Scientific Publications

@inproceedings{Nazemi2019c,

title = {A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management},

author = {Kawa Nazemi and Dirk Burkhardt},

editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Daniela Ushizima and Sek Chai and Shinjiro Sueda and Xin Lin and Aidong Lu and Daniel Thalmann and Chaoli Wang and Panpan Xu},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2019/10/2019isvc.pdf, Paper as PDF

https://dx.doi.org/10.5281/zenodo.3473065, doi:10.5281/zenodo.3473065 (Poster)},

doi = {10.1007/978-3-030-33723-0_23},

isbn = {978-3-030-33723-0},

year  = {2019},

date = {2019-10-09},

booktitle = {Advances in Visual Computing},

pages = {283--294},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analysis 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 almost neglect the human in the analysis process. Outcomes from research in 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.},

keywords = {Artificial Intelligence, Data Analytics, Human Factors, Human-Centered Interfaces, Human-Computer Interaction, Information Visualization, Intelligent Systems, maschine learning, Visual Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2019b,

title = {A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts},

author = {Dirk Burkhardt and Kawa Nazemi and Arjan Kuijper and Egils Ginters},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2019/09/2019vare-i.pdf, Dowload as PDF},

doi = {  10.5281/zenodo.3473041},

isbn = {978-88-85741-41-6},

year  = {2019},

date = {2019-09-18},

booktitle = {5th International Conference of the Virtual and Augmented Reality in Education (VARE2019)},

pages = {11--19},

publisher = {CAL-TEK SRL},

address = {Rende, Italy},

abstract = {The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.},

note = {Nominated for Best Paper Award},

keywords = {Business Analytics, Decision Support Systems, Human-Computer Interaction, Information Visualization, Mobile Devices, Mobile Visual Analytics, Visual Trend Analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2018b,

title = {Visual Analytics for Analyzing Technological Trends from Text},

author = {Kawa Nazemi and Dirk Burkhardt},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2019/08/2019iV.pdf, Paper as PDF},

doi = {10.1109/IV.2019.00041},

issn = {2375-0138},

year  = {2019},

date = {2019-07-02},

booktitle = {2019 23rd International Conference Information Visualisation (iV)},

pages = {191-200},

publisher = {IEEE},

abstract = {The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends.},

note = {Best Paper Award},

keywords = {Emerging Trend Identification, Information Visualization, Trend Analytics, Visual Analytics, Visual Business Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2018,

title = {Juxtaposing Visual Layouts – An Approach for Solving Analytical and Exploratory Tasks through Arranging Visual Interfaces},

author = {Kawa Nazemi and Dirk Burkhardt},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2018vare_ii.pdf, Paper as PDF

http://www.scopus.com/inward/record.url?eid=2-s2.0-85056741373&partnerID=MN8TOARS, Link to Publisher},

doi = {10.5281/zenodo.2542952},

isbn = {978-1-5108-7222-6},

year  = {2018},

date = {2018-09-21},

booktitle = {4th International Conference of the Virtual and Augmented Reality in Education (VARE 2018)},

pages = {144-153},

publisher = {CAL-TEK SRL},

address = {Rende, Italy},

series = {4},

abstract = {Interactive visualization and visual analytics systems enables solving a variety of tasks. Starting with simple search tasks for outliers, anomalies etc. in data to analytical comparisons, information visualizations may lead to a faster and more precise solving of tasks. There exist a variety of methods to support users in the process of task solving, e.g. superimposing, juxtaposing or partitioning complex visual structures. Commonly all these methods make use of a single data source that is visualized at the same time. We propose in this paper an approach that goes beyond the established methods and enables visualizing different databases, data-sets and sub-sets of data with juxtaposed visual interfaces. Our approach should be seen as an expandable method. Our main contributions are an in-depth analysis of visual task models and an approach for juxtaposing visual layouts as visual interfaces to enable solving complex tasks.},

keywords = {Information Visualization, Visual Analytics, Visual Interfaces, Visual Tasks},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2018a,

title = {Visualizing Law - A Norm-Graph Visualization Approach based on Semantic Legal Data},

author = {Dirk Burkhardt and Kawa Nazemi},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2018vare_i.pdf, Paper as PDF

http://www.scopus.com/inward/record.url?eid=2-s2.0-85056721291&partnerID=MN8TOARS, Link to Publisher},

doi = {10.5281/zenodo.2543729},

isbn = {978-1-5108-7222-6},

year  = {2018},

date = {2018-09-21},

booktitle = {4th International Conference of the Virtual and Augmented Reality in Education (VARE 2018)},

pages = {154-162},

publisher = {CAL-TEK SRL},

address = {Rende, Italy},

series = {4},

abstract = {Laws or in general legal documents regulate a wide range of our daily life and also define the borders of business models and commercial services. However, legal text and laws are almost hard to understand. From other domains it is already known that visualizations can help understanding complex aspects easier. In fact, in this paper we introduce a new approach to visualize legal texts in a Norm-graph visualization. In the developed Norm-graph visualization it is possible to show major aspects of laws and make it easier for users to understand it. The Norm-graph is based on semantic legal data, a so called Legal-Concept-Ontology. },

keywords = {Decision Support Systems, E-Government, Information Visualization, Law Visualization, Norm-graph, Policy Modeling, Semantic Data},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2017b,

title = {Informationsvisualisierung und Visual Analytics zur Unterstützung von E-Government Prozessen},

author = {Dirk Burkhardt and Kawa Nazemi},

editor = {Korinna Bade and Matthias Pietsch and Susanne Raabe and Lars Schütz},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2017kat.pdf, Paper as PDF

https://www.shaker.de/de/content/catalogue/index.asp?lang=de&ID=8&ISBN=978-3-8440-5439-2&search=yes, Publisher Site

https://dx.doi.org/10.2370/9783844054392, doi:10.2370/9783844054392 (Full Proceedings)},

doi = {10.5281/zenodo.2576074},

isbn = {978-3844054392},

year  = {2017},

date = {2017-01-05},

booktitle = {Technologische Trends im Spannungsfeld von Beteiligung – Entscheidung – Planung: Fachforum DIGITALES PLANEN und GESTALTEN 2017},

pages = {29--38},

publisher = {Shaker Verlag},

address = {Aachen, Germany},

abstract = {Politische und gesellschaftliche Prozesse werden durch Informationen sehr stark geprägt, wie auch die jüngsten Ereignisse aufzeigen. Diese Informationen können, trotz enormer Fortschritte, nicht immer aus den sehr großen, heterogenen und verteilten Daten entnommen werden. „Big Data“ stellt somit auch in der öffentlichen Verwaltung eine immer größere Herausforderung dar. Sowohl durch eine umfangreiche Erhebung von Statistiken, als auch durch Dokumente wie Berichte und Studien, wachsen in Behörden die zu bewältigenden Informationsaufgaben. Darüber hinaus spielt die Berücksichtigung von Bürgermeinungen, vor allem auf kommunaler Ebene, eine immer größere Rolle. Eine Auswertung ohne moderne Informationstechnik ist dabei kaum mehr möglich. Damit aber aus diesen Daten tatsächlich die relevanten Informationen extrahiert werden, bedarf es Informationsvisualisierung und Visual Analytics Systeme die sehr detaillierte, aber dennoch einfache und schnelle Analysen für den Menschen erlauben. Dies stellt aber sehr hohe Anforderungen an die visuellen Systeme, da sie gleichzeitig auch den Nutzer und dessen Fähigkeiten berücksichtigen müssen.},

keywords = {E-Government, E-Participation, Information Visualization, Interactive Visualization, Policy Modeling, Visual Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2015c,

title = {Visual Trend Analysis with Digital Libraries},

author = {Kawa Nazemi and Reimond Retz and Dirk Burkhardt and Arjan Kuijper and Jörn Kohlhammer and Dieter W. Fellner},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2015iknow.pdf, Paper as PDF},

doi = {10.1145/2809563.2809569},

isbn = {978-1-4503-3721-2},

year  = {2015},

date = {2015-10-21},

booktitle = {Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business},

pages = {14:1--14:8},

publisher = {ACM},

address = {New York, NY, USA},

abstract = {The early awareness of new technologies and upcoming trends is essential for making strategic decisions in enterprises and research. Trends may signal that technologies or related topics might be of great interest in the future or obsolete for future directions. The identification of such trends premises analytical skills that can be supported through trend mining and visual analytics. Thus the earliest trends or signals commonly appear in science, the investigation of digital libraries in this context is inevitable. However, digital libraries do not provide sufficient information for analyzing trends. It is necessary to integrate data, extract information from the integrated data and provide effective interactive visual analysis tools. We introduce in this paper a model that investigates all stages from data integration to interactive visualization for identifying trends and analyzing the market situation through our visual trend analysis environment. Our approach improves the visual analysis of trends by investigating the entire transformation steps from raw and structured data to visual representations.},

note = {Honorable Mention of the Demo},

keywords = {Data Mining, Information Extraction, Information Visualization, Trend Analysis, Visual Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2015,

title = {Explorative Visualization of Impact Analysis for Policy Modeling by Bonding Open Government and Simulation Data},

author = {Dirk Burkhardt and Kawa Nazemi and Egils Ginters and Artis Aizstrauts and Jörn Kohlhammer},

editor = {Sakae Yamamoto},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2015hcii.pdf, Paper as PDF

http://2015.hci.international, Conference Site},

doi = {10.1007/978-3-319-20612-7_4},

isbn = {978-3-319-20612-7},

year  = {2015},

date = {2015-08-02},

booktitle = {Human Interface and the Management of Information. Information and Knowledge Design},

volume = {9172},

pages = {34--45},

publisher = {Springer International Publishing},

address = {Switzerland},

series = {Lecture Notes in Computer Science, vol 9172},

abstract = {Problem identification and solution finding are major challenges in policy modeling. Statistical indicator-data build the foundation for most of the required analysis work. In particular finding effective and efficient policies that solve an existing political problem is critical, since the forecast validation of the effectiveness is quite difficult. Simulation technologies can help to identify optimal policies for solutions, but nowadays many of such simulators are stand-alone technologies. In this paper we introduce a new visualization approach to enable the coupling of statistical indicator data from Open Government Data sources with simulators and especially simulation result data with the goal to provide an enhanced impact analysis for political analysts and decision makers. This allows, amongst others a more intuitive and effective way of solution finding.},

keywords = {Decision Making, Impact Analysis, Information Visualization, Open Government Data, Policy Modeling, Simulation, Visual Analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2014c,

title = {Visual Explanation of Government-Data for Policy Making through Open-Data Inclusion},

author = {Dirk Burkhardt and Kawa Nazemi and Wilhelm Retz and Jörn Kohlhammer},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2014icitst.pdf, Paper as PDF},

doi = {10.1109/ICITST.2014.7038782},

isbn = {978-1-908320-39-1},

year  = {2014},

date = {2014-12-08},

booktitle = {The 9th International Conference for Internet Technology and Secured Transactions (ICITST-2014)},

pages = {83-89},

publisher = {IEEE},

address = {Piscataway, NJ, USA},

organization = {Infonomics Society},

abstract = {Commonly, data used in public authorities are statistical data about certain indicator. Such valid kind of data allows an objective observation about indicator developments over time. In case of a significant deviation from the normal indicator level, it is difficult to understand the reasons for upcoming problems. In our paper we present an approach that allows an enhanced information gathering through an improved information overview about the depending aspects to such an indicator by considering governmental data-sources that provide also other types of data than just statistics. Even more, our approach integrates a system that allows generating explanations for Open Government Data, especially to specific indicators, based on Linked-Open Data. This enables decision-makers to get hints for unexpected reasons of concrete problems that may influence an indicator.},

keywords = {Decision Making, E-Government, Information Visualization, Linked-Open Data Visualization, Open Government Data Visualization, Policy Modeling, Rule Generation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2014,

title = {Adaptive Visualization of Linked-Data},

author = {Kawa Nazemi and Dirk Burkhardt and Reimond Retz and Arjan Kuijper and Jörn Kohlhammer},

editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M. Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2014isvc-i.pdf, Paper as PDF},

doi = {10.1007/978-3-319-14364-4_84},

isbn = {978-3-319-14364-4},

year  = {2014},

date = {2014-12-08},

booktitle = {Advances in Visual Computing. ISVC 2014},

volume = {8888},

pages = {872--883},

publisher = {Springer International Publishing},

address = {Switzerland},

series = {Lecture Notes in Computer Science, vol 8888},

abstract = {Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictures and amplify cognition. Although the research on adaptive visualizations grew in the last years, the existing approaches do not consider the transformation pipeline from data to visual representation for a more efficient and effective adaptation. Further todays systems commonly require an initial training by experts from the field and are limited to adaptation based either on user behavior or on data characteristics. A combination of both is not proposed to our knowledge. This paper introduces an enhanced instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on content, visual layout, visual presentation, and visual interface. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonical requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling.},

keywords = {Application Scenario, Information Visualization, User Model, Visual Representation, Visual Search},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2014b,

title = {Adaptive Visualization of Social Media Data for Policy Modeling},

author = {Kawa Nazemi and Dirk Burkhardt and Wilhelm Retz and Jörn Kohlhammer},

editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M. Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2014isvc-ii.pdf, Paper as PDF},

doi = {10.1007/978-3-319-14249-4_32},

isbn = {978-3-319-14249-4},

year  = {2014},

date = {2014-12-08},

booktitle = {Advances in Visual Computing. ISVC 2014},

volume = {8887},

pages = {333--344},

publisher = {Springer International Publishing},

address = {Switzerland},

series = {Lecture Notes in Computer Science, vol 8887},

abstract = {The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens' demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process.},

keywords = {Information Visualization, Policy Modeling, Search Paradigm, Social Media Data, Visual Variable},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2014,

title = {Visualization Adaptation Based on Environmental Influencing Factors},

author = {Dirk Burkhardt and Kawa Nazemi and Jose Daniel Encarnacao and Wilhelm Retz and Jörn Kohlhammer},

editor = {Masaaki Kurosu},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2014hcii.pdf, Paper as PDF

http://2014.hci.international, Conference Site},

doi = {10.1007/978-3-319-07233-3_38},

isbn = {978-3-319-07233-3},

year  = {2014},

date = {2014-01-01},

booktitle = {Human-Computer Interaction. Theories, Methods, and Tools. HCI 2014},

volume = {8510},

pages = {411--422},

publisher = {Springer International Publishing},

address = {Switzerland},

series = {Lecture Notes in Computer Science, vol 8510},

abstract = {Working effectively with computer-based devices is challenging, especially under mobile conditions, due to the various environmental influences. In this paper a visualization adaptation approach is described, to support the user under discriminatory environmental conditions. For this purpose, a context model for environmental influencing factors is being defined. Based on this context model, an approach to adapt visualizations in regards of certain environmental influences is being evolved, such as the light intensity, air quality, or heavy vibrations.},

keywords = {Adaptive Visualization, Information Visualization, Sensor Fusion, User Experience, User-Centered Interaction},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2012b,

title = {Towards Process-Oriented Information Visualization For Supporting Users},

author = {Dirk Burkhardt and Tobias Ruppert and Kawa Nazemi},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2012icl-i.pdf, Paper as PDF

http://www.icl-conference.org/icl2012/, Conference Site},

doi = {10.1109/ICL.2012.6402080},

isbn = {978-1-4673-2427-4},

year  = {2012},

date = {2012-09-26},

booktitle = {Proceedings of 15th International Conference on Interactive Collaborative Learning (ICL 2012)},

pages = {1-8},

publisher = {IEEE },

address = {Piscataway, NJ, USA},

series = {15},

abstract = {Nowadays daily office work consists of dealing with big numbers of data and data sources, and furthermore of working with complex computer programs. In consequence many users have problems to use such programs effective and efficient. In particular beginners have significant problems to use the programs correctly due to complex functionality and interaction options. To avoid this overload of the user, the Information Visualization community has recently developed some approaches that aim to support the users. Unfortunately, these approaches are limited to one special aspect, and sometimes they are just appropriate for one special task. Thus, in this paper we introduce a process-oriented user-supporting approach. It allows selecting adequate supporting techniques in correlation to a performed process and activity to guide the user and help him to solve his task. Furthermore, we show the benefits of designing programs and applications, which implement process definitions for the existing tasks to provide the user with better process orientation. This guides the user through difficult and complex processes.},

keywords = {Information Visualization, Process  Management, Process Adaptation, Process Support, Process-oriented Information Visualization, User-Centered Interaction},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Stab2012,

title = {Semantics Visualization for Fostering Search Result Comprehension},

author = {Christian Stab and Kawa Nazemi and Matthias Breyer and Dirk Burkhardt and Jörn Kohlhammer},

editor = {Elena Simperl and Philipp Cimiano and Axel Polleres and Oscar Corcho and Valentina Presutti},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2012eswc.pdf, Paper as PDF

http://2012.eswc-conferences.org, Conference Site},

doi = {10.1007/978-3-642-30284-8_49},

isbn = {978-3-642-30284-8},

year  = {2012},

date = {2012-05-27},

booktitle = {The Semantic Web: Research and Applications; Research and Applications. ESWC 2012},

volume = {7295},

pages = {633--646},

publisher = {Springer},

address = {Berlin, Heidelberg, Germany},

series = {Lecture Notes in Computer Science, vol 7295},

abstract = {Current search engines present search results in an ordered list even if semantic technologies are used for analyzing user queries and the document contents. The semantic information that is used during the search result generation mostly remains hidden from the user although it significantly supports users in understanding why search results are considered as relevant for their individual query. The approach presented in this paper utilizes visualization techniques for offering visual feedback about the reasons the results were retrieved. It represents the semantic neighborhood of search results, the relations between results and query terms as well as the relevance of search results and the semantic interpretation of query terms for fostering search result comprehension. It also provides visual feedback for query enhancement. Therefore, not only the search results are visualized but also further information that occurs during the search processing is used to improve the visual presentation and to offer more transparency in search result generation. The results of an evaluation in a real application scenario show that the presented approach considerably supports users in assessment and decision-making tasks and alleviates information seeking in digital semantic knowledge bases.},

keywords = {Information Visualization, Search User Interface, Semantic Search, SemaVis, Visual Query Enhancement},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2018,

title = {Intelligent Exploration System - An Approach for User-Centered Exploratory Learning},

author = {Kawa Nazemi and Matthias Breyer and Christian Stab and Dirk Burkhardt and Dieter W. Fellner},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2011openclassroom-ii.pdf, Paper as PDF},

doi = {10.5281/zenodo.3455885},

isbn = { 978-960-473-323-1},

year  = {2011},

date = {2011-10-30},

booktitle = {Proceedings of Workshop of the EDEN Open Classroom 2011 Conference: Lifelong Learning in RURAL and Remote Areas},

pages = {71--83},

publisher = {Pallini},

address = {Athens, Greece},

abstract = {The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment.},

keywords = {Information Visualization, Intelligent Tutoring Systems, Knowledge Discovery, Knowledge Exploration},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Stab2011,

title = {Interacting with Semantics and Time},

author = {Christian Stab and Kawa Nazemi and Matthias Breyer and Dirk Burkhardt and Arjan Kuijper},

editor = {Julie A. Jacko},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2011hcii-viii.pdf, Paper as PDF

http://2011.hci.international/, Conference Site},

doi = {10.1007/978-3-642-21619-0_64},

isbn = {978-3-642-21619-0},

year  = {2011},

date = {2011-07-09},

booktitle = {Human-Computer Interaction. Users and Applications},

volume = {6764},

pages = {520--529},

publisher = {Springer},

address = {Berlin, Heidelberg, Germany},

series = {Lecture Notes in Computer Science, vol 6764},

abstract = {Time appears in many different semantic information systems like historical databases, multimedia systems or social communities as a common attribute. Beside the temporal information, the resources in these domains are categorized in a domain-specific schema and interconnected by semantic relations. Nevertheless, the high potential of these systems is not yet exhausted completely. Even today most of these knowledge systems present time-dependent semantic knowledge in textual form, what makes it difficult for the average user to understand temporal structures and dependencies. For bridging this gap between human and computer and for simplifying the exploration of time-dependent semantic knowledge, we developed a new interactive timeline visualization called SemaTime. The new designed temporal navigation concept offers an intuitive way for exploring and filtering time-depended resources. Additionally SemaTime offers navigation and visual filtering methods on the conceptual layer of the domain and is able to depict semantic relations. In this paper we describe the conceptual design of SemaTime and illustrate its application potentials in semantic search environments.},

keywords = {Information Visualization, Semantic Search, Semantic Visualization, Time-Dependent Ontology, Timeline Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2011b,

title = {SemaZoom: Semantics Exploration by Using a Layer-Based Focus and Context Metaphor},

author = {Dirk Burkhardt and Kawa Nazemi and Matthias Breyer and Christian Stab and Arjan Kuijper},

editor = {Masaaki Kurosu},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2011hcii-iii.pdf, Paper as PDF

http://2011.hci.international/, Conference Site},

doi = {10.1007/978-3-642-21753-1_55},

isbn = {978-3-642-21753-1},

year  = {2011},

date = {2011-07-09},

booktitle = {Human Centered Design},

volume = {6776},

pages = {491--499},

publisher = {Springer},

address = {Berlin, Heidelberg, Germany},

series = {Lecture Notes in Computer Science, vol 6776},

abstract = {The Semantic Web is a powerful technology for organizing the data in our information based society. The collection and organization of information is an important step for showing important information to interested people. But the usage of such semantic-based data sources depends on effective and efficient information visualizations. Currently different kinds of visualizations in general and visualization metaphors do exist. Many of them are also applied for semantic data source, but often they are designed for semantic web experts and neglecting the normal user and his perception of an easy useable visualization. This kind of user needs less information, but rather a reduced qualitative view on the data. These two aspects of large amount of existing data and one for normal users easy to understand visualization is often not reconcilable. In this paper we create a concept for a visualization to show a bigger set of information to such normal users without overstraining them, because of layer-based data visualization, next to an integration of a Focus and Context metaphor.},

keywords = {Human-Computer-Interfaces, Information Visualization, Semantic Web, Semantics Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}