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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 inter-disciplinary 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

 

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

Kickoff of the Stategic Networking Project VisCOST

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The now started project VisCOST aims to create a European research network to promote innovation and technology management through the interdisciplinary use of methods of visual analysis, artificial intelligence, simulation, prediction and planning of new technologies and innovations for corporate purposes (smart manufacturing, early technology detection etc.), the optimization of government strategies (e-governance) and the involvement of European citizens in government decisions (e-participation) but also in research. The core targets on answering the research question “How can innovations be created and strengthened, and future technologies as well as possible scenarios be predicted by the approaches that are currently at the forefront of technology research in order to make strategic decisions in a more targeted manner?”. A very interdisciplinary research is necessary to answer this question. Knowledge from management, such as innovation, technology and information management, but also strategic planning and predictions in companies (corporate foresight) must be brought in from economics.

Further information

– More information to the project VisCOST

– More information to the build research network

– Website about COST-actions

New Collaboration Network Started for European Collaborative Research Actions

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We have successfully initiated a new European Research Network to strengthen and supporting actions in respect of European collaborative research. The main goal of this network is to create a sustainable European (but not limited on Europe) strategic alliance to foster European research and innovation in the area of Visual Analytics, Artificial Intelligence, Simulation, Prediction, Smart Manufacturing and Technology and Innovation Management including innovations for business, manufacturing and eGovernance. On the fundament of the research network, research actions such as preparing a funding proposal (e.g. COST actions) should be faced and simplified in particular toward finding partners and expertise.

The research network is a major goal and outcome of the EuroStraNet project. The project was setup to define a strategy, build an initial fundament and finding partners to start with this new strong collaboration ship.

If you as researcher and/or representative of a research institution or company are interested in joining the network, you are more than welcome. You are just asked to mail us a logo of your institution and a brief description of your research area and interests.

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.

Events

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.

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