Scientific Publications

2019
2.		Burkhardt, Dirk; Nazemi, Kawa; Kuijper, Arjan; Ginters, Egils A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts Proceedings Article In: 5th International Conference of the Virtual and Augmented Reality in Education (VARE2019), pp. 11–19, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6, (Nominated for Best Paper Award). Abstract \| Links \| BibTeX \| Tags: Business Analytics, Decision Support Systems, Human-Computer Interaction, Information Visualization, Mobile Devices, Mobile Visual Analytics, Visual Trend Analysis @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} } Close 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. Close Dowload as PDF doi: 10.5281/zenodo.3473041 Close
2018
1.		Burkhardt, Dirk; Nazemi, Kawa Visualizing Law - A Norm-Graph Visualization Approach based on Semantic Legal Data Proceedings Article In: 4th International Conference of the Virtual and Augmented Reality in Education (VARE 2018), pp. 154-162, CAL-TEK SRL, Rende, Italy, 2018, ISBN: 978-1-5108-7222-6. Abstract \| Links \| BibTeX \| Tags: Decision Support Systems, e-Government, Information Visualization, Law Visualization, Norm-graph, Policy Modeling, Semantic Data @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} } Close 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. Close Paper as PDF Link to Publisher doi:10.5281/zenodo.2543729 Close