaluation
5.5.1 Setup of the Evaluation
5.5.2 Procedure of the Evaluation
5.5.3 Results from the Evaluation
5.5.4 Validity of the Evaluation
5.6 Summary and Outlook
6 Visualizing Uncertainty in Flow Diagrams
6.1 Introduction
6.2 Uncertainty in Product Costing
6.2.1 Background
6.2.2 Main Causes of Bad Quality in Costing Data
6.3 Visualization Concepts
6.4 Uncertainty Visualization using Ribbons
6.4.1 Selected Visualization Techniques
6.4.2 Study Design and Procedure
6.4.3 Results
6.4.4 Discussion
6.5 Revised Visualization Approach using Ribbons
6.5.1 Application to Sankey Diagram
6.5.2 Application to Parallel Sets
6.5.3 Application to Parallel Hierarchies
6.6 Uncertainty Visualization using Nodes
6.6.1 Visual Design of Nodes
6.6.2 Expert Evaluation
6.7 Summary and Outlook
7 Visual Comparison Task
7.1 Introduction
7.2 Comparing Two One-dimensional Time Steps
7.2.1 Problem Statement
7.2.2 Visualization Design
7.3 Comparing Two N-dimensional Time Steps
7.4 Comparing Several One-dimensional Time Steps
7.5 Summary and Outlook
8 Parallel Hierarchies in Practice
8.1 Application to Plausibility Check Task
8.1.1 Plausibility Check Process
8.1.2 Visual Exploration of Machine Learning Results
8.2 Integration into SAP Analytics Cloud
8.2.1 SAP Analytics Cloud
8.2.2 Ocean to Table Project
8.3 Summary and Outlook
9 Validation
9.1 Introduction
9.2 Nested Model Validation Approach
9.3 Perceptual Validation of Visualization Techniques
9.3.1 Design Validation Table
9.3.2 Discussion
9.4 Summary and Outlook
10 Conclusion and Outlook
10.1 Summary of Findings
10.2 Discussion
10.3 Outlook
A Questionnaires of the Evaluation
B Survey of the Quality of Product Costing Data
C Questionnaire of Current Practice
Bibliograph
Leveraging Citation Networks to Visualize Scholarly Influence Over Time
Assessing the influence of a scholar's work is an important task for funding
organizations, academic departments, and researchers. Common methods, such as
measures of citation counts, can ignore much of the nuance and
multidimensionality of scholarly influence. We present an approach for
generating dynamic visualizations of scholars' careers. This approach uses an
animated node-link diagram showing the citation network accumulated around the
researcher over the course of the career in concert with key indicators,
highlighting influence both within and across fields. We developed our design
in collaboration with one funding organization---the Pew Biomedical Scholars
program---but the methods are generalizable to visualizations of scholarly
influence. We applied the design method to the Microsoft Academic Graph, which
includes more than 120 million publications. We validate our abstractions
throughout the process through collaboration with the Pew Biomedical Scholars
program officers and summative evaluations with their scholars
The Need to Support of Data Flow Graph Visualization of Forensic Lucid Programs, Forensic Evidence, and their Evaluation by GIPSY
Lucid programs are data-flow programs and can be visually represented as data
flow graphs (DFGs) and composed visually. Forensic Lucid, a Lucid dialect, is a
language to specify and reason about cyberforensic cases. It includes the
encoding of the evidence (representing the context of evaluation) and the crime
scene modeling in order to validate claims against the model and perform event
reconstruction, potentially within large swaths of digital evidence. To aid
investigators to model the scene and evaluate it, instead of typing a Forensic
Lucid program, we propose to expand the design and implementation of the Lucid
DFG programming onto Forensic Lucid case modeling and specification to enhance
the usability of the language and the system and its behavior. We briefly
discuss the related work on visual programming an DFG modeling in an attempt to
define and select one approach or a composition of approaches for Forensic
Lucid based on various criteria such as previous implementation, wide use,
formal backing in terms of semantics and translation. In the end, we solicit
the readers' constructive, opinions, feedback, comments, and recommendations
within the context of this short discussion.Comment: 11 pages, 7 figures, index; extended abstract presented at VizSec'10
at http://www.vizsec2010.org/posters ; short paper accepted at PST'1
Kassiopeia: A Modern, Extensible C++ Particle Tracking Package
The Kassiopeia particle tracking framework is an object-oriented software
package using modern C++ techniques, written originally to meet the needs of
the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for
particle tracking simulations which targets experiments containing complex
geometries and electromagnetic fields, with high priority put on calculation
efficiency, customizability, extensibility, and ease of use for novice
programmers. To solve Kassiopeia's target physics problem the software is
capable of simulating particle trajectories governed by arbitrarily complex
differential equations of motion, continuous physics processes that may in part
be modeled as terms perturbing that equation of motion, stochastic processes
that occur in flight such as bulk scattering and decay, and stochastic surface
processes occuring at interfaces, including transmission and reflection
effects. This entire set of computations takes place against the backdrop of a
rich geometry package which serves a variety of roles, including initialization
of electromagnetic field simulations and the support of state-dependent
algorithm-swapping and behavioral changes as a particle's state evolves. Thanks
to the very general approach taken by Kassiopeia it can be used by other
experiments facing similar challenges when calculating particle trajectories in
electromagnetic fields. It is publicly available at
https://github.com/KATRIN-Experiment/Kassiopei
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