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

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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

Midhad Blazevic defended his Master Thesis on Visual Search and Exploration for Scientific Publications through Similarity

/in , , , /by

In his thesis, Midhad Blazevic alyzes exploratory search systems which use sophisticated features, visualizations and similarity-based algorithms to enhance exploratory searches. Examining how similarity algorithms are currently used in combination with elements from information retrieval, natural language processing and visualizations, but also examine what exploratory search is, what the requirements are and what makes it so special in modern times. Furthermore, the user himself or herself will be analyzed as user behavior during exploratory searches is a key factor that has to be taken into consideration when looking to optimize the exploratory search process overall. Based on these aspects, means of improvement will be developed and showcased, which will be used to determine if there is an improvement in comparison to other well-known systems. The outcome of this thesis will present a prototype of an exploratory search system along with a practical use case.

Two Papers Accepted at 6th Collaborative European Research Conference (CERC 2020)

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At the this year’s Collaborative European Research Conference (CERC 2020) two of our students papers titled “Visual Dashboards in Trend Analytics to Observe Competitors and Leading Domain Experts” and “A Future Prospect for European Collaboration on Advanced Analytics in Economy and Society” were accepted for presentation. Due to Corona epidemic the conference is hold virtually. The multidisciplinary CERC is an annual event that takes place since 2011 when it was initiated by University partners across Europe. It brings together researchers from a wide range of disciplines in order to foster knowledge transfer, inter-disciplinary exchange and collaboration.

Paper #1: Visual Dashboards in Trend Analytics to Observe Competitors and Leading Domain Experts

Abstract:
The rapid changes due to digitalization challenges a variety of market players and forces them to find strategies to be aware of changes in these markets, particularly those that impacts their business. The main challenge is how a practical solution could look like and how technology can support market players in these trend ob-servation tasks. The paper outlines therefore a technological solution to observe specific authors e.g. researchers who influence a certain market or engineers of competitor. In many branches both are well-known groups to market players and there is almost the need of a technology that support the topical observation. The main contributions of this paper are next to the concept of how a visual dash-board could enable a market observation and how data has to be processed for it, the prototypical implementation which enables an evaluation later on. Further-more, the definition of a principal technological analysis for innovation and tech-nology management is created and is also an important contribution to the scien-tific community that specifically considers the technology perspective and it cor-responding requirements.

Link to paper/fulltext: http://ceur-ws.org/Vol-2815/CERC2020_paper14.pdf

More information about the technology: Scitics for Visual Trend Analytics

Paper #2: A Future Prospect for European Collaboration on Advanced Analytics in Economy and Society

Abstract:
Analytical Reasoning by applying machine learning approaches, artificial intelli-gence, NLP and visualizations allow to get deep insights into the different do-mains of various stakeholders and enable to solve complex tasks. Thereby the tasks are very heterogenous and subject of investigation in the different areas of application. These tasks or challenges should be defined by the stakeholders themselves and lead through a deep investigation to advanced analytical ap-proaches. We therefore set up a strategic alliance of research, enterprises and so-cietal organization with the goal of a strong collaboration to identify in a first step these challenges and workout technological solutions for each application scenar-io. We give in this paper a first draft of current challenges and technological ad-vancements. The main contribution of this paper is next to an accurate description of the current challenges in the analytics domain, also the description of an agen-da how these challenges can be solved. Furthermore, a process is explained, how the strategic alliance should act and organize their work to realize beneficial and useful analytical solutions.

Link to paper/fulltext: http://ceur-ws.org/Vol-2815/CERC2020_paper27.pdf

More information about the project and the expected collaboration project: EuroStraNet-project, VisCOST-project, partner network for COST

 

The whole proceedings of the CERC 2020 are available under: http://ceur-ws.org/Vol-2815/.

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

Paper accepted at 14th International Symposium on Visual Computing (ISVC 2019)

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Our paper entitled “A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management” is accepted at the visual computing conference ISVC 2019 in Lake Tahoe, NV, USA. The purpose of the International Symposium on Visual Computing (ISVC) is to provide a first-class forum for researchers, scientists, engineers and practitioners throughout the world to present their latest research findings, ideas, developments and applications in visual computing. ISVC seeks papers describing contributions to the state of the art and state of the practice in the four central areas of visual computing: computer vision, computer graphics, virtual reality, and visualization. The paper reflects some new on-going advancements of our innovative Trend Analytics solution Scitics.

Paper: A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management

Abstract:
Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analytics possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and do not include the human in the analysis process. Outcomes from research on information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics.

Link to paper/fulltext: https://dx.doi.org/10.1007/978-3-030-33723-0_23
Link to poster: https://dx.doi.org/10.5281/zenodo.3473065

More information about the technology: Scitics for Visual Trend Analytics

Best Paper Award at the iV 2019

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We are proud to announce that our last paper “Visual Analytics for Analyzing Technological Trends from Text” at the iV2019 conference in Paris was honored with “The Best Paper Award” for the innovative contribution in terms of originality of concepts and application. The “Best Paper Awards” is given to contributions which will be selected by the committee among the papers presented in iV2019 and applied for the award. Study’s relevance to the symposium’s scope, its scientific contribution, writing/presentation style will be considered in the evaluation process as well.

A short interview can be found here (German).

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 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:

Visual Trend Analytics@Information Science Trends: Search Engines and Information Retrieval

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The event “Information Science Trends: Search Engines and Information Retrieval”, organized and hosted by the European Chapter of the Association for Information Science and Technology, focuses on certain research topics introduced by invited speeches from research and industry. The major covered research areas are:

  • Retrieval research on web search engines, web services, professional information services, social media
  • Information seeking behavior
  • Information retrieval
  • Discovery systems
  • People interacting with search systems
  • Searching in the library and other scientific contexts
  • Understanding user behavior

Additionally, they will provide networking space to energetically share ideas and interests from the fields of information science and related disciplines.

At this event Prof. Dr. Nazemi gives a speech on “Visual Trend Analytics in Digital Libraries”, in particular based on the experiences with the own developed Scitics solution. Here he gives an overview about current research actions and challenges toward visual trend analysis, but also on opportunities and benefits for companies. In particular the digitalization challenges a number of small and medium sized enterprises to be aware of modern technologies and trends that revolute the market or impacts the current businesses

Show full event video on YouTube

The event takes places on April 26, 2019, at the Hamburg University of Applied Sciences in Hamburg, Germany.
More information about the event can be found on the event website or on the organizers website.

Kickoff of the National AVARTIM Project

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Today is the kickoff of the national project AVARTIM. The project has to goal of the early recognition of technological trends and the targeted handling of market and technology signals are becoming increasingly important for companies. As part of the project, “AVARTIM” is to be used to develop a software-supported process for recognizing and evaluating trends, market and technology signals in order to sustainably support the process of innovation and technology management. As part of the project, an infrastructure will be set up at Darmstadt University of Applied Sciences, which is modular and thus able to react quickly to technological changes. The infrastructure to be developed here serves as preliminary research and initial technology both for industrial use by and with the SME partners as well as for the application for joint projects. First of all, participation in the LOEWE funding line 3 of the state of Hessen and subsequently in the tender for LEIT-ICT / Big Data technologies of the EU is aimed at.

More about the project you will find on project description site. The work on the infrastructure as well as the developments are all made on our novel Scitics solution.

Leading Article to „Visual Analytics for Early Technology Trend Detection”

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Prof. Nazemi wrote an interesting leading article for the Research Center of Applied Informatics about his research toward visual analytics technologies for early technology trend detection. In this article he stated the relevance of noticing early indicators for the detection of new and, above all, socially and economically important technologies that can provide scientific publications. For this purpose, he and his team developed a trend analytics solution that covers a data processing pipeline beginning with the collection and transformation of unstructured text to a final visual interactive interface that enables analysts to elaborate trends, leaders and further relevant business aspects. Please note the link to the full article: https://fzai.h-da.de/2019/02/prof-dr-kawa-nazemi-visual-analytics-zur-technologiefrueherkennung/.

Events

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

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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:

    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:

      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

      Midhad Blazevic defended his Master Thesis on Visual Search and Exploration for Scientific Publications through Similarity

      /in , , , /by

      In his thesis, Midhad Blazevic alyzes exploratory search systems which use sophisticated features, visualizations and similarity-based algorithms to enhance exploratory searches. Examining how similarity algorithms are currently used in combination with elements from information retrieval, natural language processing and visualizations, but also examine what exploratory search is, what the requirements are and what makes it so special in modern times. Furthermore, the user himself or herself will be analyzed as user behavior during exploratory searches is a key factor that has to be taken into consideration when looking to optimize the exploratory search process overall. Based on these aspects, means of improvement will be developed and showcased, which will be used to determine if there is an improvement in comparison to other well-known systems. The outcome of this thesis will present a prototype of an exploratory search system along with a practical use case.

      Major Cities of Europe Web Seminar toward Digital Ethics, Humanism and Research – Laying the Foundation for Rethinking Cities

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      We are glad to announce that we get the chance to present our intended action of a collaborative European research action in Europe at the upcoming web seminar “Digital Ethics, Humanism and Research, laying the foundation for Rethinking Cities” of the Major Cities of Europe. The title of our project proposal and contribution to the web seminar will be “Research action call for proposals: Visual Trend Analytics for the Society” and is planned in frames of a European research-action.

      Under our coordination of our group and in collaboration with other associated organisations MCE is cooperating as responsible for dissemination to the submission of a proposal for a european research-action. The frame should be the European Network for Cooperation in Science and Technology. It provides networking opportunities for researchers and innovators to strengthen Europe’s capacity to address scientific, technological, and societal challenges. Our proposal will be focused on Analytical Reasoning by applying machine learning approaches, artificial intelligence, natural language processing and visualizations to allow to get deep insights into the different domains of various stakeholders and enable to solve complex tasks. The main outcome of the action for municipalities will be the identification of current challenges that require analytical reasoning and providing technological solutions for these by the research-action technological partners. The current institutions that are interested in this action are listed on: https://vis.h-da.de/network.html.

      Online @ 24rd International Conference Information Visualization (iV 2020)

      /in /by

      We are co-organizing the International Symposium Visual Analytics and Data Science at the next 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.

      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.

      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

       

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

      The scope of the VA track 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 Analytics and Data Science
      • Computational steering for long-running Data Mining applications
      • Reviews and surveys of related literature


      Related news for further information:

      Two Papers Accepted at 6th Collaborative European Research Conference (CERC 2020)

      /in , , , , /by

      At the this year’s Collaborative European Research Conference (CERC 2020) two of our students papers titled “Visual Dashboards in Trend Analytics to Observe Competitors and Leading Domain Experts” and “A Future Prospect for European Collaboration on Advanced Analytics in Economy and Society” were accepted for presentation. Due to Corona epidemic the conference is hold virtually. The multidisciplinary CERC is an annual event that takes place since 2011 when it was initiated by University partners across Europe. It brings together researchers from a wide range of disciplines in order to foster knowledge transfer, inter-disciplinary exchange and collaboration.

      Paper #1: Visual Dashboards in Trend Analytics to Observe Competitors and Leading Domain Experts

      Abstract:
      The rapid changes due to digitalization challenges a variety of market players and forces them to find strategies to be aware of changes in these markets, particularly those that impacts their business. The main challenge is how a practical solution could look like and how technology can support market players in these trend ob-servation tasks. The paper outlines therefore a technological solution to observe specific authors e.g. researchers who influence a certain market or engineers of competitor. In many branches both are well-known groups to market players and there is almost the need of a technology that support the topical observation. The main contributions of this paper are next to the concept of how a visual dash-board could enable a market observation and how data has to be processed for it, the prototypical implementation which enables an evaluation later on. Further-more, the definition of a principal technological analysis for innovation and tech-nology management is created and is also an important contribution to the scien-tific community that specifically considers the technology perspective and it cor-responding requirements.

      Link to paper/fulltext: http://ceur-ws.org/Vol-2815/CERC2020_paper14.pdf

      More information about the technology: Scitics for Visual Trend Analytics

      Paper #2: A Future Prospect for European Collaboration on Advanced Analytics in Economy and Society

      Abstract:
      Analytical Reasoning by applying machine learning approaches, artificial intelli-gence, NLP and visualizations allow to get deep insights into the different do-mains of various stakeholders and enable to solve complex tasks. Thereby the tasks are very heterogenous and subject of investigation in the different areas of application. These tasks or challenges should be defined by the stakeholders themselves and lead through a deep investigation to advanced analytical ap-proaches. We therefore set up a strategic alliance of research, enterprises and so-cietal organization with the goal of a strong collaboration to identify in a first step these challenges and workout technological solutions for each application scenar-io. We give in this paper a first draft of current challenges and technological ad-vancements. The main contribution of this paper is next to an accurate description of the current challenges in the analytics domain, also the description of an agen-da how these challenges can be solved. Furthermore, a process is explained, how the strategic alliance should act and organize their work to realize beneficial and useful analytical solutions.

      Link to paper/fulltext: http://ceur-ws.org/Vol-2815/CERC2020_paper27.pdf

      More information about the project and the expected collaboration project: EuroStraNet-project, VisCOST-project, partner network for COST

       

      The whole proceedings of the CERC 2020 are available under: http://ceur-ws.org/Vol-2815/.

      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

      24rd International Conference Information Visualization (iV 2020)

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         The event has been modified and is now organised virtual. Please note the new annouced event under Online @ iV2020!

      We are co-organizing the International Symposium Visual Analytics and Data Science at the next 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 the iV2020 Call for Papers (CfP).

      The Visual Analytics and Data Science track is organized via the 12th International Symposium Visual Analytics and Data Science.
      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.

      The scope of the VA track 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 Analytics and Data Science
      • Computational steering for long-running Data Mining applications
      • Reviews and surveys of related literature


      Related news for further information:

      Thesis Presentation: Named-Entity Recognition on Publications and Raw-Text for Meticulous Insight at Visual Trend Analytics

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      Where: TU Darmstadt / GRIS, Fraunhoferstr. 5 (Darmstadt), Room tba

      !!!!! Due to the Corona crisis and the accompanying restrictions at the TU Darmstadt, the exam will be non-public! !!!!!

      Who: Ubaid Rana (Author), Prof. Dr. Arjan Kuijper (Supervisor), Dipl.-Inf. Dirk Burkhardt (Advisor/Co-Supervisor)
      What: Master Thesis – “Named-Entity Recognition on Publications and Raw-Text for Meticulous Insight at Visual Trend Analytics”

      Abstract:

      In the modern data-driven era, a massive amount of research documents are available from publicly accessible digital libraries in the form of academic papers, journals and publications. This plethora of data does not lead to new insights or knowledge. Therefore, suitable analysis techniques and graphical tools are needed to derive knowledge in order to get insight of this big data. To address this issue, researchers have developed visual analytical systems along with machine learning methods, e.g text mining with interactive data visualization, which leads to gain new insights of current and upcoming technology trends. These trends are significant for researchers, business analysts, and decision-makers for innovation, technology management and to make strategic decisions.
      Nearly every existing search portal uses the traditional meta-information e.g only about the author and title to find the documents that match a search request and overlook the opportunity of extracting content-related information. It limits the possibility of discovering most relevant publications, moreover it lacks the knowledge required for trend analysis. To collect this very concrete information, named entity recognition must be used to be able to better identify the results and trends. The state-of-the-art systems use static approach for named entity recognition which means that upcoming technologies remain undetected. Modern techniques like distant supervision methods leverage big existing community-maintained data sources, such as Wikipedia, to extract entities dynamically. Nonetheless, these methods are still unstable and have never been tried on complex scenarios such as trend analysis before.
      The aim of this thesis is to enable entity recognition on both static tables and dynamic community updated data sources like Wikipedia & DBpedia for trend analysis. To accomplish this goal, a model is suggested which enabled entity extraction on DBpedia and translated the extracted entities into interactive visualizations. The analysts can use these visualizations to gain trend insights, evaluate research trends or to analyze prevailing market moods and industry trends.

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