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.
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 2020. The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation, and development.
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
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.
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.
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.
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: https://doi.org/10.1007/s11042-021-10972-3
The impact Magazine for Applied Research and Art of the Darmstadt University of Applied Sciences published an article, based on an interview with Prof. Dr. Kawa Nazemi, to the research field Visual Data Analytics.
The article is about how tangible patterns can be discerned from huge data sets with the help of visual analysis and representation, and how applicable predictions can be made using a combination of artificial and human intelligence: That is the specialty of Kawa Nazemi, professor for computer science at the h_da’s Department of Media. The head of the Human-Computer Interaction and Visual Analytics research group is a sought-after expert in this still-young field and is also successfully making his mark on the international stage.
Further information
This year’s Collaborative European Research Conference (CERC) will take place with the support of scientists and members of our team. The 7th edition of the conference aims at young academics and is primarily organized and held by colleagues from Munster Technological University (Cork, Ireland). The conference will take place from 9-10 September 2021 as blended event in presence and online/virtual.
The CERC was held for the first time in 2010 by the Darmstadt University of Applied Sciences (h_da) and the Munster Technological University (Cork, Ireland) – previously named Cork Institute of Technology (CIT) – and was originally organized by lecturers from the IT department of these two institutions. The event, which takes place alternately every year at one of the partner universities, is deliberately interdisciplinary and the presented researches cover a wide range of topics – from bioinformatics to social history. This promotes the exchange of ideas between the specialist areas and thus the opportunity for new collaborations.
CERC 2021 has the goal of a broad research program. Relevant topics for the conference include, but are not limited to, the following areas:
Accepted contributions will be published in digital proceedings with an ISSN number – it is intended that publications shall be submitted to CEUR-WS for online publication, indexed among other at DBLP, Scopus, Semantic Scholar and Google Scholar. Extended versions of the best papers may be published into an upcoming special issues of “Sensors” (ISSN 1424-8220, Impact Factor: 3.275) and “Methods and Protocols” (ISSN 2409-9279; CODEN: MPERC6) Journals.
If you have interesting research results, you are invited to submit your paper by June 3oth. Interested parties can also attend the conference without a submission. Please note the information on the website: http://www.cerc-conf.eu.
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.
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
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.
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.
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:
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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