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Scientific visualizations: A bridge to knowledge

Speed read
  • Founding director of Scientific Computing and Imaging Institute chats about scientific visualizations.
  • Good visualizations are a collaborative process of discovery.
  • Visualizations are a crucial step on path to knowledge. 

Can you describe the visualization discovery and analysis process?

Visualization focuses on helping people explore or explain data through software systems that provide static or interactive visual representations. Visualization designers exploit the high bandwidth channel of human visual perception to enable people to comprehend information orders of magnitude more quickly than they could through reading raw numbers or text. 

Visualization is useful for detecting patterns, assessing situations, and prioritizing tasks.  Visualization is the tool through which computation addresses an end user and enables the user to derive knowledge from data.

The visualization discovery and analysis process. Courtesy Chris Johnson; SCI.

Data encompasses the range from a single bit to time-varying 3D tensor fields; to multimodal data sources requiring alignment, registration, and fusion; and to nonspatial high-dimensional information sources integrating broad areas of heterogeneous knowledge.

Visualization facilitates the reasoning process by supporting the human capacity to perceive, understand, and reason about complex large-scale data. It is a highly interdisciplinary field that encompasses cognitive and perceptual science, data analysis and management, knowledge representation and discovery, scientific and information visualization, and human-computer interaction (HCI).

What makes a good visualization?

Visualization forms a critical bridge from data to knowledge by facilitating interactive exploration of data, integrating domain knowledge, and helping to steer the analysis process. Scientists, engineers and other specialists rely on visualization to interactively explore and correlate numerous aspects of massive and complex data from a variety of views and at different levels of detail.

An effective visualization presents a concise and clear depiction of a specific aspect of the data and plays an important role in helping the user create a mental model of that data, which in turn leads to comprehension and the development of new knowledge.

Designing effective visualization tools and systems relies on insights from domain experts and a continuous dialogue between them and the computer scientists throughout the development process. Designing effective visualizations is an active area of HCI and visualization research. 

Can you give us examples of effective collaborations between visualization researchers and domain experts?

Certainly! Let me give you two great examples of effective collaborations between visualization researchers and domain experts. The first is work done by my colleague Professor Miriah Meyer, Professor Tamara Munzner from the University of British Columbia, and Professor Hanspeter Pfister from Harvard University working with biologists from the Broad Institute of MIT and Harvard.

In comparative genomics, researchers seek to answer questions about evolution and genomic function by comparing the genomes of different species. To study the differences and similarities between genomes, biologists analyze relationships of conservation between genomic features. Conservation refers to the similarity between genomic features in two different genomes, or sometimes within a single genome.

The goal of the visualization researchers' work was to show different conservation relationships at different scales, expressed as comprehensible visual relationships. To accomplish this goal, the visualization researchers created MizBee, a multiscale genome browser that shows different conservation relationships at different scales, expressed as comprehensible visual relationships 

The multiscale MizBee browser allows biologists to explore many kinds of conserved relationships with linked views at the genome, chromosome, and block levels. Here we compare the genomes of two fish, the stickleback and the pufferfish. Courtesy Chris Johnson, SCI.

“Biologists working in the field of comparative genomics are faced with understanding large datasets that span a range of scales and contain numerous types of interesting relationships. Visualization is an important part of their workflow, augmenting computation algorithms to gain an understanding of these relationships,” says Meyer, et al.

The MizBee visualization system allowed the biologists to interactively visually explore their models and data to both confirm known relationships and reveal previously unknown relationships, illustrating the power of effective visualization.

Read more here . . .


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