Data Visualization Tools & Techniques Workshop

Greg Nottes, workshop presenter

Workshop Resources

Tools — extracts perfect info and meaning, doesn’t exist 🙂

Not here to necessarily talk about big data, but focus on data to communicate and tell a story; Understanding it. Then looking for errors. Or asking question about anomalies.

Why use different types of viz tools?

Word clouds — frequency of words are visually represented. (?) not right…..
Great for decoration — but not powerful.

How do you get meaning from data? Pull different viewpoints
Word cloud vs this viewpoint — not much can be told at a glance with this one; tells those who are invested in the data what’s going on, but not those outside the audience.

Remember you’re the closest to the data, you know it best; what are the key points to communicate to your audience. How much time your audience will take with this data.

One second story vs. looking more closely.

Another example

7 rules for making charts and graphs

  1. Check the data
  2. Explain encodings (clear legends)
  3. Label Axes
  4. Include Units
  5. Keep Geometry in Check
  6. Include Sources
  7. Consider Audience

Greg’s library, Reference data previously collected w LibStats (OSS) now using SpringShare product

In Excel, it’s really helpful to freeze top row — helps read long set of data. Also, filtering on the rows — helps quickly filter specific sets of data.

Ahead of time, setting up instructions for directly checking — making a list, transforming…

Ask lots of questions:

  • How accurate is the data?
  • Where is it gathered from?
  • What are its weaknesses?

Question asked — could a statistician be consulted by reference librarians to find out how to get a random sample to find meaningful data?

Calculating more meaningful times (grouping data)

Pivot Tables (in Excel) — Range; build report; allows you to take data, gives sum/average for any criteria as a row/column. Step toward getting graph you want.

Every element you add to a viz, increases the cognitive load on the viewer. x axes/y axis. No title showing summary of what’s been shown.

What are the key things here you want to share with others? That’s really what matters.

  1. Checking the data is crucial in telling the story.
  2. Explain encodings; use legend; colors; . At a quick look, viewer can tell.
  3. Label axis — whats on the x and y axis and label them
  4. What are the units
  5. Keep geometry in check (look at something and compare) Bar chart easier to tell than pie because area in a circle harder to distinguish in a pie chart.
  6. Include your sources
  7. Consider audience critical one

Additionally, keep these in consideration:

  • Data understanding
  • Limitations
  • Definitions
  • Grouping — what makes sense for groupings? Depends on the story you’re trying to tell; results may require you to group differently…

Show one thing:

  • Highlight Key Points
  • Comparing Parts of a whole: Pie or stacked bar chart

Consider graphic and how to present.

Three keys to data viz:

  1. What’s the key message?
  2. What’s the time for cognitive load to get that?
  3. Keeping it simple


Common Charts: Pie, Bar, Line & Other Types:

  1. Numerical data: chart; Choosing best type
  2. Component comparison — Percentage of a total; share percentage of total; accounted for X percent — pie chart; adding labels really help. Pie charts work best with two or three; not much more
  3. Item comparison, ranking of items:
    • larger than
    • smaller than
    • equal to
    • exceeded
    • rank — bar charts
  4. Time series comparison: changes over time — column or line chart;
  5. Frequency distribution: items within ranges; range of concentration x to y range; step or line chart
  6. Correlation comparison: relationship bw variables; related to, increases with, changing, decreasing with — scatter/dot/bubble chart; paired bar char
  7. Data maps (geographic data)
    • No numerical data — pushpin; multiple symbol
    • Numerical (single field) — shared area; shaded/sized circle; multiple symbol
    • Numerical (multiple fields) — pie chart; column charts

Active Dataviz community online, does do a lot of bashing — should be more on implementation, not so much on choice.


Always, keep in mind, what’s your message

More Tools

Real time data & Gate Counter

Good definition of big data — more than you can handle in a single spreadsheet?

  • Big Data — Circ Data — where do you pull meaning from?
  • LibQual evaulations
  • Quadrants visually displayed — attendee mentioned that. (Gartner quadrant?)
  • Give data visual look — have someone with familiarity with data, and get feedback before submitting to stakeholders.

Goal: Crafting message. What data resonates with your audience.

Infographics vs Data Dashboard

Infogram — real time data (freemium)

Piktochart — reports & infographics; banners & presentations

If report is more engaging, people more willing to read, synthesize, read, understand.

  • See at a glance.
  • Telling story, choosing key pieces.

Other Tools

  • another template driven infographic generator
  • Map Viz — add-ins in excel
  • Apps for Office.
  • Excel has quick analysis option. Could be used with viz, but also analysis.
  • Fusion Tables
  • data
  • Word clouds: Wordle; Tagul; Tagxedo
  • Stemming option with Tagul
  • Zotero Visualization tool? Zotero timeline
    Papermachines; serendipomatic
  • Microsoft Power Bi
    Tiddly Map
  • Color choosing tools.
  • Many, many more tools linked to on the workshop resources page.