Challenges, Strategies and Adaptations on Interactive Dashboards

Mohammed Alhamadi

 

 

Introduction

 Interactive dashboards enable viewing and interacting with complex underlying data using visualisations such as charts, tables, maps, or even text typically on a single display. By bringing the most important information in a single place, dashboards enable performance monitoring and support decision making. Although nowadays dashboards are widely adopted in many domains, they involve challenges that prevent users from utilising them as they were intended. For example, having a dashboard with too much data can negatively affect decision making and lead to misleading interpretation. Through this research, we identify and investigate the challenges associated with dashboards, what users do in response to those challenges, and what adaptations can be applied to mitigate these challenges. Consequently, we aim to examine and evaluate a set of adaptation techniques that can improve the experience of users interacting with dashboards.

 

 

Research Questions

  • What are the interaction and information presentation challenges users encounter when they interact with dashboards?
  • What adaptations can be applied to dashboards? Which of these adaptations can be applied to address the problems found in RQ1.
  • How can we intervene to adapt the user interface? Do the adaptations improve the interaction with dashboards?

The relationship between dashboard challenges, user strategies, and adaptation techniques in our research: if we are able to establish a relationship between strategies to problems and we can detect these strategies in real time then we can adapt the user interface in real time or in the next release of the application. Then we can say that the introduced adaption techniques will have a positive effect on the challenges. Finally, the adaptation techniques might introduce unforeseen challenges which will then be detected again and dealt with accordingly.

 

 

Identified Challenges

The four identified kinds of challenges and how they relate to each other. The first category is User Flexibility challenges which include 9 challenges: design and customisation, data detail adjustment, user adaptability, display adaptability, situation adaptability, comparison support, system integration, automating & storytelling, and search functionality. The second category includes 6 challenges: visual literacy, analytic literacy, data literacy, ease of use, dashboard evaluation, and designers knowledge. The third category is Data Design challenges which include 9 challenges: data oversimplification, too much data, data and metadata, data quality, inaccurate data representation, data order and grouping, data-ink maximisation, key performance indicators and metrics, and data sources. The fourth and last category is Social Impact challenges with 8 challenges including data-driven thinking, technology resistance, automation, added value, data sharing, security and privacy, foresight deficiency, motivation or demotivation, and quality costs. User flexibility challenges are related to the users, data design challenges are related to the dashboard designers, visual, analytic and data literacy challenges are shared among users and designers, and social impact challenges span the dashboard, its users, and its designers, too.

 

User Flexibility Challenges

Visual, Analytical, and Data Literacy Challenges
Level of Detail Adjustment Visual Literacy
User Adaptability Analytic Literacy
Situation Adaptability Data Literacy
System Integration Ease of Use
Comparison Support Dashboard Evaluation
… …

Data Design Challenges

Social Impact Challenges
Data Oversimplification Data-driven Thinking
Too Much Data Added Value
Data Quality Sharing, Security & Trust
Data Sources Automation
Inaccurate Data Representation Technology Resistance
… …

 

 

What’s Next?

What is next in our research: first we will conduct a study to understand how users interact with dashboards with known challenges and what they do to overcome them. Then, we will interview expert dashboard designers to understand how adaptations can be built into dashboards. Then, in light of previous findings, we will build user models based on user goals, background, interests, etc. After that we will conduct a series of experiments to see if we can intervene to adapt dashboards based on what we learned from previous work.

 

https://doi.org/10.1145/3340631.3398678