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Tag Archive for: Visual Analytics

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Lennart Sina defended his Master Thesis on Visual Analytics for Unstructured Data and Scalable Data Models

08/11/2021/in h_da, News, Research, VIS Research Group/by Dirk Burkhardt

In the thesis, Lennart Sina conceptualized and implemented a visual analytics system that scales data through middleware to enable more efficient analysis. For this purpose, diverse approaches and systems were investigated, which led to a coherent concept. The concept was implemented and connected to an existing database, enabling real-world use of the system and real-world conditions. The scientific contribution of the present work is three-fold: (1) the concept of a visual analytics system to scale data, (2) a novel data model, and (3) a novel and a fully implemented visual dashboard that also enables reporting.

The post Lennart Sina defended his Master Thesis on Visual Analytics for Unstructured Data and Scalable Data Models appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

Best Paper Award at the iV 2021

04/08/2021/in h_da, News, Research, VIS Research Group/by Dirk Burkhardt

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 the innovative contribution in terms of originality of concepts and application. The “Best Paper Awards” is given to contributions which will be selected by the committee among the papers presented in iV2021 and applied for the award. 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 post Best Paper Award at the iV 2021 appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

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

14/06/2021/in h_da, News, Research, VIS Research Group/by Dirk Burkhardt

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

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

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

Link to Paper: https://doi.org/10.1007/s11042-021-10972-3

The post Article on Visual Analytics for Technology and Innovation Management Published in Journal Multimedia Tools and Applications appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

Proceedings of the Collaborative European Research Conference 2020 are now online!

22/02/2021/in h_da, News, Publication, Research Center, VIS Research Group/by Dirk Burkhardt

It has taken a while, but now the proceedings of the last Collaborative European Research Conference (CERC 2020) are now online on CEUR-WS.org.

The 2020 proceedings are available under: http://ceur-ws.org/Vol-2815/.

To download as zip-file: ftp://sunsite.informatik.rwth-aachen.de/pub/publications/CEUR-WS/Vol-2815.zip.

The multidisciplinary Collaborative European Research Conference (CERC) is an annual event that takes place since 2011 when it was initiated by University partners across Europe. It brings together researchers from a wide range of disciplines in order to foster knowledge transfer, inter-disciplinary exchange and collaboration. For more information about the conference, please check the website http://www.cerc-conf.eu.

Three Papers Accepted at IEEE Information Technology and Management Science Conference (ITMS 2020)

12/10/2020/in h_da, News, Research, VIS Research Group/by Dirk Burkhardt

Three of our submitted collaboration papers got accepted at the this year’s IEEE Information Technology and Management Science Conference 2020. The conference aims at bringing together young scientists and researchers from information technologies and management sciences in an effort to promote and encourage cross-fertilization of ideas and tools related to the general topics of the conference, such as Information Technology, Information Systems, Computer Technologies, Data Processing, System Security and Control, Modelling and Simulation, Automatic Control, E-Commerce and E-Governance, Cloud Computing, Human Computer Interaction, Cyber-Physical Systems, Intelligent Systems, Internet of Everything.

Paper #1: Visual Analytics Indicators for Mobility and Transportation

Abstract

Visual Analytics enables a deep analysis of complex and multivariate data by applying machine learning methods and interactive visualization. These complex analyses lead to gain insights and knowledge for a variety of analytics tasks to enable the decision-making process. The enablement of decision-making processes is essential for managing and planning mobility and transportation. These are influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans’ mobility behaviour. New technologies will lead to a different mobility behaviour with other constraints. These changes in mobility behaviour require analytical systems to forecast the required information and probably appearing changes. These systems must consider different perspectives and employ multiple indicators. Visual Analytics enable such analytical tasks. We introduce in this paper the main indicators for Visual Analytics for mobility and transportation that are exemplary explained through two case studies.


Links

  • Paper as PDF
  • doi:10.1109/ITMS51158.2020.9259321

More information about the technology and topic: Scitics for Visual Trend Analytics

Paper #2: Innovations in Mobility and Logistics: Assistance of Complex Analytical Processes in Visual Trend Analytics

Abstract

A variety of new technologies and ideas for businesses are arising in the domain of logistics and mobility. It can be differentiated between fundamental new approaches, e.g. central packaging stations or deliveries via drones and minor technological advancements that aim on more ecologically and economic transportation. The need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance is growing. The users’ behavior is commonly investigated in adaptive systems, which is considering the induvial preferences of users, but neglecting often the tasks and goals of the analysis. A process-related supports could assist to solve an analytical task in a more efficient and effective way. We introduce in this paper an approach that enables non-professionals to perform visual trend analysis through an advanced process assistance based on process mining and visual adaptation. This allows generating a process model based on events, which is the baseline for process support feature calculation. These features in form of visual adaptations and the process model enable assisting non-experts in complex analytical tasks.


Links

  • Paper as PDF
  • doi:10.1109/ITMS51158.2020.9259309

More information about the technology and topic: Scitics for Visual Trend Analytics

Paper #3: On Microservice Architecture Based Communication Environment for Cycling Map Developing and Maintenance Simulator

Abstract

Urban transport infrastructure nowadays involves environmentally friendly modes of transport, the most democratic of which is cycling. Citizens will use bicycles if a reasonably designed cycle path scheme will be provided. Cyclists also need to know the characteristics and load of the planned route before the trip. Prediction can be provided by simulation, but it is often necessary to use heterogeneous and distributed models that require a specific communication environment to ensure interaction. The article describes the easy communication environment that is used to provide microservices communication and data exchange in a bicycle route design and maintenance multi-level simulator.


Links

  • Paper as PDF
  • doi:10.1109/ITMS51158.2020.9259299


The post Three Papers Accepted at IEEE Information Technology and Management Science Conference (ITMS 2020) appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

Two Paper accepted at 6th Collaborative European Research Conference (CERC 2020)

22/08/2020/in h_da, News, Publication, Research, VIS Research Group/by Dirk Burkhardt

At the this year’s Collaborative European Research Conference (CERC 2020) two of our students papers titled “Visual Dashboards in Trend Analytics to Observe Competitors and Leading Domain Experts” and “A Future Prospect for European Collaboration on Advanced Analytics in Economy and Society” were accepted for presentation. Due to Corona epidemic the conference is hold virtually. The multidisciplinary CERC is an annual event that takes place since 2011 when it was initiated by University partners across Europe. It brings together researchers from a wide range of disciplines in order to foster knowledge transfer, inter-disciplinary exchange and collaboration.

Paper #1: Visual Dashboards in Trend Analytics to Observe Competitors and Leading Domain Experts

Abstract:
The rapid changes due to digitalization challenges a variety of market players and forces them to find strategies to be aware of changes in these markets, particularly those that impacts their business. The main challenge is how a practical solution could look like and how technology can support market players in these trend ob-servation tasks. The paper outlines therefore a technological solution to observe specific authors e.g. researchers who influence a certain market or engineers of competitor. In many branches both are well-known groups to market players and there is almost the need of a technology that support the topical observation. The main contributions of this paper are next to the concept of how a visual dash-board could enable a market observation and how data has to be processed for it, the prototypical implementation which enables an evaluation later on. Further-more, the definition of a principal technological analysis for innovation and tech-nology management is created and is also an important contribution to the scien-tific community that specifically considers the technology perspective and it cor-responding requirements.

Link to paper/fulltext: http://ceur-ws.org/Vol-2815/CERC2020_paper14.pdf

More information about the technology: Scitics for Visual Trend Analytics

Paper #2: A Future Prospect for European Collaboration on Advanced Analytics in Economy and Society

Abstract:
Analytical Reasoning by applying machine learning approaches, artificial intelli-gence, NLP and visualizations allow to get deep insights into the different do-mains of various stakeholders and enable to solve complex tasks. Thereby the tasks are very heterogenous and subject of investigation in the different areas of application. These tasks or challenges should be defined by the stakeholders themselves and lead through a deep investigation to advanced analytical ap-proaches. We therefore set up a strategic alliance of research, enterprises and so-cietal organization with the goal of a strong collaboration to identify in a first step these challenges and workout technological solutions for each application scenar-io. We give in this paper a first draft of current challenges and technological ad-vancements. The main contribution of this paper is next to an accurate description of the current challenges in the analytics domain, also the description of an agen-da how these challenges can be solved. Furthermore, a process is explained, how the strategic alliance should act and organize their work to realize beneficial and useful analytical solutions.

Link to paper/fulltext: http://ceur-ws.org/Vol-2815/CERC2020_paper27.pdf

The whole proceedings of the CERC 2020 are available under: http://ceur-ws.org/Vol-2815/.

Paper accepted at 24rd Internation Conference Information Visualization (iV 2020)

06/08/2020/in Events, h_da, News, Research, VIS Research Group/by Dirk Burkhardt

We are very glad to be accepted for presenting our paper titled “Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing” at the high-class conference Information Visualisation Conference (iV 2020). Due to Corona epidemic the conference is hold virtually. The iV 2020 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.

Comparison of Full-text Articles and Abstracts for Visual Trend Analytics through Natural Language Processing

Abstract:
Scientific publications are an essential resource for detecting emerging trends and innovations in a very early stage, by far earlier than patents may allow. Thereby Visual Analytics systems enable a deep analysis by applying commonly unsupervised machine learning methods and investigating a mass amount of data. A main question from the Visual Analytics viewpoint in this context is, do abstracts of scientific publications provide a similar analysis capability compared to their corresponding full-texts? This would allow to extract a mass amount of text documents in a much faster manner. We compare in this paper the topic extraction methods LSI and LDA by using full text articles and their corresponding abstracts to obtain which method and which data are better suited for a Visual Analytics system for Technology and Corporate Foresight. Based on a easy replicable natural language processing approach, we further investigate the impact of lemmatization for LDA and LSI. The comparison will be performed qualitative and quantitative to gather both, the human perception in visual systems and coherence values. Based on an application scenario a visual trend analytics system will further illustrate the outcomes.

Link to paper/fulltext: DOI: 10.1109/10.1109/IV51561.2020.00065

More information about the technology: Scitics for Visual Trend Analytics

Thesis Presentation: Named-Entity Recognition on Publications and Raw-Text for Meticulous Insight at Visual Trend Analytics

16/03/2020/in Events, h_da, News, Teaching, VIS Research Group/by Dirk Burkhardt

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.

The post Thesis Presentation: Named-Entity Recognition on Publications and Raw-Text for Meticulous Insight at Visual Trend Analytics appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

Advanced Seminar toward Visual Analaytics in next Summer Semester at h_da/FBI (computer science)

12/03/2020/in h_da, Teaching, VIS Research Group/by Dirk Burkhardt

In the upcoming summer semester 2020, our team provides an advanced seminar at the department of computer science at the Darmstadt University of Applied Sciences. The topic of the seminar will be toward “Visual Analytics for Smart Manufacturing and Trend Analysis”:

Due to the increasing digitization, analyzes are a constant necessity, which also applies to the identification of errors, problems or opportunities for improvement. With visual analytics, the combination of algorithmic and massive calculation opportunities of computer-based systems on the one side as well as the visual and cognitive skills of the users on the other side are used together. The seminar focuses on the use of visual analytics in the two current areas of smart manufacturing and trend analysis. On behalf of the given task, current approaches, methods and implementations should be researched and examined. The goal should be a scientific elaboration based on empirical and scientific standards.

Interested students are invited to register soon, since the number of places will be limited.

The post Advanced Seminar toward Visual Analaytics in next Summer Semester at h_da/FBI (computer science) appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

Kickoff of the Stategic Networking Project VisCOST

26/02/2020/in h_da, News, Project, Research, VIS Research Group/by Dirk Burkhardt

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.

 

The post Kickoff of the Stategic Networking Project VisCOST appeared first on Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h_da).

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