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

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: tba

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: tba

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

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: tba

More information about the technology: Scitics for Visual Trend Analytics

6th Collaborative European Research Conference (CERC 2020)

We, particularly me and the Human-Computer Interaction & Visual Analytics group of the Darmstadt University of Applied Sciences, 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).

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

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.

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Kickoff of the Stategic Networking Project VisCOST

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.

 

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Two succeeful Submissions to ICTE in Transportation and Logistics book

We could successfully submit two chapters to the current ICTE in Transportation and Logistics book. The goal of the book “ICTE in Transportation and Logistics” is an interdisciplinary annual issue published by Springer Nature Switzerland AG on the edge between transportation, logistics, economy and computer science highlighting sociotechnical aspects of any real sustainable system. The issue would be the announcing area of successful research projects giving possibilities for fast dissemination the information about new findings. The book will be covered by Scopus and Web of Science.

#1 Visual Analytics in Mobility, Transportation and Logistics

Mobility, transportation and logistics are more and more influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans’ mobility behavior. These indicators will lead to massive changes in our daily live with regards to mobility, transportation and logistics. New technologies will lead to a different mobility behavior with new constraints. These changes in mobility behavior and logistics require analytical systems to forecast the required information and probably appearing changes. These systems have to consider different perspectives and employ multiple indicators. Visual Analytics provides both, the analytical approaches by including machine learning approaches and interactive visualizations to enable such analytical tasks. In this paper the main indicators for Visual Analytics in the domain of mobility transportation and logistics are discussed and followed by exemplary case studies to illustrate the advantages of such systems. The examples are aimed to demonstrate the benefits of Visual Analytics in mobility.

Link to paper: doi: 10.1007/978-3-030-39688-6_12

#2 Process Support and Visual Adaptation to Assist Visual Trend Analytics in Managing Transportation Innovations

In the domain of mobility and logistics, a variety of new technologies and business ideas are arising. Beside technologies that aim on ecologically and economic transportation, such as electric engines, there are also fundamental different approaches like central packaging stations or deliveries via drones. Yet, there is a growing 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. Commonly adaptive systems investigate only the users’ behavior, while a process-related supports could assist to solve an analytical task more efficient and effective. In this article an approach that enables non-experts to perform visual trend analysis through an advanced process support based on process mining is described. This allow us to calculate a process model based on events, which is the baseline for process support feature calculation. These features and the process model enable to assist non-expert users in complex analytical tasks.

Link to paper: doi: 10.1007/978-3-030-39688-6_40

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VIS-Group co-organizes the International Information Visualisation Conference (iV2020)

Our research group on Human-Computer Interaction and Visual Analytics is co-organizing the track International Symposium Visual Analytics and Data Science (VA) at the next International Information Visualisation Conference (iV 2020) in Vienna, Austria on 28-31 July 2020. The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development.

Interested parties in the arae of Visual Computing are invited to submit paper propsals until 15 March 2020 via the conference submission system. Please note the covered topics and the call for papers, as well as the submision guidelines.

Please note our summarization to the 24rd International Conference Information Visualization (iV 2020) event.

Research Day at h_da

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.

The event takes place at the h_da, building B15 on 26 November 2019, 14:00-18:00.

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Paper accepted at 14th International Symposium on Visual Computing (ISVC 2019)

I’m proud to announce that our paper titled “A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management” is accepted at the high-class visual computing conference ISVC 2019 in Lake Tahoe, NV, USA. The purpose of the International Symposium on Visual Computing (ISVC) is to provide a common forum for researchers, scientists, engineers and practitioners throughout the world to present their latest research findings, ideas, developments and applications in visual computing. ISVC seeks papers describing contributions to the state of the art and state of the practice in the four central areas of visual computing: computer vision, computer graphics, virtual reality, and visualization. The paper reflects some new on-going advancements of our innovative Trend Analytics solution Scitics.

Paper: A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management

Abstract:
Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analytics possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and do not include the human in the analysis process. Outcomes from research on information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics.

Link to paper/fulltext: https://dx.doi.org/10.1007/978-3-030-33723-0_23
Link to poster: https://dx.doi.org/10.5281/zenodo.3473065

 

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Insight on Visual Text Analytics for Technology and Innovation Management at OpenRheinMain Conference

We get the opportunity to give some insights to “Visual Text Analytics for Technology and Innovation Management”, based on our core Trend Analytics technology Scitics, on the OpenRheinMain Conference. We want to give insights on how Visual Analytics techniques can be used to enable effective technology and innovation management on behalf of external/web data as well as internal/company data.

The 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 is to interlink researchers and industrial partner of the Rhein Main region. Therefore, the conference considers stakeholders from both in an appropriate proportion. The conference will take place on September 13th, 2019 at Darmstadt University of Applied Science.

Due to heterogeneity of the event participants, the chances are high to strengthen the cooperation with local enterprises. We expect, that this will be relevant for further research actions to strengthen  the local region.

The extended abstract of the presentation is available under: https://dx.doi.org/10.5281/zenodo.3408391
More information on the event website: https://www.openrheinmain.org

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