Special Issue "Trends and Opportunities in Visualization and Visual Analytics"
Deadline for manuscript submissions: 28 February 2021.
Interests: information visualization; visual analytics; visual data mining; explainable machine learning; machine learning or data mining interpretability
Over the past few decades, significant advances in data production, storage, and dissemination are promoting a paradigm shift in science and our society towards more data-driven processes and decision-making. In this scenario, visualization tools and techniques are becoming popular, giving their inherent ability to ease communication and increase user trust. Many areas that habitually use data mining and machine learning solutions are now starting to adopt visualization as part of their analytical pipelines.
From physics, biology, and chemistry areas to data democratization initiatives and applications of machine learning interpretability, visualization is becoming essential when users play a central role in the analytical process. If the goal is to understand decisions made by machines or to help users to comprehend different phenomena based on data, interactive visual representations are becoming pervasive, creating novel research opportunities, and highlighting new trends in the field.
This Special Issue is aimed at industrial and academic researchers applying visualization methods to help people take full advantage of their data collections to interpret complex phenomena or make more informed decisions. The key areas of this Special Issue include, but are not limited to the following:
- Visual data analysis and knowledge discovery
- Visual data mining
- Graph visualization
- Visual analytical reasoning
- High-dimensional data and dimensionality reduction
- Text, document, and social media visualization
- Data management and knowledge representation
- Explainable machine learning by visualization
- Data-driven storytelling
- Machine learning interpretability
- Human-in-the-loop processing
- Interactive data mining and machine learning
- Progressive analytics
- Analytics in the fields of scholarly data, digital libraries, multimedia, scientific data, and social data
- Physics, chemistry, and biology visualization tools and applications
Prof. Dr. Fernando Paulovich
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 papers will be 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. Information 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 1400 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.
- Information visualization
- visual analytics
- machine learning interpretability
- visual data mining
- visualization tools and applications