Short answer

Adopt a systematic approach by first understanding the available encoding variables, then defining clear evaluation criteria, and finally selecting appropriate methods to test the effectiveness of your data physicalisations.

Field: User-Centred Design
Source: Multimodal Technologies and Interaction (2023)
Method: Narrative and Systematic Literature Review
Evidence: Strong effect

A structured approach to data physicalisation design involves defining encoding variables, establishing clear evaluation criteria, and employing appropriate methods to assess their effectiveness. This user-centred design research insight is drawn from a 2023 study published in Multimodal Technologies and Interaction. Using Narrative and systematic literature review, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Adopt a systematic approach by first understanding the available encoding variables, then defining clear evaluation criteria, and finally selecting appropriate methods to test the effectiveness of your data physicalisations.

Study

User-Centred DesignRecentStrong effect

Data Physicalisation Design: A Framework for Encoding, Evaluation, and Iteration

A structured approach to data physicalisation design involves defining encoding variables, establishing clear evaluation criteria, and employing appropriate methods to assess their effectiveness.

Multimodal Technologies and Interaction · 2023

Key Findings

01Identification of a comprehensive set of encoding variables for data physicalisation.
02Compilation of relevant evaluation criteria for assessing data physicalisations.
03Categorization of methods suitable for evaluating data physicalisations.
04Development of a conceptual framework and a seven-stage model for designing and evaluating data physicalisations.

Application

Design takeaway

How to apply

When designing a data physicalisation, consciously consider the physical properties you will use to represent data (e.g., shape, colour, texture, size) and plan how you will test its clarity and impact with users.

Project actions

01When designing a physical representation of data, think about what physical attributes (like size, colour, or texture) you can change to represent different data points.
02Plan how you will ask people if your physical data representation is easy to understand and what it means.

Method & Evidence

AimWhat are the key encoding variables, evaluation criteria, and evaluation methods for data physicalisations, and how can they be integrated into a design and evaluation framework?

MethodNarrative and Systematic Literature Review

ProcedureThe researchers conducted a narrative review of literature from Information Visualisation, HCI, and Cartography to identify encoding variables for data physicalisations. They also performed a systematic review to extract evaluation criteria and methods used for assessing data physicalisations. A conceptual framework and a seven-stage design/evaluation model were developed based on these findings.

ContextData Physicalisation Design and Evaluation

Variables

IV["Encoding variables (e.g., shape, size, colour, texture)","Evaluation criteria (e.g., clarity, accuracy, memorability)","Evaluation methods (e.g., user testing, expert review)"]

DV["Effectiveness of data communication","User comprehension","User engagement","Accuracy of data interpretation"]

CV["Complexity of the dataset","Target audience characteristics","Physical environment of use"]

Strengths & Limitations

Strengths

+Provides a comprehensive overview of current knowledge in data physicalisation design and evaluation.
+Offers a practical framework and model to guide designers and researchers.

Limitations

The scope of encoding variables and evaluation methods might be limited by the available research. Practical constraints may affect the feasibility of certain evaluation methods.

Reliability & validity

The reliability of the findings depends on the thoroughness of the literature search and the consistency of identified themes. Validity is supported by drawing from multiple disciplines (HCI, InfoVis, Cartography) and employing both narrative and systematic review methods.

Think critically

How might the choice of physical material itself influence the encoding variables and the overall effectiveness of a data physicalisation?

Design Principles

"Effective data physicalisations are achieved through deliberate selection of encoding variables and rigorous, user-centred evaluation."

Understanding the available encoding variables and evaluation methods is crucial for designers creating physical data representations. This structured approach ensures that the resulting physicalisations are not only aesthetically pleasing but also effectively communicate data and meet user needs.

What This Means for Your Design

This research helps designers by giving them a checklist of ways to make physical data representations and a way to check if they work well.

How to use in your project

1.Use the identified encoding variables to justify your design choices for representing data in your physical product.
2.Incorporate the suggested evaluation criteria and methods to assess the success of your design in communicating information.

Add to My Project

Quick Cite

Paragraph starter

The design of this physical data representation was informed by research into data physicalisation, specifically by considering established encoding variables such as [mention specific variables used, e.g., size, colour, texture] to convey [mention data being represented]. The effectiveness of this encoding was evaluated using criteria aligned with [mention criteria, e.g., clarity, accuracy, engagement], employing methods such as [mention methods, e.g., user interviews, task-based observation] to ensure the data is communicated effectively to the target user.

Source

Multimodal Technologies and Interaction

Encoding Variables, Evaluation Criteria, and Evaluation Methods for Data Physicalisations: A Review

journal · 2023

View source

Questions About This Research

What does the research say about data physicalisation design: a framework for encoding, evaluation, and iteration?: Adopt a systematic approach by first understanding the available encoding variables, then defining clear evaluation criteria, and finally selecting appropriate methods to test the effectiveness of your data physicalisations. Evidence: Multimodal Technologies and Interaction (2023).
Why does "Data Physicalisation Design: A Framework for Encoding, Evaluation, and Iteration" matter for design?: Understanding the available encoding variables and evaluation methods is crucial for designers creating physical data representations. This structured approach ensures that the resulting physicalisations are not only aesthetically pleasing but also effectively communicate data and meet user needs.
How can designers apply this research?: Adopt a systematic approach by first understanding the available encoding variables, then defining clear evaluation criteria, and finally selecting appropriate methods to test the effectiveness of your data physicalisations.
What were the main findings?: Identification of a comprehensive set of encoding variables for data physicalisation.. Compilation of relevant evaluation criteria for assessing data physicalisations.. Categorization of methods suitable for evaluating data physicalisations.. Development of a conceptual framework and a seven-stage model for designing and evaluating data physicalisations.
What research method was used?: Narrative and Systematic Literature Review.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2023 journal from Multimodal Technologies and Interaction.
What should I do differently in my next project?: When designing a data physicalisation, consciously consider the physical properties you will use to represent data (e.g., shape, colour, texture, size) and plan how you will test its clarity and impact with users.
What are the limitations?: The review is based on existing literature, and novel encoding variables or evaluation methods may emerge over time. The effectiveness of specific criteria and methods may vary depending on the context and type of physicalisation.