Graphical interfaces and interactive visualisations are typical mediators between human users and data analytics systems. HCI researchers and developers have to be able to understand both human needs and back-end data analytics. Participants of our tutorial will learn how visualisation and interface design can be combined with data analytics to provide better visualisations. In the first of three parts, the participants will learn about visualisations and how to appropriately select them. In the second part, restrictions and opportunities associated with different data analytics systems will be discussed. In the final part, the participants will have the opportunity to develop visualisations and interface designs under given scenarios of data and system settings.
From Data to Visualisations and Back:
Selecting Visualisations Based on
Data and System Design
Considerations
Belgin Mutlu1, Vedran Sabol1, Heimo Gursch2, Roman Kern2
Knowledge Visualization Group, Know-Center GmbH1
Knowledge Discovery Group, Know-Center GmbH2
Abstract
Graphical interfaces and interactive visualisations are typical mediators between human users and data
analytics systems. HCI researchers and developers have to be able to understand both human needs and
back-end data analytics. Participants of our tutorial will learn how visualisation and interface design can
be combined with data analytics to provide better visualisations. In the first of three parts, the participants
will learn about visualisations and how to appropriately select them. In the second part, restrictions and
opportunities associated with different data analytics systems will be discussed. In the final part, the
participants will have the opportunity to develop visualisations and interface designs under given
scenarios of data and system settings.
1
Tutorial Content and Organisation
Creating high-quality user interfaces and visualisations requires understanding of interface
design and visualisation guidelines. Since back-end data analytics and data storage impose
restrictions on user interfaces and visualisations design, HCI researchers and developers have
to be familiar with user interface design, visualisation selection and the features of the
information processing system to create the best possible interface for all users. This tutorial
covers context-sensitive choice and configuration of visualisations, as well as data analysis
systems design. To that end, the tutorial is organised in three main parts. The first part the
focuses on the state-of-the-art visualisation and interface design. We present theoretical
background on perception, visual encoding rules, interaction design, and rules and guidelines
for describing the semantics of visualizations. Based on these theoretical foundations, best
From Data to Visualisations and Back: Selecting Visualisations Based on Data and System
Design Considerations
2
practices and techniques are described to select visualizations. Using these guidelines, the
participants can select new or evaluate existing designs based on data, system requirements,
use case, target user groups, etc. To put the knowledge at work, we provide examples of
cutting-edge interfaces and visualisations currently researched at the Know-Center, such as a
personalised visualisation suggestion. Participants will be encouraged to assess the presented
prototypes based on the above-mentioned guidelines and their personal experiences.
The second part of the tutorial focuses on data and the algorithms required to enhance
visualisations. The participants will learn about various back-ends and their features with
regard to interfaces and visualisations. Knowledge discovery algorithms will be discussed in
connection with data storages, back-end, and visualisation requirements. The presented
algorithms offer additional insights into data and extract relationships that are helpful in
visualisations as well as provide user support in visual analytics. At the end of the second part,
the interface designers should have an overview of the drawbacks and opportunities that
various data storages provide and how to utilize these techniques in order to create more
elaborate visualizations. Additionally, the participants will gain insights on what knowledge
discovery algorithms can provide, especially if the raw data is not ideal for visualisations.
In the third part, small groups of participants will have to work on a given interface design and
visualisation problem. They will receive a description of a use case and the data and system
involved. Each group will have to develop an interface and visualisation design suited for the
given problem. Poster material and pre-printed visual elements will be provided to the teams.
The teams will have to design a poster illustrating their solutions. The teams will present their
solution and collect feedback from the other teams and the tutors. The goal of this session is
to master a real-life design scenario with the discussed information, guidelines and hand-outs
from parts one and two. With the help of the tutors, the participants will be shown how such
guidelines can be used in a day-to-day business of interface design.
2
Didactic Concept
Participants receive handouts describing the rules, guidelines and techniques presented during
the tutorial. The tutorial will be divided into three sessions aligned with the three main parts
presented above. Participants will be encouraged to ask questions and engage in discussions
in the first two parts. In the third part, the tutors’ attendants will form small groups with a
mixed expertise in the fields of visualisations, interface design, and data analytics. In the mixed
groups, the parti
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