Interactive Visual Analytics: Bridging Human Cognition and Complex Data

A special issue of Data (ISSN 2306-5729).

Deadline for manuscript submissions: 30 April 2026 | Viewed by 43

Special Issue Editors


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Guest Editor
Department of Computer Science, Faculty of Information and Media Studies, The University of Western Ontario, London, ON N6A 3K7, Canada
Interests: human-data interaction; visual analytics; human-centred informatics; interactive visualizations; joint human–computer cognitive
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Guest Editor
Department of Computer Science, Western University, London, ON, Canada
Interests: machine learning; data mining and knowledge discovery; pattern recognition; statistical learning; predictive modelling

Special Issue Information

Dear Colleagues,

In an era defined by an unprecedented deluge of data, the ability to extract meaningful insights, detect patterns, and make informed decisions is more critical and challenging than ever. Visual Analytics has emerged as a powerful scientific discipline to address this challenge, integrating automated data analysis with interactive visualizations to create a synergistic human-in-the-loop process. At the heart of this discipline is interaction, the mechanism that empowers users to navigate, manipulate, and query vast data spaces, transforming static images into dynamic analytical dialogues.

This Special Issue aims to bring together leading researchers and practitioners to share the latest advances in the theory, design, application, and evaluation of Interactive Visual Analytics (IVA). We are particularly interested in novel work that pushes the boundaries of how human cognition can be augmented through interactive systems to tackle the scale and complexity of modern datasets, from scientific research and business intelligence to the growing demands of explainable AI.

We invite the submission of high-quality, original research articles that have not been previously published and are not under review for another journal or conference.

Theoretical Foundations:

  • Formal models of interaction in visual analytics
  • Cognitive and perceptual theories for interactive data exploration
  • Taxonomies and frameworks for visual analysis and reasoning

Novel Systems and Techniques:

  • Innovative interaction techniques for high-dimensional, temporal, geospatial, graph, and other complex data types
  • Scalable visual analytics systems for big data
  • Human-in-the-loop methods for data transformation, cleaning, and integration
  • Advances in direct manipulation, brushing and linking, and dynamic queries

Visual Analytics and Artificial Intelligence (AI):

  • Interactive systems for explainable AI (XAI) and interpretable machine learning
  • Visual analytics for model steering, debugging, and comparison
  • Human-AI collaboration through interactive visual interfaces
  • Systems that integrate natural language interaction with visual analysis

Applications and Case Studies:

  • IVA applications in key domains such as:
  • Healthcare, bioinformatics, and personalized medicine
  • Cybersecurity and intelligence analysis
  • Business intelligence and financial analysis
  • Climate science, energy, and environmental studies
  • Digital humanities and social sciences
  • IoT, smart cities, and urban planning

Emerging Technologies and Platforms:

  • Immersive analytics using Virtual and Augmented Reality (VR/AR)
  • Collaborative visual analytics on large-scale and multi-surface displays
  • Touch, tangible, and multimodal interaction for data analysis
  • Mobile visual analytics

Evaluation and Methodology:

  • Novel methodologies for evaluating the effectiveness and usability of IVA systems
  • Longitudinal studies and in-depth case studies of visual analytics in practice
  • Metrics for measuring insight generation, discovery, and user engagement

Prof. Dr. Kamran Sedig
Dr. Sheikh Shaugat Abdullah
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • interactive visual analytics (IVA)
  • human-in-the-loop
  • sensemaking
  • explainable AI (XAI)
  • big data visualization
  • human-AI collaboration
  • high-dimensional data visualization
  • interaction theory

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Published Papers

This special issue is now open for submission.
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