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Participation at IV 2022

/in , , , /by

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

Call for Articles to Special Issue in Journal of Electronics

/in , , , /by

Prof. Dr.-Ing. Kawa Nazemi is organizing together with Prof. Dr. Egils Ginters and Dr. Michael Bažant a special issue on “Visual Analytics, Simulation, and Decision-Making Technologies” in the MDPI Journal of Electronics.

The Journal of Electronics is an international, peer-reviewed, open-access journal on the science of electronics and its applications published semimonthly online by MDPI. It publishes reviews, research articles, short communications, and letters. The aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided.

With the recent rise in cutting-edge technologies such as artificial intelligence, new and unsolved societal economic challenges can be solved sophisticatedly. Disciplines such as visual analytics, simulation, data analytics, natural language processing, and image and video processing combined with the human in the interaction loop have led to new systems, methods, concepts, and architectural designs that help us to face societal challenges, e.g., climate, mobility, sustainability, smart city. Furthermore, these approaches lead to predicting likely future scenarios in the economy. These enhancements enable gathering the market relevance of upcoming technologies, analyzing the competitors and other forthcoming competitive technologies, and analyzing new markets for technologies. Thus, the aspect of sustainability plays an increasing role, even in market positioning or in the development and deployment of new technologies.

In this Special Issue, we are interested in systems, system architectures, computational techniques, methods and models, and literature reviews in the areas of analytical decision making, collaborative work, sustainability, economy, simulation, object monitoring, and behavior detection.

From a methodological point of view, the focus is on combining technological approaches from various disciplines to provide new ways and methods for analyzing data and models and enabling novel approaches for solving societal and economic challenges. On the practical side, we are looking for algorithms, software, prototypes, and demonstrators of decision-making support with the human-in-the-loop in various application fields. Topics of interest include but are not limited to the following:

  • Visual analytics and information visualization
  • Artificial intelligence and machine learning
  • Simulation and modeling for digital twins
  • Collaboration systems and collaborative work
  • Data analytics and natural language processing
  • Analytical systems for mobility, transportation, and traffic
  • Analytical systems for sustainability and environment
  • Analytical systems for corporate foresight
  • Analytical systems for smart manufacturing
  • Technologies for smart city, virtual, and augmented reality applications
  • Quantum and high-performance computing use
  • Digital wallet and blockchain synergy
  • Fault diagnosis in cyber-physical systems
  • Predictive maintenance in Industry 4.0
  • Object monitoring and behavior detection

If you are interested in the journal and in submitting an article, please note the information on the special issue website: Special Issue “Visual Analytics, Simulation, and Decision-Making Technologies”.

Advisory Board of the EUt+ Academic Press

/in , , , , , , , /by

Professor Kawa Nazemi was assigned as an advisory board member of the academic press of the European University of Technology (EUt+).

The EUt+ is an alliance of eight universities that make up the European University of Technology. The partners are Technical University of Sofia, Cyprus University of Technology, University of Technology Troyes, Hochschule Darmstadt, University of Applied Sciences, Technological University Dublin, Riga Technical University, Technical University of Cluj-Napoca, Technical University of Cartagena.

The EUT+ is part of the European initiative to build a European Education Area. The EUT+ Academic Press is an open access academic press. All material is free to read online. The academic press is committed to the principle that scholarship should be available to all without barriers or paywalls. It offers authors a global readership and thus contributes to the dissemination of knowledge. The academic press welcomes quality works of scholarship regardless of the subject area. The material is licensed under Creative Commons Attribution-Non-commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license We are committed to Gold Open Access which is the free, immediate and permanent online access to a publication’s version of record. Currently, there are no fees for authors.

Please find more information here.

Book appeared – Integrating Artificial Intelligence and Visualization

/in , , /by
Professor Kawa Nazemi edited together with colleagues from the London South Bank University, Instituto Superior de Engenharia de Lisboa, and the Central Washington University enhanced contributions of selected papers of the International Conference on Information Visualisation particularly on the intersection of artificial intelligence and visualization. The book will appear in the series Studies in Computational Intelligence by Springer Nature. The book “Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery” is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytics. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is a fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering “n-D glasses,” where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain.
Read more

Call for Papers to the International Information Visualisation Conference (iV 2022)

/in , , /by

We are again co-organizing the track International Symposium Visual Analytics and Data Science (VA) at the next International Information Visualisation Conference (iV 2022) in Vienna, Austria on 19-22 July 2022. 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.

In the present information era, most aspects of our lives depend on and are driven by data, information, knowledge, user experience, and culture. Information Visualisation, Visual Analytics, Business Intelligence, Machine Learning, and Data Science are only a few research areas of the current state of art enabling to increase the comprehension of the information on which is based the infrastructure of our society. The International Conference on Information Visualisation is concentrated around these hot topics. As in the previous edition, also this year there will be the opportunity of starting international cooperations and European research projects, and of discussing with international relevance keynote speakers. The conference is articulated in symposia, with details and further information available on the Symposia webpage.

 

Your work may be submitted as

 

These submissions include, but are not limited to

  • Information Visualisation Theory & Practice
  • Narrative
  • Visualization and Storytelling
  • Glyphs: Shapes, Icons, Text and Imagery in Visualization
  • Information Visualization Evaluation
  • Visual Analytics
  • Social media analytics
  • GeoVisual Analytics and Spatial-Temporal Analytics
  • Knowledge Visualization and Visual Thinking
  • Advances in Interactive and Visual Data Clustering
  • Visualisation in Business Intelligence and Open Data
  • Knowledge Domain Visualisation
  • Open Source Intelligence and Web Mining & Web Visualization
  • Co-operative Design Visualisation
  • Human-Computer Interaction for Information Visualization
  • Graph and Network Visualisation
  • Digital Humanities Knowledge Visualization
  • BioMedical Visualization
  • Visualization, Art, & Design
  • Symposium of Digital Art and Gallery
  • Augmented Reality Visualization and Art
  • Computer Animation, Information Visualisation, and Digital Effects
  • Computer Games and their applications (CGa)
  • Multimedia and E-learning
  • Digital Entertainment

 

Interested parties in the area of Visual Computing are invited to submit paper their proposal until 15 March 2022 via the conference submission system.

Please note our summarization of the 26th International Conference Information Visualization (iV 2022) event.

26th International Conference Information Visualization (iV 2022)

/in /by

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

/in , , , /by

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

Call for Articles to Special Issue in Journal of Electronics

/in , , , /by

Prof. Dr.-Ing. Kawa Nazemi is organizing together with Prof. Dr. Egils Ginters and Dr. Michael Bažant a special issue on “Visual Analytics, Simulation, and Decision-Making Technologies” in the MDPI Journal of Electronics.

The Journal of Electronics is an international, peer-reviewed, open-access journal on the science of electronics and its applications published semimonthly online by MDPI. It publishes reviews, research articles, short communications, and letters. The aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided.

With the recent rise in cutting-edge technologies such as artificial intelligence, new and unsolved societal economic challenges can be solved sophisticatedly. Disciplines such as visual analytics, simulation, data analytics, natural language processing, and image and video processing combined with the human in the interaction loop have led to new systems, methods, concepts, and architectural designs that help us to face societal challenges, e.g., climate, mobility, sustainability, smart city. Furthermore, these approaches lead to predicting likely future scenarios in the economy. These enhancements enable gathering the market relevance of upcoming technologies, analyzing the competitors and other forthcoming competitive technologies, and analyzing new markets for technologies. Thus, the aspect of sustainability plays an increasing role, even in market positioning or in the development and deployment of new technologies.

In this Special Issue, we are interested in systems, system architectures, computational techniques, methods and models, and literature reviews in the areas of analytical decision making, collaborative work, sustainability, economy, simulation, object monitoring, and behavior detection.

From a methodological point of view, the focus is on combining technological approaches from various disciplines to provide new ways and methods for analyzing data and models and enabling novel approaches for solving societal and economic challenges. On the practical side, we are looking for algorithms, software, prototypes, and demonstrators of decision-making support with the human-in-the-loop in various application fields. Topics of interest include but are not limited to the following:

  • Visual analytics and information visualization
  • Artificial intelligence and machine learning
  • Simulation and modeling for digital twins
  • Collaboration systems and collaborative work
  • Data analytics and natural language processing
  • Analytical systems for mobility, transportation, and traffic
  • Analytical systems for sustainability and environment
  • Analytical systems for corporate foresight
  • Analytical systems for smart manufacturing
  • Technologies for smart city, virtual, and augmented reality applications
  • Quantum and high-performance computing use
  • Digital wallet and blockchain synergy
  • Fault diagnosis in cyber-physical systems
  • Predictive maintenance in Industry 4.0
  • Object monitoring and behavior detection

If you are interested in the journal and in submitting an article, please note the information on the special issue website: Special Issue “Visual Analytics, Simulation, and Decision-Making Technologies”.

Advisory Board of the EUt+ Academic Press

/in , , , , , , , /by

Professor Kawa Nazemi was assigned as an advisory board member of the academic press of the European University of Technology (EUt+).

The EUt+ is an alliance of eight universities that make up the European University of Technology. The partners are Technical University of Sofia, Cyprus University of Technology, University of Technology Troyes, Hochschule Darmstadt, University of Applied Sciences, Technological University Dublin, Riga Technical University, Technical University of Cluj-Napoca, Technical University of Cartagena.

The EUT+ is part of the European initiative to build a European Education Area. The EUT+ Academic Press is an open access academic press. All material is free to read online. The academic press is committed to the principle that scholarship should be available to all without barriers or paywalls. It offers authors a global readership and thus contributes to the dissemination of knowledge. The academic press welcomes quality works of scholarship regardless of the subject area. The material is licensed under Creative Commons Attribution-Non-commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license We are committed to Gold Open Access which is the free, immediate and permanent online access to a publication’s version of record. Currently, there are no fees for authors.

Please find more information here.

Book appeared – Integrating Artificial Intelligence and Visualization

/in , , /by
Professor Kawa Nazemi edited together with colleagues from the London South Bank University, Instituto Superior de Engenharia de Lisboa, and the Central Washington University enhanced contributions of selected papers of the International Conference on Information Visualisation particularly on the intersection of artificial intelligence and visualization. The book will appear in the series Studies in Computational Intelligence by Springer Nature. The book “Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery” is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytics. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is a fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering “n-D glasses,” where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain.
Read more

Call for Papers to the International Information Visualisation Conference (iV 2022)

/in , , /by

We are again co-organizing the track International Symposium Visual Analytics and Data Science (VA) at the next International Information Visualisation Conference (iV 2022) in Vienna, Austria on 19-22 July 2022. 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.

In the present information era, most aspects of our lives depend on and are driven by data, information, knowledge, user experience, and culture. Information Visualisation, Visual Analytics, Business Intelligence, Machine Learning, and Data Science are only a few research areas of the current state of art enabling to increase the comprehension of the information on which is based the infrastructure of our society. The International Conference on Information Visualisation is concentrated around these hot topics. As in the previous edition, also this year there will be the opportunity of starting international cooperations and European research projects, and of discussing with international relevance keynote speakers. The conference is articulated in symposia, with details and further information available on the Symposia webpage.

 

Your work may be submitted as

 

These submissions include, but are not limited to

  • Information Visualisation Theory & Practice
  • Narrative
  • Visualization and Storytelling
  • Glyphs: Shapes, Icons, Text and Imagery in Visualization
  • Information Visualization Evaluation
  • Visual Analytics
  • Social media analytics
  • GeoVisual Analytics and Spatial-Temporal Analytics
  • Knowledge Visualization and Visual Thinking
  • Advances in Interactive and Visual Data Clustering
  • Visualisation in Business Intelligence and Open Data
  • Knowledge Domain Visualisation
  • Open Source Intelligence and Web Mining & Web Visualization
  • Co-operative Design Visualisation
  • Human-Computer Interaction for Information Visualization
  • Graph and Network Visualisation
  • Digital Humanities Knowledge Visualization
  • BioMedical Visualization
  • Visualization, Art, & Design
  • Symposium of Digital Art and Gallery
  • Augmented Reality Visualization and Art
  • Computer Animation, Information Visualisation, and Digital Effects
  • Computer Games and their applications (CGa)
  • Multimedia and E-learning
  • Digital Entertainment

 

Interested parties in the area of Visual Computing are invited to submit paper their proposal until 15 March 2022 via the conference submission system.

Please note our summarization of the 26th International Conference Information Visualization (iV 2022) event.

26th International Conference Information Visualization (iV 2022)

/in /by

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:

Online @ 25th International Conference Information Visualization (iV 2021)

/in /by

We are co-organizing the International Symposium Visual Analytics and Data Science at the next International Information Visualisation Conference (iV 2021), 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 viewed as the science of analytical reasoning empowered by interactive visualizations. It combines interactive visualizations with models and approaches of machine learning and artificial intelligence, enabling solving complex analytical tasks by uncovering hidden patterns in data.
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, whereas Visual Analytics allows commonly a direct manipulation of the underlying models through graphical representations. By leveraging human perception of the visual space, patterns that might not otherwise be discovered. Visual Analytics utilizes concepts from a wide variety of 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.

Topics of interest:

  • Combining visual and computational methods of data analysis
  • Visual querying
  • Visual analytics of spatial, temporal, and spatiotemporal data
  • Knowledge construction and management in visual analytics
  • Privacy issues in visual analytics
  • Cognitive approaches and explanations for visual data mining
  • Visualization of the data mining algorithm
  • Scalability issues
  • Empirical studies of performance
  • Evaluation of visual data mining methods
  • Collaborative visualization and mining
  • Applications of visual data mining and analytics
  • Case studies
  • Computational steering for long-running data mining applications
  • Reviews and surveys of related literature


Related news for further information:

Book Chapter published in Student Handbook “Praxishandbuch Forschungsdatenmanagement”

/in , , , , /by

We are glad to announce that our chapter to the student handbook “Praxishandbuch Forschungsdatenmanagement” (Engl.: practice handbook research data management) was accepted and got printed at De Gruyter. Our chapter addresses the foundations of Data Visualization, which is explained on behalf of selected examples.

The book covers nowadays societal research challenges in pespective of data management and how current approaches in research can helo to handle it. Therewith, events such as the entry into force of the code “Guidelines for Safeguarding Good Scientific Practice” of the German Research Foundation (DFG) or the establishment of the National Research Data Infrastructure (NFDI) and the European Open Science Cloud (EOSC) put providers, producers and users of research data in front of specialist, technical, legal and organizational challenges. The practical handbook for research data management comprehensively covers all relevant aspects of research data management and the current framework conditions in the data ecosystem.

In particular, the practical implications of data policy and law, the respective data market, data culture, personal qualification, data management and “FAIR” data transfer and reuse are examined. The practical handbook also provides an overview of projects, developments and challenges in Research data management.

IEEE Information Technology and Management Science Conference

/in , /by

The 61st INTERNATIONAL SCIENTIFIC CONFERENCE OF RIGA TECHNICAL UNIVERSITY: IEEE Section of Information Technology and Management Science (ITMS 2020) aims at bringing together young scientists and researchers from information technologies and management sciences in an effort to promote and encourage cross-fertilization of ideas and tools related but not limited to the general topics of the conference, such as Information Technology, Information Systems, Computer Technologies, Data Processing, System Security and Control, Modelling and Simulation, Automatic Control, E-Commerce and E-Governance, Cloud Computing, Human Computer Interaction, Cyber-Physical Systems, Intelligent Systems, Internet of Everything.

Due to the COVID-19 pandemic, the conference will be hold online.

 

Related news for further information:

Three Papers Accepted at IEEE Information Technology and Management Science Conference (ITMS 2020)

/in , , , , /by

Three of our submitted collaboration papers got accepted at the this year’s IEEE Information Technology and Management Science Conference 2020. The conference aims at bringing together young scientists and researchers from information technologies and management sciences in an effort to promote and encourage cross-fertilization of ideas and tools related to the general topics of the conference, such as Information Technology, Information Systems, Computer Technologies, Data Processing, System Security and Control, Modelling and Simulation, Automatic Control, E-Commerce and E-Governance, Cloud Computing, Human Computer Interaction, Cyber-Physical Systems, Intelligent Systems, Internet of Everything.

Paper #1: Visual Analytics Indicators for Mobility and Transportation

Abstract:
Visual Analytics enables a deep analysis of complex and multivariate data by applying machine learning methods and interactive visualization. These complex analyses lead to gain insights and knowledge for a variety of analytics tasks to enable the decision-making process. The enablement of decision-making processes is essential for managing and planning mobility and transportation. These are influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans’ mobility behavior. New technologies will lead to a different mobility behavior with new constraints. These changes in mobility behavior and logistics require analytical systems to forecast the required information and probably appearing changes. These systems have to consider different perspectives and employ multiple indicators. Visual Analytics enable such analytical tasks. We introduce in this paper the main indicators for Visual Analytics for mobility and transportation that are e exemplary explained through two case studies to illustrate the advantages of such systems. The examples are aimed to demonstrate the benefits of Visual Analytics in mobility.

Link to paper/fulltext: DOI: 10.1109/ITMS51158.2020.9259321

More information about the technology and topic: Scitics for Visual Trend Analytics, Business Analytics,  Trend Analytics and Technology Foresights

Paper #2: Innovations in Mobility and Logistics: Assistance of Complex Analytical Processes in Visual Trend Analytics

Abstract:
A variety of new technologies and business ideas are arising in the domain of mobility and logistics. It can be differentiated between fundamental new approaches, e.g. central packaging stations or deliveries via drones and minor technological advancements that aim on more ecologically and economic transportation. The need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance is growing. The users’ behavior is commonly investigated in adaptive systems, which is considering the induvial preferences of users, but neglecting often the tasks and goals of the analysis. A process-related supports could assist to solve an analytical task in a more efficient and effective way. We introduce in this paper an approach that enables non-professionals to perform visual trend analysis through an advanced process assistance based on process mining and visual adaptation. This allows to calculate a process model based on events, which is the baseline for process support feature calculation. These features in form of visual adaptations and the process model enable assisting non-experts in complex analytical tasks.

Link to paper/fulltext: DOI: 10.1109/ITMS51158.2020.9259309

More information about the technology and topic: Scitics for Visual Trend Analytics, Business Analytics,  Trend Analytics and Technology Foresights

Paper #3: On Microservice Architecture Based Communication Environment for Cycling Map Developing and Maintenance Simulator

Abstract:
Urban transport infrastructure nowadays involves environmentally friendly modes of transport, the most democratic of which is cycling. Citizens will use bicycles if a reasonably designed cycle path scheme will be provided. Cyclists also need to know the characteristics and load of the planned route before the trip. Prediction can be provided by simulation, but it is often necessary to use heterogeneous and distributed models that require a specific communication environment to ensure interaction. The article describes an easy communication environment that is used to implement interaction and interoperability in a multi-agent-based cycle path design and exploitation simulator, where each domain simulation is performed as a microservice.

Link to paper/fulltext: DOI: 10.1109/ITMS51158.2020.9259299

More information about the the topic: eGovernance and Policy Modeling

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