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Best Paper Award at the iV 2021

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We are proud to announce that our paper on “Visual Analytics and Similarity Search – Interest-based Similarity Search in Scientific Data” at the iV2021 conference was honored with “The Best Paper Award” for its innovative contribution in terms of originality of concepts and application in Visual Analytics and Data Science. The “Best Paper Awards” is given to contributions that will be selected by the committee among the papers presented in iV2021 and applied for the award. The study’s relevance to the symposium’s scope, its scientific contribution, writing/presentation style will be considered in the evaluation process as well.

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 conference was held virtually at the University of Technology, Sydney.

Two Paper Accepted at 24rd Internation Conference Information Visualization (iV 2020)

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We are very glad to be accepted for presenting our papers titled “Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing” and “An Industry 4.0-Ready Visual Analytics Model for Context-Aware Diagnosis in Smart Manufacturing” at the high-class conference Information Visualisation Conference (iV 2020). Due to Corona epidemic the conference is hold virtually. The iV 2020 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.

Paper #1: Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing

Abstract:
Scientific publications are an essential resource for detecting emerging trends and innovations in a very early stage, by far earlier than patents may allow. Thereby Visual Analytics systems enable a deep analysis by applying commonly unsupervised machine learning methods and investigating a mass amount of data. A main question from the Visual Analytics viewpoint in this context is, do abstracts of scientific publications provide a similar analysis capability compared to their corresponding full-texts? This would allow to extract a mass amount of text documents in a much faster manner. We compare in this paper the topic extraction methods LSI and LDA by using full text articles and their corresponding abstracts to obtain which method and which data are better suited for a Visual Analytics system for Technology and Corporate Foresight. Based on a easy replicable natural language processing approach, we further investigate the impact of lemmatization for LDA and LSI. The comparison will be performed qualitative and quantitative to gather both, the human perception in visual systems and coherence values. Based on an application scenario a visual trend analytics system will further illustrate the outcomes.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00065

More information about the technology: Scitics for Visual Trend Analytics

Paper#2: An Industry 4.0-Ready Visual Analytics Model for Context-Aware Diagnosis in Smart Manufacturing

Abstract:
The integrated cyber-physical systems in Smart Manufacturing generate continuously vast amount of data. These complex data are difficult to assess and gather knowledge about the data. Tasks like fault detection and diagnosis are therewith difficult to solve. Visual Analytics mitigates complexity through the combined use of algorithms and visualization methods that allow to perceive information in a more accurate way. Thereby, reasoning relies more and more on the given situation within a smart manufacturing environment, namely the context. Current general Visual Analytics approaches only provide a vague definition of context. We introduce in this paper a model that specifies the context in Visual Analytics for Smart Manufacturing. Additionally, our model bridges the latest advances in research on Smart Manufacturing and Visual Analytics. We combine and summarize methodologies, algorithms and specifications of both vital research fields with our previous findings and fuse them together. As a result, we propose our novel industry 4.0-ready Visual Analytics model for context-aware diagnosis in Smart Manufacturing.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00064

Elected in the Board of Publication Chairs @ International Information Visualisation Conference (iV2020)

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Professor Dr. Kawa Nazemi was elected as member of the publication chair board of the International Information Visualisation Conference (iV 2020) in Vienna, Austria. 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 scope of the conference covers the following topics:

  • 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 of spatial, temporal, and spatio-temporal data
  • Knowledge construction and management in Visual Analytics
  • Guidance in Visual Analytics
  • Intelligent approaches of Visual Analytics and Data Science
  • Adaptive 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

Please note that the IV2020 will be held online and the submission deadline was extended. The processings will be published as usual in IEEE Xplore.

Our Group co-organizes the main symposium 12th International Symposium Visual Analytics and Data Science.

VIS-Group co-organizes the International Information Visualisation Conference (iV2020)

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We are co-organizing the track International Symposium Visual Analytics and Data Science (VA) at the next International Information Visualisation Conference (iV 2020) in Vienna, Austria on 28-31 July 2020. 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.

Interested parties in the arae of Visual Computing are invited to submit paper propsals until 15 March 2020 via the conference submission system. Please note the covered topics and the call for papers, as well as the submision guidelines.

Please note our summarization to the 24rd International Conference Information Visualization (iV 2020) event.

Paper accepted at 23rd Internation Conference Information Visualization (iV 2019)

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We are very glad to be accepted for presenting our paper titled “Visual Analytics for Analyzing Technological Trends from Text” at the high-class conference iV 2019 in Paris, France. 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.

Paper: Visual Analytics for Analyzing Technological Trends from Text

Abstract:
The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends.

Link to paper/fulltext: https://dx.doi.org/10.1109/IV.2019.00041

More information about the technology: Scitics for Visual Trend Analytics

Demo video:

Events

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:

Best Paper Award at the iV 2021

/in , , /by

We are proud to announce that our paper on “Visual Analytics and Similarity Search – Interest-based Similarity Search in Scientific Data” at the iV2021 conference was honored with “The Best Paper Award” for its innovative contribution in terms of originality of concepts and application in Visual Analytics and Data Science. The “Best Paper Awards” is given to contributions that will be selected by the committee among the papers presented in iV2021 and applied for the award. The study’s relevance to the symposium’s scope, its scientific contribution, writing/presentation style will be considered in the evaluation process as well.

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 conference was held virtually at the University of Technology, Sydney.

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:

Two Paper Accepted at 24rd Internation Conference Information Visualization (iV 2020)

/in , , , , /by

We are very glad to be accepted for presenting our papers titled “Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing” and “An Industry 4.0-Ready Visual Analytics Model for Context-Aware Diagnosis in Smart Manufacturing” at the high-class conference Information Visualisation Conference (iV 2020). Due to Corona epidemic the conference is hold virtually. The iV 2020 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.

Paper #1: Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing

Abstract:
Scientific publications are an essential resource for detecting emerging trends and innovations in a very early stage, by far earlier than patents may allow. Thereby Visual Analytics systems enable a deep analysis by applying commonly unsupervised machine learning methods and investigating a mass amount of data. A main question from the Visual Analytics viewpoint in this context is, do abstracts of scientific publications provide a similar analysis capability compared to their corresponding full-texts? This would allow to extract a mass amount of text documents in a much faster manner. We compare in this paper the topic extraction methods LSI and LDA by using full text articles and their corresponding abstracts to obtain which method and which data are better suited for a Visual Analytics system for Technology and Corporate Foresight. Based on a easy replicable natural language processing approach, we further investigate the impact of lemmatization for LDA and LSI. The comparison will be performed qualitative and quantitative to gather both, the human perception in visual systems and coherence values. Based on an application scenario a visual trend analytics system will further illustrate the outcomes.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00065

More information about the technology: Scitics for Visual Trend Analytics

Paper#2: An Industry 4.0-Ready Visual Analytics Model for Context-Aware Diagnosis in Smart Manufacturing

Abstract:
The integrated cyber-physical systems in Smart Manufacturing generate continuously vast amount of data. These complex data are difficult to assess and gather knowledge about the data. Tasks like fault detection and diagnosis are therewith difficult to solve. Visual Analytics mitigates complexity through the combined use of algorithms and visualization methods that allow to perceive information in a more accurate way. Thereby, reasoning relies more and more on the given situation within a smart manufacturing environment, namely the context. Current general Visual Analytics approaches only provide a vague definition of context. We introduce in this paper a model that specifies the context in Visual Analytics for Smart Manufacturing. Additionally, our model bridges the latest advances in research on Smart Manufacturing and Visual Analytics. We combine and summarize methodologies, algorithms and specifications of both vital research fields with our previous findings and fuse them together. As a result, we propose our novel industry 4.0-ready Visual Analytics model for context-aware diagnosis in Smart Manufacturing.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00064

Elected in the Board of Publication Chairs @ International Information Visualisation Conference (iV2020)

/in , , /by

Professor Dr. Kawa Nazemi was elected as member of the publication chair board of the International Information Visualisation Conference (iV 2020) in Vienna, Austria. 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 scope of the conference covers the following topics:

  • 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 of spatial, temporal, and spatio-temporal data
  • Knowledge construction and management in Visual Analytics
  • Guidance in Visual Analytics
  • Intelligent approaches of Visual Analytics and Data Science
  • Adaptive 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

Please note that the IV2020 will be held online and the submission deadline was extended. The processings will be published as usual in IEEE Xplore.

Our Group co-organizes the main symposium 12th International Symposium Visual Analytics and Data Science.

VIS-Group co-organizes the International Information Visualisation Conference (iV2020)

/in , , /by

We are co-organizing the track International Symposium Visual Analytics and Data Science (VA) at the next International Information Visualisation Conference (iV 2020) in Vienna, Austria on 28-31 July 2020. 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.

Interested parties in the arae of Visual Computing are invited to submit paper propsals until 15 March 2020 via the conference submission system. Please note the covered topics and the call for papers, as well as the submision guidelines.

Please note our summarization to the 24rd International Conference Information Visualization (iV 2020) event.

Paper accepted at 23rd Internation Conference Information Visualization (iV 2019)

/in , , , , /by

We are very glad to be accepted for presenting our paper titled “Visual Analytics for Analyzing Technological Trends from Text” at the high-class conference iV 2019 in Paris, France. 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.

Paper: Visual Analytics for Analyzing Technological Trends from Text

Abstract:
The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends.

Link to paper/fulltext: https://dx.doi.org/10.1109/IV.2019.00041

More information about the technology: Scitics for Visual Trend Analytics

Demo video:

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