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- 2 November 2016
See also Data management | Data visualization | Information technology topics | Mashups in medicine | Research Portal for Academic Librarians | Social network analysis
- " ...from library catalogues to mind maps to visual search engines join us as we tour some of the best, most interesting, most useful, or just plain coolest visualization tools out there. One of the most important trends to emerge from the Web 2.0 phenomenon is the advent of visualization tools that can illuminate, reveal, and shine a bright light on otherwise complex, dense, or dare we say boring data and text. Explore how these tools offer unique ways to visualize information patterns, facilitate information discovery and navigation, and reveal hidden concepts. Find the sweet spots for these new visualization tools for libraries, including how library users responded when the library catalog went "visual" with AquaBrowser...." — Darlene Fichter, Canadian academic librarian
Information visualization (InfoVis or IV) is a digital age repurposing of data, and refers to the development of interactive visual representations of abstract, multidimensional data sets. Sometimes referred to as "using vision to think" or "thinking by seeing", IV provides different views of knowledge to help the viewer gain a deeper understanding of something. IV can help to reveal unknown or unseen aspects of phenomena, including relationships between things, information and people.
Some of the major goals of visualization are:
- To make large datasets coherent
- To present huge amounts of information concisely
- To present information from various viewpoints
- To present information at several levels of detail, from overviews to fine structure
- To support visual comparisons
- To tell stories about the data
Using information visualization techniques can help you to explore digital storytelling, learn how colour conveys information our brains recognize before we're fully aware of it, discover how books reveal clues to our deeper selves and find out how researchers investigate unknown phenomena, from initial sketches to published papers using data.
Popular texts & figures
- ...a classic text that discusses how complex information should be presented graphically. Tufte's book has been called "The Strunk & White of visual design" and should be within arm's reach to understand numerical data graphically. The books' design is an exemplar of the principles it espouses: elegant typography and layout, and seamless integration of lucid text and perfectly chosen graphical examples.
Medical databases & articles visualized
The massive growth of MEDLINE since 1966 coupled with exponential growth in biomedical knowledge has led to literature mining techniques aimed at extracting information from the scientific literature. Ontologies are extensively used as controlled vocabularies or as frameworks for mapping between concepts in biology and medicine. Literature-based approaches have been used to generate hypotheses in connection with drug discoveries. Attempts to integrate literature mining with other types of data arising from the use of these technologies as well as visualization tools assisting in the discovery of novel associations between existing drugs and new indications will also be presented.
Some of the reasons for visualizing information is because the eye is especially adept at pattern recognition, and human beings are generally good at
scanning, recognizing and remembering images than text. In addition, graphical elements of information facilitate comparisons around shapes, lengths, connections and changes over time. Colour and aesthetics also help learners make distinctions and make the process seem more appealing somehow.
InfoVis in clinical care
The amount and the complexity of data available at clinicians’ fingertips are constantly increasing as a result of technology advancements in computer performance and storage capacity. Unfortunately, due to well-known cognitive and perceptual limitations, the quantity of information a user can examine and handle at a given instant is very limited.
The use of information technologies in clinical care is increasing both the amount and complexity of information and data accessible to health professionals. By providing interactive visual representations of data and information, IV aims to deepen the exploration of the "information space", support optimal use of data and information and help avoid information overload.
Chittaro (2001) summarizes the goals of InfoVis for healthcare as:
- allowing "users to explore available data at various levls of abstraction"
- giving "users a greater sense of engagement with data"
- giving "users a deeper understanding of data"
- encouraging "discovery of details and relations which would be difficult to notice otherwise"
- supporting "recognition of relevant patterns by exploiting the visual recognition capabilities of users."
Visualization tools have been used in the medical domain for many years. Most applications have been in the field of scientific visualization, for example 3D volume visualization tasks, x-rays, computer tomography visualizations. Tasks involving abstract data (such as patient data, treatment data or lab results) or computerized treatment guideline plans have however not been targeted by InfoVis researchers until recently.
Websites & other sources
Information visualization projects for healthcare
- KNAVE II supports visualization, summarization, (intelligent) interpretation, explanation and context-sensitive navigation of raw data sets
The GLARE knowledge acquisition tool; Guide Editor; Protégé support for development of guidelines and protocols
- Andronis C, Sharma A, Virvilis V, Deftereos S, Persidis A. Literature mining, ontologies and information visualization for drug repurposing. Brief Bioinform. 2011;12(4):357-68.
- Card SK, Mackinlay JD, Shneiderman B. Readings in information visualization: using vision to think. San Francisco: Morgan Kaufman, 1999.
- Chittaro L. Information visualization and its application to medicine. Artif Intell Med. 2001;22(2):81-8.
- Eick SG. Data visualization sliders. In: Readings in information visualization: using vision to think. San Francisco: Morgan Kaufman, 2000.
- Frijters R, Smeets R. Literature mining for the discovery of hidden connections between drugs, genes and diseases. PLoS Comput Biol. 2010;6(9):e1000943.
- Gesteland PH. The EpiCanvas infectious disease weather map: an interactive visual exploration of temporal and spatial correlations. J Am Med Inform Assoc. 2012 Feb 22.
- Lei XC. Visualization of the MEDLINE database for prostate cancer.
- Pirolli P, Card S. Visual information foraging in a focus + context visualization. CHI Proceedings. 2001;3(1):506-513.
- Rani M, Buckley BS. Systematic archiving and access to health research data: rationale, current status and way forward. Bull World Health Organ. 2012;90:932–939.
- Srinivasan P. Mining MEDLINE for implicit links between dietary substances and diseases. Bioinformatics. 2004;20 Suppl 1:290-6.
- Stahl-Timmins W. Information graphics in health technology assessment. PhD thesis, University of Exeter, UK. 2011.
- Tufte E. The visual display of quantitative information. Cheshire, Conn: Graphics Press, c2001.
- Wang TD. Extracting insights from electronic health records: case studies, a visual analytics process model, and design recommendations. J Med Syst. 2011;35(5):1135-52.
- Ware C. Information visualization: perception for design. San Francisco: Morgan Kaufmann, 2012.