data visualization services nc state university...
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Data & Visualization Servicesat NC State University Libraries
Walt GurleyData & Visualization Librarian
Why?
A Brief History
90s, early 2000s: GIS and Data Services in Research and Information Services
2013: Construction of visualization spaces
2014: Formation of cross-departmental Visualization Services Team
2015: Visualization Services in the Digital Library Initiatives department
2015: Data visualization workshops series, Coffee & Viz event series
2018: Formation of Data & Visualization Services department
GIS and Data Services
Visualization Spaces
Data Visualization Workshops Series
Coffee & Viz Seminar Series
Data & Visualization Services Department
Karen CicconeDepartment Head
Mike NuttAssociate Head
Alison BlaineData & Visualization Librarian
Jeff EssicData & Visualization Librarian
Walt GurleyData & Visualization Librarian
Natalia LopezData & Visualization Librarian
Mia PartlowNCSU Libraries Fellow
Jacob ShelbyMetadata Technologies Librarian
Consultation and Instruction
Our expertise include (but are not limited too):
● Data visualization
● Finding and acquiring datasets
● GIS and mapping
● Data cleaning and manipulation
● Data modeling and database design
● Metadata creation and mapping
● Qualitative analysis
● Quantitative analysis
“We help students and researchers develop critical data science and visualization skills through...”
Consultation and Instruction
“We help students and researchers develop critical data science and visualization skills through...”
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Beginning RIntermediate RData Cleaning with RData Visualization with RIntroduction to Jupyter NotebooksVisualizing Sound with Code…go.ncsu.edu/vizmaterials
Data and Visualization WorkshopsElements of Visualization DesignBeginning TableauIntermediate TableauTableau Lab: Bring Your Own DataCreating Thematic Maps in TableauGeospatial Visualizations with QGISIntroduction to APIs and JSON
“We help students and researchers develop critical data science and visualization skills through...”
Course Instruction Support
Our services include the following:
● Visiting an instructor’s classroom to provide hands-on workshops
● Workshops in the libraries’ lab spaces (we can provide laptops)
● Consulting with students by appointment related to your assignments
● Consulting with an instructor on developing course projects and assignments
“We help students and researchers develop critical data science and visualization skills through...”
Access to Computing Resources and Software
● We curate a software stack on devoted Macs and PCs
● Including popular free data and visualization software, such as:
R, Python, Gephi, Tableau Public, QGIS
● We also have licenses for popular paid applications, such as:
MATLAB, ArcGIS, Excel, Adobe Creative Cloud, NVivo
“We help students and researchers develop critical data science and visualization skills through...”
The Hunt Library Dataspace
The Hunt Library Dataspace
● Advanced PC and iMac Pro workstations
● Programs for analysis, design, and programming, such as ArcGIS, MATLAB, Microsoft Power BI, SAS, and Adobe Creative Cloud
● Support for accessing campus virtual computing and HPC
“We help students and researchers develop critical data science and visualization skills through...”
Access to Computing Resources and Software
The Hunt Library Dataspace & D. H. Hill Data Point
● Data Science Consultants providing walk-up peer tutoring
● Pop-up tutorials
● Consultant lead workshops
Consultation and Instruction
“We help students and researchers develop critical data science and visualization skills through...”
Data and Visualization Workshops
The Hunt Library Dataspace
“We help students and researchers develop critical data science and visualization skills through...”
Data & Visualization Servicesat NC State University Libraries
Walt GurleyData & Visualization Librarian
Library support through:
● Staffing (Who can do this?)
● Services (What can you offer?)
● Expertise (What skills do you have?)
● Infrastructure (Do you have the space… the hardware… the software?)
What do you have? What do you need?
Staffing
Who can do this?
What do you have? What do you need?
Expertise
What skills do you have?
What do you have? What do you need?
Infrastructure
Do you have the space… the hardware…
the software...?
What do you have? What do you need?
Services
What can you offer?
What do you have? What do you need?
Walt GurleyNC State University Libraries
Elements of Visualization Design
Goals
This session will provide:
● an introduction to core design concepts● exposure to free tools for color and chart selection● practice doing a visualization “makeover”● ways to get help and learn more
What is data visualization?
Why visualize?
Let’s get started…
For each of the following visualizations, you will get 30 seconds to jot down your main takeaway of that viz
Source: Cole Nussbaumer Knaflic, http://www.storytellingwithdata.com/blog/2014/06/alternatives-to-pies
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Source: http://www.nytimes.com/interactive/2013/03/29/sports/baseball/Strikeouts-Are-Still-Soaring.html
Source: https://www.good.is/infographics/america-s-richest-counties-and-best-educated-counties
Source: https://excelcharts.com/animation-small-multiples-growth-walmart-excel-edition/
Source: https://excelcharts.com
Choose the best encoding for your data typePosition on common scale
Position on unaligned scale
Length
Angle/tilt
Area
Color saturation & luminance
Area
Effe
ctiv
enes
s
Accurate estimates
General estimates
Spatial Region
Color hue
Shape
Categoricaldata
Ordereddata
ColorType
S P A C E& GROUPING
Basic designconsiderations
Color Characteristics
Hue (color name)
Saturation (chroma)
Lightness (brightness)
Color
Which characteristic to use?Color
Hue is not naturally ordered
Dark
Paired
Choose different hues for categorical dataColorPastel1
Accent
Choose different hues for categorical dataColor
Source: https://visual.ly/blog/subtleties-of-color-different-types-of-data-require-different-color-schemes/
Use an ordered palette for quantitative dataColorGreys
Blues
YlGnBu
YlOrRd
Use an ordered palette for quantitative dataColor
Source: https://www.climate.gov/maps-data
Use a diverging palette for diverging dataColor
RdBu
RdYlBu
PuOr
Use a diverging palette for diverging dataColor
Source: https://www.climate.gov/maps-data
Perceptually uniform color scaleColor
Perceptually uniform color scaleColor
Magma
Inferno
Plasma
Viridis
Choose a colorblind-safe paletteColor
Source: https://visual.ly/blog/subtleties-of-color-different-types-of-data-require-different-color-schemes/
Choose a colorblind-safe paletteColor
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216103/figure/pone-0111530-g010/
Consider the presentation mediumColor
Source: http://flowingdata.com/2012/11/09/incredibly-divided-nation-in-a-map/
Picking FontsTypePick serious fonts for serious work.
Avoid fonts like Comic Sans, Marker Felt, and fonts that look like handwriting.
Stay consistent with font choices. An easy way to do this is to pick one font and stick with it.
Creating Type SystemsTypeCreate a system for your type!
Consistency is key.
Make differences obvious.
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Type Systems in Data VizTypeUse different weights and sizes in data visualizations too.
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Type Systems in Data VizTypeUse different weights and sizes in data visualizations too.
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Type DetailsType
Centered and right aligned text are difficult to read.
Give text room to breathe (especially in boxes).
Keep type horizontal.
In modern science, it is regarded as good scientific practice to aim for principles
such as objectivity and reproducibility.
My TitleThis is one sentence about my graph or visualization.
In modern science, it is regarded as good scientific practice to
aim for principles such as objectivity and
reproducibility.
Avoid VerticalAvo
id slants
In modern science, it is regarded as good scientific practice to aim for principles such as objectivity and reproducibility.
Horizontal type!
My Title
Don’t Do
Use notation to aid interpretationType
Source: https://flowingdata.com/2014/05/29/bars-versus-grocery-stores-around-the-world/
Source: http://www.nytimes.com/interactive/2013/03/29/sports/baseball/Strikeouts-Are-Still-Soaring.html
Use notation to aid interpretationType
Comprehensive overview of typeType
Thinking with Type: thinkingwithtype.com
Gestalt principlesS P A C E& GROUPING
Proximity Similarity Enclosure
Slides available here: go.ncsu.edu/wrri-vis-design
ProximityS P A C E& GROUPING
Slides available here: go.ncsu.edu/wrri-vis-design
Proximity S P A C E& GROUPING
Slides available here: go.ncsu.edu/wrri-vis-design
Similarity & EnclosureS P A C E& GROUPING
Source: https://www.nytimes.com/interactive/2017/09/09/us/hurricane-irma-records.html
Proximity, similarity, & enclosureS P A C E& GROUPING
Proximity, similarity, & enclosureS P A C E& GROUPING
The elements of Design: vanseodesign.com/web-design/design-elements
Visualization Makeover
Best practices for making good visualizations1. Select an appropriate chart type. Keep it simple!2. Use color thoughtfully and carefully:
○ Use color to highlight/emphasize ○ Categorical data uses hues; quantitative data uses
ordered and diverging palettes○ Use colorblind safe color palettes
3. Use a consistent type system and tell a story with annotation.
4. Keep psychological principles of grouping in mind.
How effective is this visualization?
● Chart type?
● Use of color?
● Type?
● Grouping?
Visualization makeover: make it easier to interpret
Visualization makeover: make it easier to interpret
Visualization makeover: add labels and color
How effective is this visualization?
Alternative 1: show the numbers directly
Alternative 2: simple bar chart
Alternative 3: stacked horizontal bar chart
Alternative 4: slope graph
Visualization makeover
Choose an ordered palette for quantitative data
Choose a colorblind-safe palette
Choose an appropriate chart type
Don’t show too much data