Our group presented at this year’s Information Visualisation Conference (iV 2022) two papers entitled “Visual Analytics for Systematic Reviews According to PRISMA” and “Visual Collaboration – An Approach for Visual Analytical Collaborative Research”. In addition, Professor Kawa Nazemi, the head of the research group, was a co-chair of the conference and chaired the program committee and various sessions and tracks. Due to the ease of COVID travel restrictions, we were able to participate in person Vienna. The iV 2022 is an international conference that aims to provide a foundation for integrating information visualization’s human-centered, technological and strategic aspects to promote international exchange, cooperation, and development.

Paper #1: Visual Analytics for Systematic Reviews According to PRISMA

Lead author: Lennart B. Sina

Abstract:
Systematic reviews play an essential role in various disciplines. Particularly, in biomedical sciences, systematic reviews according to a predefined schema and protocol are how related literature is analyzed. Although a protocol-based systematic review is replicable and provides the required information to reproduce each step and refine them, such a systematic review is time-consuming and may get complex. To face this challenge, automatic methods can be applied that support researchers in their systematic analysis process. The combination of artificial intelligence for automatic information extraction from scientific literature with interactive visualizations as a Visual Analytics system can lead to sophisticated analysis and protocoling of the review process. We introduce in this paper a novel Visual Analytics approach and system that enables researchers to visually search and explore scientific publications and generate a protocol based on the PRISMA protocol and the PRISMA statement.

Link to paper/fulltext: Soon available

Paper #2: Visual Collaboration – An Approach for Visual Analytical Collaborative Research

Lead author: Midhad Blazevic

Abstract:

Studies have shown that collaboration in scientific fields is rising and considered enormously important. However, collaboration has proved to be challenging for various reasons, among others, the requirements for human-machine workflows. The importance of scientific collaboration lies in the complexity of the challenges that are faced today. The more complex the challenge, the more scientists should work together. The current form of collaboration in the scientific community is not as intelligent as it should be. Scientists have to multitask with various applications, often losing cognitive focus. Collaboration itself is very nearsighted as it is usually conducted not solely based on expertise but instead on social or local networks. We introduce a single-source visual collaboration approach based on learning methods in this work. We use machine learning and natural language processing approaches to improve the traditional research and development process and create a system that facilitates and encourages collaboration based on expertise, enhancing the research collaboration process in many ways. Our approach combines collaborative Visual Analytics with enhanced collaboration techniques to support researchers from different disciplines

Link to paper/fulltext: Soon available

We are co-organizing the International Symposium Visual Analytics and Data Science at the next International Information Visualisation Conference (iV 2022), which is held online. The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development. The proceedings will be published as usual in IEEE Xplore.

Visual Analytics is the science of analytical reasoning empowered by interactive visualizations. The research on Visual Analytics is closely related to that of Data Science. Both areas seek to enhance the knowledge discovery process using machine learning, data mining, and artificial intelligence methods. In contrast, Visual Analytics allows direct manipulation of the underlying models through graphical representations commonly. By leveraging human perception of the visual space, patterns that might not otherwise be discovered emerge. Visual Analytics utilizes concepts from various disciplines, including computer graphics, information visualization, machine learning, artificial intelligence, knowledge discovery, cognition, and visual perception.

Papers on all aspects of Visual Analytics and Data Science are solicited. Papers will be refereed and appear in the main conference proceedings published by Conference Publishing Services CPS – Conference Publishing Services, – Library of Congress/ISSN, ISBN, and other bibliographical registration details; Arrange for indexing through INSPEC, EI (Compendex), Thomson ISI, and other indexing services. A selection of the best papers will be recommended for publication in special issues of scientific journals, or as an edited book.

The topics of interest include but are not limited to:

• Combining visual and computational methods of Data Analysis, Machine Learning, and Artificial Intelligence
• Visual Analytics models and approaches
• Novel Visual Analytics applications
• Visual Trend Analytics
• Visual Analytics, geo-visualization and geographical visualization of spatial, temporal, and Spatio-temporal data
• Visualization support for multi-criteria decision analysis related to multivariate and spatial data
• Knowledge construction and management in Visual Analytics
• Guidance in Visual Analytics
• Intelligent approaches of Visual Analytics and Data Science
• Adaptive Visual Analytics
• HCI issues of geographical and Spatio-temporal visual analytics
• Cognitive approaches and explanations for Visual Analytics
• Visual Analytics for explaining AI
• Visualization of Data Mining algorithms
• Empirical performance studies
• Evaluation of Visual Data Mining methods
• Collaborative Visual Analytics and Data Science
• Computational steering for long-running Data Mining applications
• Reviews and surveys of related literature

Related news for further information:

• Participation at IV 2022
• Call for Papers to the International Information Visualisation Conference (iV 2022)