Hello! I’m Zezhong from the University of Edinburgh, and this project, cheat sheets for
data visualization techniques collaborates with Lovisa Sundin, Dave Murray-Rust, and Benjamin Bach.
This video will introduce cheat sheets for data visualization
techniques to support understanding and using unfamiliar visualization techniques
visualization techniques are central to the practice of data visualization
They turn patterns in data into visual patterns that can be read and understood by people.
Some of these examples you may know, others may look unfamiliar.
While visualization techniques are intended to make information comprehensible,
many techniques require some degree of learning
and understanding of the visual mappings, graphical conventions, symbols,
marks, layouts and patterns to properly decode the visualization. There is no shortage
of resources to learn about data visualization, including books, survey papers,
workshops, classes, and online catalogs of techniques. Here are screenshots from visualization catalog,
python graph gallery, and a treemap introduction page
from andy kirk's book, there are other similar works, they provide text explanations
and pictures of examples. But much of this material talks
about general topics in visualization such as deception, design principles,
presentation, tasks, storytelling or layouts. So, How to help novice users
understand and decode visualization techniques correctly? For example, this includes:
What patterns can we see and how should we interpret them?
What are the common misinterpretations to avoid for a given technique?
There is a call for resources that are tightly structured and standardized, which align with
established visual design principles and which are easy to understand.
In order to support the development of material for learning, teaching, and the regular
use of visualization techniques. We present cheat sheets for visualization techniques.
This slide shows two cheat sheets. We deﬁne a cheat sheet as
“a set of concise, annotated graphical explanations of aspects for a speciﬁc visualization technique”.
We imagine the cheat sheets to support two scenarios:
the first scenario for ﬁrst-time learning aided through slides,
posters, books, or activities, and for the second scenario, as look-up material
during an actual data exploration process. The current form of our cheat sheets,
do not aim to overview and classify visualization techniques,
nor to support ﬁnding the “right” technique for a certain task.
We present cheat sheets for a selection of non-trivial visualization techniques for
different data types like temporal, relational, hierarchical, statistical, and multidimensional.
We chose six visualization techniques, which we believe
are non-trivial to understand. They are parallel coordinate plots, adjacency matrices,
box-plots, treemaps, conﬂuence graphs, and time curves.
We have carried out an iterative design process that involved 8 experts and their feedback.
We will look at each step in detail later, but let me show you the cheat sheets first.
We designed six different types of cheat sheets for each
technique, each of them explains a speciﬁc aspect of a technique and
supports different usage scenarios. Let’s start with the anatomy, it explains
the visual elements of visualization, inspired by illustrations in patents.
It demonstrates their composition, their speciﬁc terminology, and how they relate
to the data. The visual components of visualization
can include individual visual marks as well as
groups of marks, axes, locations in visualization and etc.
CONSTRUCTION explains the conceptual idea behind a visualization design and how it encodes data.
It reﬂects the relation between the data and its visual encoding, demonstrating
the process of constructing or providing a familiar metaphor. VISUAL PATTERN sheets
provide a catalog of meaningful patterns that may occur in a visualization.
Spotting patterns can be important to correctly interpret visualizations and
making discoveries—for example, network cliques
in adjacency matrices are visible as solid blocks.
PITFALLS show possible misinterpretations of a visualization.
Distinct from ways that visualizations can be poorly designed such as missing labels,
different but hard to perceive colors, not colorblind safe, or
deceptive titles, pitfalls are speciﬁc to a given technique and can occur even
with well-designed outputs. FALSE-FRIENDS list visualization techniques that are
visually similar but functionally different. For example, boxplots share
visual similarities with candlestick charts and error bars in bar charts. For the unfamiliar eyes,
time curves can look similar to connected scatter plots.
Well-known relative highlights other approaches to visualize the same data, for example,
node-link diagrams and adjacency matrices; scatterplots and parallel coordinates.
An Introduction is a format that introduces a visualization
technique within a speciﬁc context, explains its purpose, and highlights
important aspects described in the individual sheets.
An Introduction is a more elaborate component that can include information
from other sheets to provide an overview of the technique. Starting with
some context, data example, including constructions, pitfalls and finishing with a joke.
Ok, after seeing these data visualization cheatsheet examples, let’s turn
back to see the methodology. We’ve experienced 7 stages of iteration to
improve the contents and design. First, we selected several common but non-trivial
visualization techniques such as treemaps, adjacency matrices, and horizon graphs,
and used these to try a range of cheat sheet types to explore: comparison,
variation, advantages, drawbacks, and concrete examples. Second, we conducted a
two-hour co-design workshop with three senior university lecturers. They were then
asked to feedback on the draft sheets prepared in step 1. The expert workshop
highlighted the need for concrete examples when introducing a
visualization technique. After redesigning our sheets based on feedback,
we consulted individually with four university lecturers on potential use cases.
After another set of internal iterations, we conducted individual
readability walk-throughs with four graduate students. We obtained feedback
on ambiguities that required further explanation and how much they have
understood the concepts. We asked a researcher and designer unfamiliar with
our research to create cheat sheets for additional 3 visualizations based on
our examples. The example’s structure was found to be straightforward and salient.
To obtain further feedback on readability, usability, and to reﬁne our
design, we conducted an empirical user study following the rapid iterative test
and evaluation method with 11 participants novel to visualization.
we eventually, conducted two workshops with a total of ﬁve visualization experts and
non-experts to apply, evaluate, and reﬁne design guidelines for creating
additional cheat sheets with the support of our mate cheat sheets.
There is a lot of value in creating cheat sheets by students as making cheat sheets requires a
good understanding of technique, a critical eye, the structuring of knowledge,
and a clear presentation. Here is an example of a meta cheat
sheets for designing Anatomy. The full set of instructional material for
creating visualization cheat sheets including the full list of guidelines
and accompanying graphical explanations can be found on our website.
These guidelines were learned through the multiple iterations, For example:
Abstraction is good to make examples general and make this generalizability
understood. Concrete examples help to understand a visualization in the ﬁrst
place such as in our Introduction. Visual hierarchy, using fonts, sizes,
gray backgrounds, grouping, and careful use of colors and separators helps structure
content and make information retrievable. Maximize graphic-text ratio to support
lookup and visual exampliﬁcation; use text to give additional information.
Show pattern variations wherever possible to help to understand the main graphic
characteristic of a pattern. Use complementary terminology to help link
concepts from visual space, abstract data space, and concrete application space.
There is potentially a huge design space for cheat sheet formats to explore.
Besides Introduction, examples include posters, slide-shows,
videos, or embedded in interactive visualizations as pop-up reading-guides.
To summarize, We deﬁned six types of sheets for six common but
non-trivial visualization techniques and reﬁned them through an iterative method
involving expert interviews and workshops,
readability feedback, design-by-example, a readability study,
and a guideline workshop. To aid the creation of new cheat sheets,
we present a reﬁned set of design guidelines along with our freely available and modiﬁable
library of cheat sheets. Click the link here to our website, where
you can find all of these materials. We hope that this material helps the
community to build a common language and repository of material towards
deﬁning and developing a plan for visualization literacy.