Human-Computer Interaction & Visual Analytics Reasearch Department (vis) at Darmstadt University of Applied Sciences (h_da)

IV2025 and AI&VIS25 Conferences
2025-08-05 - 2025-08-08 | Darmstadt University of Applied Sciences, Schöfferstraße, Darmstadt, Hesse, 64295, Germany
IV2025 – 29th International Conference Information Visualisation and AI&VIS25 – 6th International Conference on Artificial Intelligence and Visualization
The IV2025 and AI&VIS25 conferences provide a vibrant international forum for researchers, practitioners, and thought leaders to exchange the latest advances, innovations, and practical
challenges in the domains of information visualization, visual analytics, and AI-powered visual computing. For nearly three decades, the IV conference has been a cornerstone event in the visualization community, promoting interdisciplinary dialogue and showcasing cutting-edge research. In its 6th edition, AI&VIS25 focuses on the intersection of AI, visualization, and immersive analytics across a wide range of application domains. All accepted papers will be peer-reviewed and published by IEEE in the IEEE Xplore Digital Library and will be submitted for indexing to leading indexing services, including Scopus, Web of Science, and DBLP. Selected contributions will be invited for publication in special issues of the Information Visualisation Journal or an edited volume.
Conference Dates: 5th to 8th August 2025
Location: Darmstadt University of Applied Sciences, Germany
https://www.graphicslink.co.uk/IV2025/index.htm

Theme and scope are planned as a series of symposia with details, and further information is available at IV2025: https://iv.csites.fct.unl.pt/de/symposia/iv/va/
Submission Portal: https://www.conftool.org/IV-cgiv-2025/
Publication: https://iv.csites.fct.unl.pt/de/call-for-papers/publication/
Important Dates – https://iv.csites.fct.unl.pt/de/call-for-papers/important-dates/

Conference Themes
We invite high-quality contributions on (but not limited to) the following themes:

IV2025 – Information Visualisation Themes

Theories and Models in Information Visualization
Human-Centred Design and Interaction
Knowledge Visualization and Visual Thinking
Visual Storytelling and Design for Insight
Cognitive and Perceptual Aspects of Visualization
Sustainable and Environmental Visualization

AI&VIS25 – AI & Visualisation Themes

Explainable and Trustworthy AI in Visualization
Visual Analytics for Data Science
AI-Powered Knowledge Discovery and Pattern Recognition
Multimodal and Cross-Modal Visualisation
Immersive Visualisation: AR, VR, and MR
Human-AI Collaboration for Decision Support

Interdisciplinary and visionary submissions are strongly encouraged.

Special Tracks and Workshops

Researchers Link Forum
A dedicated forum to promote research aligned with the UN Sustainable Development Goals through AI and Visualization. Participants can present early-stage ideas, receive feedback from mentors, and identify future collaborators. This format is ideal for sparking new international research alliances.
PhD Workshop
Doctoral candidates are invited to present their dissertation research, challenges, and preliminary findings. The workshop offers mentoring, peer feedback, and visibility in the research community. Presentation slots are limited; early submission is recommended.
Tutorials and Panels
The conference will host expert-led tutorials and thematic panel discussions on emerging trends and grand challenges in AI and Visualisation.
Submission Guidelines
We welcome:

Full Papers (6 pages, IEEE format)
Short Papers (4 pages, IEEE format)
Posters (up to 4-page extended abstract + poster, IEEE format)

All submissions must follow the IEEE conference format and be uploaded via the submission portal.
Important Dates

15 May 2025 – Submission Deadline (Papers, Posters, Tutorials)
15 June 2025 – Notifications & Camera-Ready Submissions Due
30 June 2025 – Poster Display Version, Doctoral Abstract, Researchers Link Proposal Due
20 July 2025 – Final Registration Closes
5-8 August 2025 – Researcher Link
5 August 2025 – Tutorials & Doctoral Workshop Day
6–8 August 2025 – Main Conference Days

Preconference course: Doctoral Research Workshop
Researcher Link Forum: Research Project Collaboration
Focus Group Publication: Post-conference publication
Conference Format
IV2025 and AI&VIS25 will be held in a part-hybrid format, with a focus on in-person participation in Darmstadt. Virtual attendance will be supported to ensure global accessibility. The event features:

Keynote Lectures by Renowned Experts
Peer-Reviewed Paper Presentations
Thematic Panels & Tutorials
PhD Workshop and Researchers Link Forum
Social and Networking Events

Participation & Discounts

EUt+ Members can participate free of charge and receive a 30% discount on publication
fees.
IEEE Members receive a 15% discount on both registration and publication fees.
Further details will be available on the conference website.

Honorary Chair
Prof. Dr. Arnd Steinmetz (President, Darmstadt University of Applied Sciences – European
University of Technolgy EUt+)
General Co-Chairs:

Ebad Banissi (Em Prof. Dr.), London South Bank University (LSBU), UK
Kawa Nazemi (Prof. Dr.), Darmstadt University of Applied Sciences, DE – European University of Technolgy (EUt+) – hessian.AI

Call for Papers: Electronics - Special Issue - "Unlocking Data’s Potential: Artificial Intelligence and Visual Analytics in the Modern Age"
2024-08-30 - 2025-01-15
In the rapidly evolving fields of artificial intelligence (AI) and visual analytics, there is growing recognition of their combined potential to reshape diverse sectors, emerging as a crucial pathway for progressing research and practical applications. The synergy between AI-driven techniques—such as natural language processing, image and video processing, and data analytics—and visual analytics methodologies augments our ability to decipher complex data structures. Such interdisciplinary approaches reveal subtle data patterns, enhancing decision-making processes and establishing more effective predictive mechanisms essential for addressing societal and economic challenges and progress.
This Special Issue endeavors to delve deep into the interplay between AI and visual analytics, seeking contributions highlighting novel methodologies, computational strategies, systematic reviews, and system architectures of real-world applications. Our goal is to foster an interdisciplinary exchange of ideas, extending to areas including analytical decision-making, corporate strategy evolution, AI-driven collaborative frameworks, healthcare analytics, sustainability metrics, and innovative techniques for behavior and trend detection.
In the current era, where data stand as the backbone of contemporary challenges and opportunities, this Special Issue serves as a platform for researchers and professionals to showcase pioneering work, laying the foundation for breakthroughs that cater to the multifaceted challenges of our society. By combining AI and visual analytics, we are able to unlock unprecedented insights from data, driving our global community toward a more resilient and prosperous future.
Topics of interest include, but are not limited to, the following:

Integrative visual analytics and artificial intelligence systems and approaches;
AI and visual analytics to support decision-making;
Techniques and methods in explainable AI;
Visual analytic solutions for handling big data challenges;
AI and visual analytics in strategic corporate planning;
AI and visual analytics in healthcare;
AI and visual analytics for social well-being and mental health;
Facilitation of collaborative work through AI interventions;
Insights into collaborative intelligence mechanisms;
AI and visual analytics for sustainability and environmental analysis and management;
AI and visual analytics for policy modeling and political decision support.

Prof. Dr. Kawa Nazemi
Prof. Dr. Nuno Datia
Prof. Dr. Rita Francese
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI’s English editing service prior to publication or during author revisions.

Keywords

artificial intelligence (AI)
visual analytics
natural language processing
explainable AI
big data analytics
data interpretation

International Conference Information Visualisation (IV2024)
2024-07-23 - 2024-07-26 | Private: Coimbra University, 3004-531, Coimbra, Portugal
IV2024 – 28th International Conference Information Visualisation
23-26 July 2024
Coimbra University ● Portugal
https://www.graphicslink.co.uk/IV2024/index.htm

Call for Papers, Poster, Videos, and Participation

Theme and scope are planned as a series of symposia with details, and further information is available at IV2024: https://iv.csites.fct.unl.pt/fi/symposia/
Submission Porta: https://www.conftool.org/IV-cgiv-2024/
Publication: https://iv.csites.fct.unl.pt/fi/call-for-papers/publication/

Visual Analytics is the science of analytical reasoning empowered by interactive visualizations. The research on Visual Analytics is closely related to that of Data Science. Both areas seek to enhance knowledge discovery using machine learning, data mining, and artificial intelligence methods. In contrast, Visual Analytics commonly allows direct manipulation of the underlying models through graphical representations. By leveraging human perception of the visual space, patterns that might not otherwise be discovered emerge. Visual Analytics utilizes concepts from various disciplines, including computer graphics, information visualization, machine learning, artificial intelligence, knowledge discovery, cognition, and visual perception.
The topics of interest include but are not limited to:

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, geo-visualization, and geographical visualization of spatial, temporal, and Spatio-temporal data
Visualization support for multi-criteria decision analysis related to multivariate and spatial data
Knowledge construction and management in Visual Analytics
Guidance in Visual Analytics
Intelligent approaches of Visual Analytics and Data Science
Adaptive Visual Analytics

Integrative visual analytics and artificial intelligence systems and approaches

AI and visual analytics to support decision-making

Techniques and methods in explainable AI

Visual analytic solutions for handling big data challenges

HCI issues of geographical and Spatio-temporal 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

Preconference course: Doctoral Research Workshop
Researcher Link Forum: Research Project Collaboration
Focus Group Publication: Post-conference publication

——————————————————————————-
Important Dates – https://iv.csites.fct.unl.pt/fi/call-for-papers/important-dates/
Submission Portal: https://www.conftool.org/IV-cgiv-2024/
========= ===================================
General Co-Chairs:
Ebad Banissi (Em Prof. Dr), LSBU, UK
Dr Evgheni Polisciuc, Coimbra University, Portugal

Symposium General Co-Chairs:
Kawa Nazemi (Prof.), Darmstadt University of Applied Sciences, Germany – Visual Analytics and Data Science
Boris Kovalerchuk (Prof.), University of Central Washington, USA – AI and Visual Knowledge Discovery
Urska Cvek (Prof.), Louisiana State University, USA – Visualization and Artificial Intelligence for Medicine, Healthcare
Anna Ursyn (Prof.), University of Northern Colorado, USA – Digital Art and Gallery

We are hiring! Two open position with PhD oppurtunity.
2023-10-02 08:00 - 2023-11-23 23:59 (Europe/Berlin) | Job, Max-Planck-Str. 2, Dieburg - Darmstadt, Hesse, 64807, Germany
The research group “Human-Computer Interaction and Visual Analytics” (vis) at the Faculty of Media of the Darmstadt University of Applied Sciences announces two open positions commencing from 01.01.2024 for a period of 3 years.
Position Highlights:

Pursue a PhD at the esteemed Hessian Doctoral Center for Applied Computer Science.
Contribute to the critical European project “FARMWISE – Future Agricultural Resource Management and Water Innovations for a Sustainable Europe”, (Horizon Europe – Research and Innovation Action).
The offered salary is competitive within the sector.
Engage with a team of computer, data, and information scientists committed to advancing the state of knowledge and generating impactful solutions.

Qualifications: Candidates must have a Master’s degree in Computer Science or a related discipline and strong analytical and problem-solving skills. Interest in the intersection of artificial intelligence and visual analytics is essential.
For an in-depth overview of the roles and associated responsibilities, please refer to the detailed job descriptions at the following links:

PhD-position 100% (full-stack development) – Position description (German)
PhD-position 75% (backend development) – (with an option to upgrade to 100%) – Position description (German)

If you’re seeking a role that blends rigorous computational research with pressing challenges in sustainability and AI, we invite you to consider these positions.
Join us in advancing the field of AI for environmental resource management and water innovations for Europe. Create new solutions for AI-based decision-making systems and approaches on different levels.
We encourage you to review the position specifics and apply at your earliest convenience.

Call for Papers: 1st International Workshop on Disinformation and Toxic Content Analysis (DiTox 2023)
2023-09-13
Call for Papers: 1st International Workshop on Disinformation and Toxic Content Analysis (DiTox 2023), September 13th, 2023
In conjunction with the 4th biennial conference on Language, Data and Knowledge (LDK 2023) to be held in Vienna, Austria.
The spread of misinformation and disinformation not only affects people’s perceptions and beliefs, but can also have a direct impact on democratic institutions, critical infrastructure, and lives and families. Most critically, it raises the more fundamental issue of what sources of information can be trusted at all, potentially calling into question our relationship of trust with traditional media. Because of these profoundly harmful effects, disinformation is seen as one of the most pressing problems of our time.
The weak definition of the research task of disinformation analysis and detection, as well as the enormous range in terms of the heterogeneity and multimodality of the data involved, make this an exceptionally challenging field of research. The complexity ranges from media tampering detection to text content analysis to large-scale information fusion to analyze disinformation trends. Maintaining a comprehensive overview is equally difficult.
Respectively, the overall goal of this workshop is therefore to provide insights on how approaches from different domains can be used to address disinformation at a technical level including AI/ML-based methods, visual analytics, and visualization approaches as well as interdisciplinary approaches inspired by the social sciences (i.e., computational social science). To this end, we invite task-specific contributions, as well as large-scale integration approaches, demo and project presentations, to provide a comprehensive overview of the current state of the art in countering disinformation.

Topics:
Full Paper Submissions:

Machine and Deep learning methods for disinformation (e.g., analysis, detection)
Visual analytics and visualization approaches for disinformation
Audio tampering detection
Social network analysis (e.g., key actors, distribution patterns) including visualization approaches
Graph algorithms for disinformation identification
Natural language processing methods (e.g., content evaluation, toxicity, radicalization)
AI-supported fact checking and detection of disinformation campaigns
Identification of fabricated and manipulated content (e.g., deep fakes, audio, generated text)
Community detection and characterization in social networks (e.g., conspiracy theories, echo chambers)
Bots characterization and detection
Multimodal fake content detection
Recommendation systems and disinformation
AI uses, practices and tools in fact-checking journalism
Qualitative and quantitative studies on disinformation
Ethics and law in disinformation

Demo and Project Presentation (Short Paper Track, Poster Presentation):

Demo presentations (e.g., fact checking tools, disinformation detection tools)
Project platform presentations
Project presentations

Important Dates:

Paper submission: May 21st, 2023
Notification: June 20th, 2023
Camera-ready submission deadline: July 9th, 2023
DiTox workshop: September 13th, 2023

Submission:
Submissions can be in the form of Long papers (9–12 pages) and Short papers (4-6 pages). All submission lengths are given including references. Accepted submissions will be published by ACL in an open-access conference proceedings volume, free of charge for authors. The reviewing process is single-blind, submissions should not be anonymised. The workshop will be hybrid (face-to-face and remote). At least one author of each accepted paper must register to present the paper at the workshop (either remotely or on-site). There will be no registration fee administered for participating in LDK 2023. Papers should be submitted via OpenReview at the following address: https://openreview.net/group?id=LDK/2023/Conference

Organizing Committee

Alexander Schindler, Austrian Insititue of Technology GmbH
Mina Schütz, Austrian Institute of Technology GmbH, Darmstadt University of Applied Sciences
Melanie Siegel, Darmstadt University of Applied Sciences
Kawa Nazemi, Darmstadt University of Applied Sciences
Matthias Zeppelzauer, St. Poelten University of Applied Sciences
Djordje Slijepčević, St. Poelten University of Applied Sciences

International Conference Information Visualisation (IV2023)
2023-07-25 08:00 - 2023-07-28 17:00 (Europe/Berlin) | Tampere University, Kalevantie 4, Tampere, 33100, Finland
IV2023 – 27th International Conference Information Visualisation
25 – 28 July 2023
Tampere University ● Tampere ● Finland ●
https://www.graphicslink.co.uk/IV2023/index.htm

Call for Papers, Poster, Videos, and Participation

Theme and scope are planned as a series of symposia with details, and further information is available at IV2023: https://iv.csites.fct.unl.pt/fi/symposia/
Submission Porta: https://www.conftool.org/IV-cgiv-2023/
Publication: https://iv.csites.fct.unl.pt/fi/call-for-papers/publication/

IV2023 – Information visualization:

Information Visualisation Theory & Practice
Applications of Information Visualization
Information Visualization Evaluation
Human-Computer Interaction for Information Visualization
Graph Theory & Network Visualization

IV2023 – Knowledge Visualization

Knowledge Visualization and Visual Thinking
Learning Analytics
Music Visualization
Digital Humanities Knowledge Visualisation

IV2023 – AI/ML, Visual Analytics, and Visual Knowledge Discovery

13 International Symposium Visual Analytics and Data Science
AI and Visual Knowledge Discovery
Visualization in Data Science and Machine Learning
Advances in Interactive and Visual Data Clustering

IV2023 – Visual Methods in Big Data, social, and business analytics

Big data Visualization and Visual Analytics
Visualisation in Business Intelligence and Open Data
Social Issues Analysis and Visualisation

vis2023– Visualization

2nd Symposium on AI-Empowered Visual Computing
Augmented Reality Visualization and Art
D-ART – Symposium of Digital Art and Gallery
Scientific Visualization
Visualization, Art, & Design
CAivDE – Computer Animation, Information Visualisation, and Digital Effects
Digital Entertainment
Computer Games and their applications

MediVis2023

Visualization and Artificial Intelligence for Medicine, Healthcare, and Social Good

BuiltViz2023

Visualisation in Built and Rural Environment
ResearcherLink in Sustaining Built Heritage
Visualisation for the Heritage of Asia-Pacific Architecture and Urbanism

GMAI2023

Geometric Modelling and Imaging

Preconference course: Doctoral Research Workshop
Researcher Link Forum: Research Project Collaboration
Focus Group Publication: Post-conference publication

——————————————————————————-
Important Dates – https://iv.csites.fct.unl.pt/fi/call-for-papers/important-dates/
Submission Portal: https://www.conftool.org/IV-cgiv-2023/
========= ===================================
General Co-Chairs:
Harri Siirtola (Dr.), Tampere University, Finland
Ebad Banissi (Em Prof.), LSBU, UK

Symposium General Co-Chairs:
Kawa Nazemi (Prof.), Darmstadt University of Applied Sciences, Germany – Visual Analytics and Data Science
Boris Kovalerchuk (Prof.), University of Central Washington, USA – AI and Visual Knowledge Discovery
Urska Cvek (Prof.), Louisiana State University , USA – Visualization and Artificial Intelligence for Medicine, Healthcare
Anna Ursyn (Prof.), University of Northern Colorado, USA – Digital Art and Gallery

Call for Papers - MDPI Electronics - Special Issue "Visual Analytics, Simulation, Decision Making Technologies"
2023-03-15
Please consider the revised submission date.
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 behaviour 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 behaviour detection

Prof. Dr. Kawa Nazemi
Prof. Dr. Egils Ginters
Dr. Michael Bažant
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI’s English editing service prior to publication or during author revisions.

26th International Conference Information Visualization (iV 2022)
2022-07-19 - 2022-07-22 | TU Wien, Karlsplatz 13, Vienna, 1040, Austria
We are co-organizing the International Symposium Visual Analytics and Data Science at the next International Information Visualisation Conference (iV 2022), 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 the science of analytical reasoning empowered by interactive visualizations. 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. In contrast, Visual Analytics allows direct manipulation of the underlying models through graphical representations commonly. By leveraging human perception of the visual space, patterns that might not otherwise be discovered emerge. Visual Analytics utilizes concepts from various 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.

The topics of interest include but are not limited to:

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, geo-visualization and geographical visualization of spatial, temporal, and Spatio-temporal data
Visualization support for multi-criteria decision analysis related to multivariate and spatial data
Knowledge construction and management in Visual Analytics
Guidance in Visual Analytics
Intelligent approaches of Visual Analytics and Data Science
Adaptive Visual Analytics
HCI issues of geographical and Spatio-temporal 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: Process Mining for Workflow-Driven Assistance in Visual Trend Analytics
2022-04-26 14:00 - 15:30 (Europe/Berlin) | TU Darmstadt / GRIS, Fraunhoferstraße 5, Darmstadt, Hessian, 64283, Germany
Where: TU Darmstadt / GRIS, Zoom: https://tu-darmstadt.zoom.us/j/86845586436?pwd=[REDACTED]
Who: Shahrukh Badar (Author), Prof. Dr. Arjan Kuijper (Supervisor), Dipl.-Inf. Dirk Burkhardt (Advisor/Co-Supervisor)
What: Master Thesis – “Process Mining for Workflow-Driven Assistance in Visual Trend Analytics”
Abstract:
In today’s data-driven world, a large amount of data is being generated daily. This data is generated by different sources, such as social networking platforms, industrial machinery, daily transactions, etc. The companies or businesses are not only generating data but also utilizing them to improve their processes, business decisions, etc. There are several applications and tools that help users to analyze this big data in-depth, by providing numerous ways to explore it, including different types of visualization, pivoting, filtering, grouping data, etc. The challenge with such applications is that it creates long and heavy learning curves for users, who need to work with such applications. Many systems are often designed for a specific purpose, and therewith to know how a single system works is not enough. To enable a better work entrance with such an analytical system, a kind of adaptive assistance would be helpful. So, the system would hint the users regarding his previous work and interaction, what next action might be useful. The thesis aims to face this challenge with process-driven assistance that is applied to the visual trend analytics domain. The goal is, based on previous users interactions and solved tasks, to assist further users in their work. Therefore, a universal visual assistance model is defined and acts also as the main contribution, based on defined interaction event taxonomy. This concept is applied on the Visual Trend Analytics domain on the SciTic reference system, This “SciTic – Visual Trend Analytics” is connected with different data sources and provides analysis of scientific documents. The interaction model provides assistance in terms of recommendations, where the user has an option either to apply a recommendation or ignore it. The solution provided in this thesis is model-based and utilizes the potential of Process Mining and Discovery techniques. It is started by creating an event taxonomy by identifying all possible ways of user interactions on the “SciTic – Visual Trend Analytics” web application. Next, enable the “SciTic – Visual Trend Analytics” web application to start logging events chronologically based on predefined taxonomy. Later, these events log is converted into Process Mining log format. Next, it applies the Process Discovery algorithm “Heuristics Miner” on these log data to generate a process model, which shows the overall flow of user interaction along with the frequencies. Later, this process model is used to provide users with recommendations.

Thesis Presentation: Visual Analytics on Enterprise Reports for Investment and Strategical Analysis
2022-03-28 14:00 - 15:30 (Europe/Berlin) | TU Darmstadt / GRIS, Fraunhoferstraße 5, Darmstadt, Hessian, 64283, Germany
Where: TU Darmstadt / GRIS, Zoom: https://tu-darmstadt.zoom.us/j/83620126004?pwd=[REDACTED]
Who: Sibgha Nazir (Author), Prof. Dr. Arjan Kuijper (Supervisor), Dipl.-Inf. Dirk Burkhardt (Advisor/Co-Supervisor)
What: Master Thesis – “Visual Analytics on Enterprise Reports for Investment and Strategical Analysis”
Abstract:
Given the availability of enormous data in today’s time, suitable analysis techniques and graphical tools are required to derive knowledge in order to make this data useful. Scientists and developers have come up with visual analytical systems that combine machine learning technologies, such as text mining with interactive data visualization, to provide fresh insights into the present and future trends. Data visualization has progressed to become a cutting-edge method for displaying and interacting with graphics on a single screen. Using visualizations, decision-makers may unearth insights in minutes, and teams can spot trends and significant outliers in minutes [1]. A vast variety of automatic data analysis methods have been developed during the previous few decades. For investors, researchers, analysts, and decision-makers, these developments are significant in terms of innovation, technology management, and strategic decision-making.
The financial business is only one of many that will be influenced by the habits of the next generation, and it must be on the lookout for new ideas. Using cutting-edge financial analytics tools will, of course, have a significant commercial impact. Visual analytics, when added to the capabilities, can deliver relevant and helpful insights. By collecting financial internal information from different organizations, putting them in one place, and incorporating visual analytics tools, financial analytics software will address crucial business challenges with unprecedented speed, precision, and ease.
The goal of the thesis is to make use of visual analytics for the fundamental analysis of a business to support investors and business decision-makers. The idea is to collect the financial reports, extract the data and feed them to this visual analytics system. Financial reports are PDF documents published by public companies annually and quarterly which are readily available on companies’ websites containing the values of all financial indicators which fully and vividly paint the picture of a companies’ business. The financial indicators in those reports make the basis of fundamental analysis. The thesis focuses on those manually collected reports from the companies’ websites and conceptualizes and implements a pipeline that gathers text and facts from the reports, processes them, and feeds them to a visual analytics dashboard. Furthermore, the thesis uses state-of-the-art visualization tools and techniques to implement a visual analytics dashboard as the proof of concept and extends the visualization interface with interaction capability by giving them options to choose the parameter of their choice allowing the analyst to filter and view the available data. The dashboard fully integrates with the data transformation pipeline to consume the data that has been collected, structured, and processed and aims to display the financial indicators as well as allow the user to display them graphically. It also implements a user interface for manual data correction ensuring continuous data cleansing.
The presented application makes use of state-of-the-art financial analytics and information visualization techniques to enable visual trend analysis. The application is a great tool for investors and business analysts for gaining insights into a business and analyzing historical trends of its earnings and expenses and several other use-cases where financial reports of the business are a primary source of valuable information.

7th Collaborative European Research Conference (CERC 2021)
2021-09-09 09:00 - 2021-09-10 18:00 (Europe/Berlin) | Munster Technological University, MTU - Cork Campus, Bishopstown, Cork, T12 P928, Ireland
We support the organization of the Collaborative European Research Conference (CERC 2021) in Cork, Ireland. The multidisciplinary Collaborative European Research Conference 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.
In previous years, contributions came from computer science, biology, bioinformatics, business information systems, marketing, IT-security, civil engineering, education, psychology, multimedia, art and others. Contributing authors came among other from Ireland, Germany, United Kingdom, Norway, France and USA.
Please note the Call for Papers (CfP).

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Online @ 25th International Conference Information Visualization (iV 2021)
2021-07-05 - 2021-07-09 | University of Technology Sydney, 15 Broadway, Ultimo NSW, Sydney, 2007, Australia
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

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Research Day 2021 at h_da
2021-05-18 14:00 - 18:00 (Europe/Berlin) | h_da, Darmstadt, Germany, Schöfferstraße 3, Darmstadt, 64295, Germany
The “Research Day” (German original title: “Tag der Forschung”) was first held back in 2002, establishing a tradition, where every year in November, news about current research activities were shown and the time for networking and discussion is given. The annual Research Day has a special significance for the Darmstadt University of Applied Sciences. It is aimed at university members, company representatives, institutions in the region, and the interested public. Exciting lectures and discussions on current research activities at the university and the awarding of the science prize are part of the program.

International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020)
2020-11-23 09:00 - 2020-11-25 18:00 (Europe/Berlin) | University of Applied Sciences Upper Austria, Hagenberg Campus, Softwarepark 11, Hagenberg im Mühlkreis, 4232, Austria
Over the past few years, the growing and intensive development of information technology in the manufacturing industry has led to a significant change in the methods and tools supporting the factories of the future. The hot topics around Industry 4.0 and smart manufacturing aim at the digital and organizational transformation of traditional factories and industrial systems as well as several other sectors. The International Conference on Industry 4.0 and Smart Manufacturing (ISM) provides the perfect setting and a unique opportunity for knowledge exchange, the review and discussion of theoretical advances, research results, and industrial experiences, among scientists, researchers, decision makers, practitioners and students.
Authors are invited to submit a regular or short paper on the following topics. Nevertheless, papers dealing with other Industry 4.0 and Smart Manufacturing topics are also welcome.
The conference is co-located with other three events. Visit the ISM website for more information.

a B2B brokerage event, a unique opportunity to find potential partners and right contacts to build new cross-border international business and research partnerships;
the Win-Log 2020, the International Workshop on Innovation for Logistics, the scenario for scientists and practitioners to discuss current trends and challenges in the Logistics 4.0;
the WAMS 2020, the International Workshop on Applied Modeling & Simulation, which concentrates on applications of M&S in multiple sectors including industry, logistics, defence, business and services.

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IEEE Information Technology and Management Science Conference
2020-10-16 09:00 - 17:00 (Europe/Riga) | TU Riga, Kaļķu iela 1, Rīga, LV-1658, Latvia
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.

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6th Collaborative European Research Conference (CERC 2020)
2020-09-10 09:00 - 2020-09-11 18:00 (Europe/Berlin) | Ulster University, York Street, Belfast, County Antrim, BT15 1ED, Belfast, Northern Ireland, BT15 1ED, United Kingdom
We support the organization of the Collaborative European Research Conference (CERC 2020) in Belfast, Northern-Ireland. The multidisciplinary Collaborative European Research Conference 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.
In previous years, contributions came from computer science, biology, bioinformatics, business information systems, marketing, IT-security, civil engineering, education, psychology, multimedia, art and others. Contributing authors came among other from Ireland, Germany, United Kingdom, Norway, France and USA.
Please note the Call for Papers (CfP).

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Major Cities of Europe Web Seminar toward Digital Ethics, Humanism and Research - Laying the Foundation for Rethinking Cities
2020-09-09 16:00 - 17:30 (Europe/Berlin) | Online / Virtual Conference
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)
2020-09-07 01:30 - 2020-09-11 14:15 (Europe/Berlin) | TU Wien, Karlsplatz 13, Vienna, 1040, Austria
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

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Thesis Presentation: Named-Entity Recognition on Publications and Raw-Text for Meticulous Insight at Visual Trend Analytics
2020-03-17 16:00 - 16:30 (Europe/Berlin) | TU Darmstadt / GRIS, Fraunhoferstraße 5, Darmstadt, Hessian, 64283, Germany
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.

21. Darmstadt Computer Graphics Evening
2019-12-05 16:30 - 21:00 (Europe/Berlin) | Fraunhofer IGD, Fraunhoferstraße 5, Darmstadt, Hesse, 64283, Germany
The Darmstadt Computer Graphics Evening (Darmstädter Computer Graphik Abend – CGA) has been a fixed program item of the Fraunhofer IGD for more than two decades. As in the years before, Fraunhofer IGD and its affiliated chairs will be honored with the most successful works, most promising promotions and most innovative ideas from the past twelve months.
In addition, the Computer Graphics Evening will provide the opportunity to gather information about trends in applied Visual Computing in a festive atmosphere and to network with representatives from research, industry and politics.

Research Day 2019 at h_da
2019-11-26 14:00 - 18:00 (Europe/Berlin) | h_da, B15, Stephanstraße 7, Darmstadt, Darmstadt, 64295
The “Research Day” (German original title: “Tag der Forschung”) was first held back in 2002, establishing a tradition, where every year in November, news about current research activities were shown and the time for networking and discussion is given. The annual Research Day has a special significance for the Darmstadt University of Applied Sciences. It is aimed at university members, company representatives, institutions in the region and the interested public. Exciting lectures and discussions on current research activities at the university and the awarding of the science prize are part of the program.
This year’s Research Day is themed Digitalization and Sustainable Development.

Research Day 2019 of the Hessian Universities of Applied Sciences (HAW)
2019-10-29 14:00 - 18:30 (Europe/Berlin) | Frankfurt UAS, Nieblungenplatz 1, Frankfurt am Main, Hesse, 60318, Germany
On 29 October, the focus will be on research at the HAWs in Hesse: within the framework of the Research Day 2019, the research awards will be presented to HAW Hessen.
To the agenda: After the welcome by President Prof. dr. Frank E.P. Dievernich speaks to Secretary of State Ayse Asar (HMWK). Prof. Dr. Dr. h.c. Volker Mosbrugger (Senckenberg Society for Natural Research, Polytechnic Society Frankfurt am Main) gives the keynote address on the topic “Science in transition – the new challenges”. Subsequently, the festive award ceremony takes place.
After the break, scientists from the Frankfurt UAS present their research projects in the entertaining Pecha Kucha format. The event concludes with a panel discussion under the motto “Vision, Success, Appreciation – Applied Research Makes People Happy”.
In addition, in the form of a poster exhibition “Research for the practice – 10 years of research campaign by HAW Hessen and HMWK” projects from ten years of research funding for the Hessian HAW are presented.
We were invited to join to event as an active research contributor. We are going to present our latest results the Hessian funded research project AVARTIM toward Advanced Visual Analytical Reasoning for Technology and Innovation Management (please also note our summary poster) .

WissDok 2019
2019-10-07 09:00 - 19:00 (Europe/Berlin) | h_da, Dieburg, Germany, Max-Planck-Straße 2, Dieburg, Hesse, 64807, Germany
WissDok is an annual event for scientific and media documentation of public media organizations. The event focuses on the pragmatic-current edge of technical, organizational and scientific development in the documentation in its role as an incarnation of information science. The invited speakers deliver an annual update on the current development of various dimensions in this professional field in approximately 2-hour sessions. The event is part of the wissDok program and an offer to the specialist with opportunity for discussion.
The symposium at the Mediencampus is part of the wissDok program and an offer to the specialist public with opportunity for discussion. At the symposium our team will give a talk about Artificial Intelligence and Data Analytics.

14th International Symposium on Visual Computing (ISVC 2019)
2019-10-07 - 2019-10-09 | Harrah’s Hotel & Casino, 15 US-50, Stateline, Lake Tahoe, NV, 89449, United States
We are attending the 14th International Symposium on Visual Computing (ISVC 2019) and presenting our accepted paper titled “A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management”.
More information about our paper and the conference you will find in the news. The program is available on the conference website

Virtual and Augmented Reality in Education (VARE 2019) Conference
2019-09-18 - 2019-09-20 | Altis Grand Hotel, Rua Castilho 13A, Lisbon, 1269-072, Portugal
We are attending this year’s Virtual and Augmented Reality in Education conference (VARE 2019) and presenting our accepted paper titled “A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts”.
More information about our paper and the conference you will find in the news. Also note the conference program.

OpenRheinMain Conference 2019
2019-09-13 | h_da, Darmstadt, Germany, Schöfferstraße 3, Darmstadt, 64295, Germany
OpenRheinMain (ORM 2019) is the 1st edition of an annual IT conference on open source and emerging digital technologies. This includes, but is not limited to, Open-Source, Intelligent Automation and DevOps, Cloud Computing, and Internet of Things.
The purpose of the conference to interlink researchers and industrial partner of the Rhein Main region. Therefore, the conference considers stakeholders from both in an appropriate proportion.
At the conference we will present our insights to “Visual Text Analytics for Technology and Innovation Management”.

Pre-Conference Workshop "Automated data analysis as a tool of TIE research"
2019-09-11 15:00 - 18:00 (Europe/Berlin) | HUB31, Darmstadt, Hilpertstraße 31, Darmstadt, Hesse, 64295, Germany
This year we get the opportunity to give a keynote speech at the pre-conference workshop on “Automated data analysis as a tool of TIE research” (original German title: “Automated Datenanalyse als Werkzeug der TIE Forschung”). The talk will be about “Visual Analytics for early technology detection”.
The TIE conference has always had a permanent place in the calendar of leading German and German-speaking scientists in the fields of technology and innovation management as well as entrepreneurship.

Thesis Presentation: Contrasted Data from Science and Web for Advanced Visual Trend Analytics
2019-08-26 15:30 - 16:00 (Europe/Berlin) | TU Darmstadt / GRIS, Fraunhoferstraße 5, Darmstadt, Hessian, 64283, Germany
Where: TU Darmstadt / GRIS, Fraunhoferstr. 5, Room 073
Who: Rehman Ahmed Abdul (Author), Prof. Dr. Arjan Kuijper (Supervisor), Dipl.-Inf. Dirk Burkhardt (Advisor/Co-Supervisor)
What: Master Thesis – “Contrasted Data from Science and Web for Advanced Visual Trend Analytics”
Abstract:
With more publicly accessible digital libraries accessible, a plethora of digital research data is now available for gaining insights into actual and upcoming technology trends. These trends are essential to researchers, business analysts, and decision-makers for making strategic decisions and setting strategic goals. Appropriate processing and graphical analysis methods are required in order to extract meaningful information from the data. In particular, the combination of data mining approaches together with visual analytics leads to real beneficial applications to support decision making in e.g. innovation or technology management.
The data from digital libraries is only limited to research and overlooks the market aspects e.g if the trend is not important for key business players, it is irrelevant for the market. This importance of market aspects creates a demand for validation approaches based on market data. Most of the current market data can be found publically on websites and social networks, e.g. as news from enterprises or on tech review sites or on tech blogs. Therefore, it makes sense to consider this public and social media data as contrasting data to the research digital library data that can be used to validate technology trends.
The goal of this thesis is to enable trend analysis on public and social web data and compare it with retrieved trends based on research library data to enable validation of trends. To achieve this goal a model is proposed that acquires public/social web and digital library data based on user-defined scope called a “campaign”, which is then visually transformed from raw data into interactive visualizations passing through different stages of data management, enrichment, transformation, and visual mapping. These interactive visualizations can either be used in insight analysis to gain trend insights for an individual data source or they can be used in comparative analysis with the goal of validating trends from two contrasting data sources.

Thesis Presentation: Visual Trend Analysis on Condensed Expert Data beside Research Library Data for Enhanced Insights
2019-08-26 15:00 - 15:30 (Europe/Berlin) | TU Darmstadt / GRIS, Fraunhoferstraße 5, Darmstadt, Hessian, 64283, Germany
Where: TU Darmstadt / GRIS, Fraunhoferstr. 5, Room 073
Who: Muhammad Ali Riaz (Author), Prof. Dr. Arjan Kuijper (Supervisor), Dipl.-Inf. Dirk Burkhardt (Advisor/Co-Supervisor)
What: Master Thesis – “Visual Trend Analysis on Condensed Expert Data beside Research Library Data for Enhanced Insights”
Abstract:
In the present age of information, we live amidst seas of digital text documents including academic publications, white papers, news articles, patents, newspapers. To tackle the issue of the ever-increasing amount of text documents, researchers from the field of text mining and information visualization have developed tools and techniques to facilitate text analysis. In the context of visual trend analysis on text data, the use of well-structured patent data and public digital libraries are quite established. However, both sources of information have their limitations. For instance, the registration process for patents takes at least one year, which makes the extracted insights not suitable to research on present scenarios. In contrast to patent data, the digital libraries are up-to-date but provide high-level insights, only limited to broader research domains, and the data usage is almost restricted on meta information, such as title, author names and abstract, and they do not provide full text.
For a certain type of detailed analysis such as competitor analysis or portfolio analysis, data from digital libraries is not enough, it would also make sense to analyze the full-text. Even more, it can be beneficial to analyze only a limited dataset that is filtered by an expert towards a very specific field, such as additive printing or smart wearables for medical observations. Sometimes also a mixture of both digital library data and manually collected documents is relevant to be able to validate a certain trend, where one gives a big picture and other gives a very condensed overview of the present scenario.
The thesis aims, therefore, to focus on such manually collected documents by experts that can be defined as condensed data. So, the major goal of this thesis is to conceptualize and implement a solution that enables the creation and analysis of such a condensed data set and compensate therewith the limitations of digital library data analysis. As a result, a visual trend analysis system for analyzing text documents is presented, it utilizes the best of both state-of-the-art text analytics and information visualization techniques. In a nutshell, the presented trend analysis system does two things. Firstly, it is capable of extracting raw data from text documents in the form of unstructured text and meta-data, convert it into structured and analyzable formats, extract trends from it and present it with appropriate visualizations. Secondly, the system is also capable of performing gap-analysis tasks between two data sources, which in this case is digital library data and data from manually collected text documents (Condensed Expert Data). The proposed visual trend analysis system can be used by researchers for analyzing the research trends, organizations to identify current market buzz and industry trends, and many other use-cases where text data is the primary source of valuable information.

23rd International Conference Information Visualization (iV 2019)
2019-07-02 - 2019-07-05 | Paris, 20, avenue George Sand, La Plaine Saint-Denis, 93210, France
We are attending this year’s International Information Visualisation Conference (iV 2019) and presenting our accepted paper titled “Visual Analytics for Analyzing Technological Trends from Text”.
More information about our paper and the conference you will find in the news.
