Information Visualization

Karen E.

GutzmanMarch 2014

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Road map

What’s a librarian to do?

Words to live by

Resources

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Words to live by

• Edward Tufte’s seminar:

Presenting Data and Information

• Katy Börner’s course:

Information Visualization

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Words to live by

…the task of the designer is to give visual

access to the subtle and the difficult …-Edward Tufte (2001, p. 191)

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Words to live by

Graphics reveal data

greatest number of ideas

shortest time least ink smallest space

Example 1. Brenner (2002)

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Words to live by

Graphics reveal data

greatest number of ideas

shortest time least ink smallest space

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Words to live by

Graphics reveal data

greatest number of ideas

shortest time least ink smallest space

Example 2. Tufte (n.d.)

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Resources• Data sources

• Visualization tools

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Resources: data sources

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Resources: visualization tools

Supports visualization of datasets

Temporal Geospatial Topical Network analysis

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What’s a librarian to do?

• Dream up ideas

• Use the data

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Temporal data

Types of visualizations

Time-Series Plot Histogram Stacked graph Burst Detection (see visualization)

What to visualize The increase in the number of

citations for a specific publication over time

Number of new collaborators participating in a specific program

The amount of funding provided to an organization or researcher (see visualization)

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Geospatial Data

Types of visualizations

Proportional Symbol Map Choropleth Maps (see visualization)

What to visualize The location (state/country) of

researchers, experts, or collaborators

The amount of funding on specific topic by geographical area

The location of authors who have cited, viewed, or downloaded a particular publication or work (see visualization)

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Topical Data

Types of visualizations

Cross Maps Wordle Topic Bursts (see

visualization)

What to visualize Word co-occurrence on a

single document, book or other text-based research output combined with burst detection (see visualization)

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Topical Data

Types of visualizations Cross Maps Wordle (see visualization) Topic Bursts

What to visualize Word co-occurrence on a single

document, book or other text-based research output combined with burst detection (see visualization)

Word bursts of top 50 terms in the abstracts of the top 10 most highly cited publications for Dr. Name Redacted.

(from wordle.net)

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Network Data

Types of visualizations Radial Tree Graph Tree Map Social Networks (see visualization)

What to visualize The hierarchy of a network drive or

organization

Identify highly connected authors or papers through collaborations or citations (see visualization)

Dr. Name Redacted

Dr. Co-Author 2

Dr. Co-Author 1

Author Co-occurrence (co-author) Network

Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies, https://sci2.cns.iu.edu.

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Sources

Börner, K., Polley, D.E. (2014). Visual Insights. Cambridge, MA. Massachusetts Institute of Technology

Brenner, H. (2002). Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis. The Lancet, 360, pp. 1131-1135

Tufte, E. (2001). The Visual Display of Quantitative Information. 2nd Ed. Cheshire, CT. Graphics Press.

Tufte, E. (n.d.) Cancer survival rates: tables, slopegraphs, barcharts. [online forum] Retrieved from: http://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=0000Jr

Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies, https://sci2.cns.iu.edu

Information Visualization Portfolio: http://visualizinginformationportfolio.blogspot.com/

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Thank you

This research was supported in part by an appointment to the NLM Associate Fellowship Program sponsored by the National Library of Medicine and administered by the Oak Ridge Institute for Science and Education.