scholarly journals Designing Visualizations For Biological Data

Leonardo ◽  
2013 ◽  
Vol 46 (3) ◽  
pp. 270-271 ◽  
Author(s):  
Miriah Meyer
Keyword(s):  
Biological Data ◽  
Discovery Process ◽  
Design Studies ◽  
Biological Discovery ◽  
Vital Component ◽  
Visualization Tools ◽  
Visualization Design ◽  
Effective Visualization

Visualization is now a vital component of the biological discovery process. This article presents visualization design studies as a promising approach for creating effective, visualization tools for biological data.

scholarly journals Enhancing the operational value of snowpack models with visualization design principles

2020 ◽  
Vol 20 (6) ◽  
pp. 1557-1572
Author(s):  
Simon Horton ◽  
Stan Nowak ◽  
Pascal Haegeli
Keyword(s):  
Spatial Scales ◽  
Critical Role ◽  
Design Principles ◽  
Physical Models ◽  
Model Data ◽  
User Testing ◽  
Avalanche Forecasting ◽  
Cognitive Principles ◽  
Visualization Tools ◽  
Visualization Design

Abstract. Forecasting snow avalanches requires a reliable stream of field observations, which are often difficult and expensive to collect. Despite the increasing capability of simulating snowpack conditions with physical models, models have seen limited adoption by avalanche forecasters. Feedback from forecasters suggests that model data are presented in ways that are difficult to interpret and irrelevant to operational needs. We apply a visualization design framework to enhance the value of snowpack models to avalanche forecasters. An established risk-based avalanche forecasting workflow is used to define the ways forecasters solve problems with snowpack data. We suggest that model data be visualized in ways that directly support common forecasting tasks such as identifying snowpack features related to avalanche problems and locating avalanche problems in terrain at relevant spatial scales. Examples of visualizations that support these tasks and follow established perceptual and cognitive principles from the field of information visualization are presented. Interactive designs play a critical role in understanding these complex datasets and are well suited for forecasting workflows. Although extensive user testing is still needed to evaluate the effectiveness of these designs, visualization design principles open the door to more relevant and interpretable applications of snowpack model for avalanche forecasters. This work sets the stage for implementing snowpack models into visualization tools where forecasters can test their operational value and learn their capabilities and deficiencies.

Semiotic Content of Visuals and Communication

2014 ◽  
pp. 174-192
Keyword(s):  
Data Visualization ◽  
Verbal Communication ◽  
Biological Data ◽  
Scientific Study ◽  
Visual Design ◽  
Basic Information ◽  
Natural Processes ◽  
Sign Systems ◽  
Visualization Tools ◽  
Living Organisms

The semiotic content of visual design makes a foundation for non-verbal communication applied to practice, especially for visualizing knowledge. The ways signs convey meaning define the notion of semiotics. After inspection of the notions of sign systems, codes, icons, and symbols further text examines how to tie a sign or symbol to that for which it stands, combine images, and think figuratively or metaphorically. Further text introduces basic information about communication through metaphors, analogies, and about the scientific study of biosemiotics, which examines communication in living organisms aimed at conveying meaning, communicating knowledge about natural processes, and designing the biological data visualization tools.

scholarly journals Integrated System for easier and effective Drug Information

2019 ◽  
Vol 12 (3) ◽  
pp. 1069-1077
Author(s):  
Susmitha Shankar ◽  
S. Thangam
Keyword(s):  
New Technologies ◽  
Treatment Strategies ◽  
Biological Data ◽  
Integrated System ◽  
Data Type ◽  
Drug Label ◽  
Novel Approach ◽  
Label System ◽  
Single Data ◽  
Effective Visualization

With the advent of new technologies, a large amount of biological data is easily generated in comparatively cheaper cost. Prior to this data integration was done by simple means of database addition, with less complexity due to lesser data generated in a standardized format. Understanding a complete biological phenomenon, such as disease, need a comprehensive understanding of many dimensions associated with it. This information cannot be captured in a single data type format. Mandating the use of a single data type study would leave us with incomplete answers to various biological questions. Thus the development of an effective integration technique with effective visualization platform is the need of the hour. One such framework requires the identification of relevant data from the input system, storing and transforming data into the intermediary level and then mapping these data into an appropriate position in the output systems. This intermediate level helps in reducing the number of connection and repeated specification creation. Integration of drug dataset would not only reduce the propagation of incorrect and not-updated medicinal information among doctors, but it would also help build better treatment strategies. Integration of drug data and visualization technique would be a novel approach to study drugs and effect on one platform. In this work, we tried to integrate the Adverse Effects, Drug Enforcement and Drug Label data from openFDA. This integrated database is coupled with a visualization platform IDEALS, an abbreviation for Integrated Drug Events, Adverse Effect and Label System.

scholarly journals Visualizing Structure and Transitions for Biological Data Exploration

2017 ◽  
Author(s):  
Kevin R. Moon ◽  
David van Dijk ◽  
Zheng Wang ◽  
Scott Gigante ◽  
Daniel B. Burkhardt ◽  
...  
Keyword(s):  
Biological Data ◽  
Data Exploration ◽  
High Dimensional ◽  
Visualization Method ◽  
Mass Cytometry ◽  
Nonlinear Structure ◽  
Single Cell Rna Sequencing ◽  
Visualization Tools ◽  
Microbiome Data ◽  
Germ Layer Differentiation

AbstractWith the advent of high-throughput technologies measuring high-dimensional biological data, there is a pressing need for visualization tools that reveal the structure and emergent patterns of data in an intuitive form. We present PHATE, a visualization method that captures both local and global nonlinear structure in data by an information-geometric distance between datapoints. We perform extensive comparison between PHATE and other tools on a variety of artificial and biological datasets, and find that it consistently preserves a range of patterns in data including continual progressions, branches, and clusters. We define a manifold preservation metric DEMaP to show that PHATE produces quantitatively better denoised embeddings than existing visualization methods. We show that PHATE is able to gain unique insight from a newly generated scRNA-seq dataset of human germ layer differentiation. Here, PHATE reveals a dynamic picture of the main developmental branches in unparalleled detail, including the identification of three novel subpopulations. Finally, we show that PHATE is applicable to a wide variety of datatypes including mass cytometry, single-cell RNA-sequencing, Hi-C, and gut microbiome data, where it can generate interpretable insights into the underlying systems.

Bioinfo-Kit: A Sharing Software Tool for Bioinformatics

2014 ◽  
Vol 472 ◽  
pp. 466-469
Author(s):  
Yu Huang ◽  
Jian Yong Wang ◽  
Xiao Mei Wei ◽  
Bin Hu
Keyword(s):  
Graphical User Interface ◽  
Software Tool ◽  
Biological Data ◽  
Software System ◽  
Biomedical Data ◽  
Application Development ◽  
General Application ◽  
Multiple Electrodes ◽  
Visualization Tools ◽  
Friendly Graphical User Interface

In bioinformatics research, for the lacks of an effective algorithm-integrating mechanism and a friendly graphical user interface of the toolkits in the field of biological data processing and analyzing, the authors designed and implemented a sharing software system Bioinfo-Kit based on the Java 2 Platform Enterprise Edition (J2EE), which provides 1) a general application development interface to integrate or bridge other programs and 2) a workflow mechanism to operate them and make them talk easily. In addition, a module for biological data (multiple electrodes data, biomedical data and etc.) analysis was implemented in the software system, which provided a workflow mechanism to integrate a series of algorithms and visualization tools. Because the interface developed is very general and flexible, new analysis tools can be integrated effectively as required. Bioinfo-Kit implies an ideal environment for integrative bioinformatics research.

scholarly journals Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco

2018 ◽  
Author(s):  
Dominik Moritz ◽  
Chenglong Wang ◽  
Greg Nelson ◽  
Halden Lin ◽  
Bill Howe ◽  
...  
Keyword(s):  
Empirical Studies ◽  
Design Guidelines ◽  
Visual Exploration ◽  
Design Knowledge ◽  
Formal Framework ◽  
Design Systems ◽  
Visualization Tools ◽  
Visualization Design ◽  
Additional Constraints ◽  
Design Guidance

There exists a gap between visualization design guidelines and their application in visualization tools. While empirical studies can provide design guidance, we lack a formal framework for representing design knowledge, integrating results across studies, and applying this knowledge in automated design tools that promote effective encodings and facilitate visual exploration. We propose modeling visualization design knowledge as a collection of constraints, in conjunction with a method to learn weights for soft constraints from experimental data. Using constraints, we can take theoretical design knowledge and express it in a concrete, extensible, and testable form: the resulting models can recommend visualization designs and can easily be augmented with additional constraints or updated weights. We implement our approach in Draco, a constraint-based system based on Answer Set Programming (ASP). We demonstrate how to construct increasingly sophisticated automated visualization design systems, including systems based on weights learned directly from the results of graphical perception experiments.

Animated Visualization of Multiple Intersecting Hierarchies

2002 ◽  
Vol 1 (1) ◽  
pp. 50-65 ◽  
Author(s):  
George Robertson ◽  
Kim Cameron ◽  
Mary Czerwinski ◽  
Daniel Robbins
Keyword(s):  
System Architecture ◽  
Information Structure ◽  
User Studies ◽  
Visualization Technique ◽  
Web Based ◽  
Iterative Design ◽  
Cache Architecture ◽  
New Information ◽  
Visualization Tools ◽  
Visualization Design

The authors describe a new information structure composed of multiple intersecting hierarchies, which we call a Polyarchy. Visualizing polyarchies enables use of novel views for discovery of relationships which are very difficult using existing hierarchy visualization tools. This paper will describe the visualization design and system architecture challenges as well as our current solutions. Visual Pivot is a novel web-based polyarchy visualization technique, supported by a ‘polyarchy server’ implemented with a Mid-Tier Cache architecture. A series of five user studies guided iterative design of Visual Pivot. Finally, the effectiveness of animation in Visual Pivot is discussed.

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