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Book published– Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery

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Professor Kawa Nazemi edited together with colleagues from the London South Bank University, Instituto Superior de Engenharia de Lisboa, and the Central Washington University enhanced contributions of selected papers of the International Conference on Information Visualisation particularly on the intersection of artificial intelligence and visualization. The book will appear in the series Studies in Computational Intelligence by Springer Nature.

The book “Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery” is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytics. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is a fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering “n-D glasses,” where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain.

This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics-related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level.  The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations.

The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.

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”.

Advisory Board of the EUt+ Academic Press

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

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

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

Please find more information here.

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.

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.

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

Book Chapter published in Student Handbook “Praxishandbuch Forschungsdatenmanagement”

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

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

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

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

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/.

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