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Participation at IV 2022

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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

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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”.

Our team wishes you happy christmas holidays and a happy new year!

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After the second challenging year in the pandemic, the Human-Computer Interaction and Visual Analytics team at the h_da wishes you peace, joy, and prosperity throughout the coming year 2022.

Thank you for your continuous support and partnership. We look forward to working with you in the upcoming year.

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

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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.

Article on Visual Analytics for Technology and Innovation Management Published in Journal Multimedia Tools and Applications

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We are glad to announce that our article Visual analytics for technology and innovation management: An interaction approach for strategic decision making gets published in the current special issue of the Journal of Multimedia Tools and Applications.

Article: Visual analytics for technology and innovation management: An interaction approach for strategic decision making

Abstract:
The awareness of emerging trends is essential for strategic decision making because technological trends can affect a firm’s competitiveness and market position. The rise of artificial intelligence methods allows gathering new insights and may support these decision-making processes. However, it is essential to keep the human in the loop of these complex analytical tasks, which, often lack an appropriate interaction design. Including special interactive designs for technology and innovation management is therefore essential for successfully analyzing emerging trends and using this information for strategic decision making. A combination of information visualization, trend mining and interaction design can support human users to explore, detect, and identify such trends. This paper enhances and extends a previously published first approach for integrating, enriching, mining, analyzing, identifying, and visualizing emerging trends for technology and innovation management. We introduce a novel interaction design by investigating the main ideas from technology and innovation management and enable a more appropriate interaction approach for technology foresight and innovation detection.

Link to Paper: DOI: 10.1007/s11042-021-10972-3

Kickoff of the European Project “Partnerships with Eastern Europe”

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With the kickoff of the European collaboration project “Partnerships with Eastern Europe”, the Darmstadt University of Applied Sciences, and particularly our team, has decided to focus more on European cooperation. Our exchange project funded by the German Academic Exchange Service (DAAD) includes partners from Russia, Romania and Poland and aims at strengthening the collaboration with Eastern Europe.

Subject of our collaboration activities are machine learning and information visualization with a strong collaboration with the Technical University of Ulyanovsk in Russia. The project is set up for three years and involves various faculties of the Darmstadt University.

Further information

– More information to the project Partnerships with Eastern Europe

Our team wishes you happy christmas holidays and a happy new year!

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After an extremely challanging year, the Human-Computer Interaction and Visual Analytics team at h_da wishes you peace, joy and prosperity throughout the coming year.

Thank you for your continued support and partnership. We look forward to working with you in the years to come.

Guest Editing of Special Issue in Big Data Research Journal

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Prof. Dr. Kawa Nazemi acts as guest editor together with Vincenzo Deufemia and Giuseppe Polese the special issue on “Visualization in Big Data and Data Science” of the Big Data Research Journal.

 

Call for Papers:

Visualization in Big Data and Data Science

 

Introduction

As witnessed by Covid19 outbreak, big data and data science are becoming vital disciplines in several application domains, mainly due to the great availability of big data collections from which it is possible to mine precious patterns of knowledge. The Internet of Things (IoT) industrial revolution has furtherly contributed to boost this trend, yielding an increased interest for data analytics techniques capable of working on streams of data and time series. This has led to the development of powerful predictive models, including deep neural networks, also thanks to the availability of powerful hardware and distributed computing paradigms. Nevertheless, one of the aspects that is hindering the contamination of Big Data and Data Science in many sectors is to be ascribed to the difficulty in explaining the rationale underlying complex data analytics processes to stakeholders. While it is well-known that the data pre-processing and analytics phases account for about 70% and 20% of the whole data analytics process, respectively, there is a remaining 10% of the effort that should be devoted to the visualization and explanation of the results, also known as data journalism. Although this is a small percentage, and for this reason overlooked by many data scientists, it is one of the most critical ones in order to draw the attention of stakeholders and motivate them to trust and invest on the adoption of Big Data and Data Science technologies. This is true also in artificial intelligence where explainable AI is also becoming crucial. One way to tackle this problem is to rely on efficient visualization metaphors and intelligent visual interaction paradigms.

In this respect, we expect interdisciplinary contributions from several research communities, such as, data mining, big data, machine learning, and human-computer interaction, to provide new scalable ways for visualizing the results of complex data analytics processes, including efficient interaction techniques to explore them. In particular, they should stimulate the active involvement of stakeholders in the data analytics process by enhancing their understanding capabilities.

Paper Submission Format and Guidelines

All submitted papers must be clearly written in English and must contain only original work, which has not been published by, or is currently under review for, any other journal, conference, symposium, or workshop. Submissions are expected to not exceed 30 pages (including figures, tables, and references) in the journal’s single-column format using 11-point font. Detailed submission guidelines are available under “Guide for Authors” at:

http://www.journals.elsevier.com/big-data-research/

All manuscripts and any supplementary material should be submitted through the Elsevier Editorial System (EES). The authors must select “VSI: Big Data Science Vis” as Article Type when they reach the Article Type step in the submission process. The EES website is located at:

http://ees.elsevier.com/bdr

All papers will be peer-reviewed by at least three independent reviewers. Requests for additional information should be addressed to the guest editors.

Topics for the Special Issue

Topics of interest include, but are not limited to:

· User interfaces for data science

· Visualization of time-dependent data, geo-localized data, and maps

· Data to visualization mappings

· Interactive knowledge discovery

· Visual operators on data and knowledge

· Big data visualization in various domains (health, education, politics, …)

· Visual exploration of datasets

· Visualization of data correlations

· Visual data mining and visual knowledge discovery

· Visualization of learning models

· Visualization techniques for data profiles

· Visualization for IoT data analytics

· Visual analytics for explainable AI

· Collaborative visual analytics and data science

· Adaptive visual analytics

· Visual trend analytics

· User evaluations and case studies, reports on real cases and experiments

Important Dates

Submission Deadline: February 15, 2021

Author Notification: May 15, 2021

Revised Manuscript Due: July 1, 2021

Notification of Acceptance: October 1, 2021

Final Manuscript Due: October 15, 2021

Tentative Publication Date: December, 2021

Guest Editors

Vincenzo Deufemia, University of Salerno

Kawa Nazemi, Darmstadt University of Applied Sciences

Giuseppe Polese, University of Salerno

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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

Kickoff of the e-Learning Project Digitallabor

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With the kickoff of the e-Learning project Digitallabor, we are supporting the education and training strategy of digital teaching in vocational training. Especially the COVID-19 crisis increased the need for solutions and approaches to enable digital trainings. However, there are many challenges, starting with the required infrastructure, moving further to pedagogic strategies and ending in individual electronic learning features.

In the project, any step has to be cover. Together with the project partners in the field of digital education, it is intended to use the opportunities offered by digitization for vocational education and training and to open up access possibilities for multipliers and teachers.

Further information

– More information to the project Digitallabor

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