Ongoing Projects

Data-driven exploration and explanation of ethics cases in business world

Beginn: since 2021.09

Contact: Chuan Chen / Mengyi Wei

This project funded by industry partner addresses the ethical issues in business world from a data scientific perspective. The ethics cases in big data are mainly reflected in narratives of conflicts, negotiation contents, trial processes and results, professional comments, public opinions, analytical judgments, and constantly updated lists of "should do" and "should not do". However, without AI support, the human brain alone cannot see through the intricate and varying strengths and weaknesses of connections among the elements of a case or among different cases. In this project we attempt to develop an interactive visual analytical platform that can combine the data-driven deep learning ability with knowledge-driven human's reasoning and interpretation ability. The platform will enable us to perform tasks along a value chain such as automatic collection of ethics cases from the globally accessible public media and social media, analysis and clustering of collected data, creation of a specific ontology and knowledge graph, and visual explanation of the knowledge graph. Being driven by big data, the platform may serve the general objectives for different stakeholders in the business world.

Semantic Data Mining for OSM Building Layer

Beginn: since 2022.04

 Contact: Leul Kahsay

One of the fundamental supporting technologies of AR map is to build a complete, accurate, consistent and up-to-date 3D city model dataset. The future success of the AR map application relies on the capability of extending its coverage to city-level and even larger areas. For the moment, the major data sources for the ultimate experience areas include LiDAR point clouds, aerial imagery and panoramic images. The data collection is costly and requires large amount of manual work. While for the city-level 3D model construction, one of the approaches is the use of stereo satellite imagery. This method is able to provide the global coverage, but has a relatively long repetition cycle (more than three years) and is severely affected by weather conditions. Besides, its cost per square kilometer is also higher than for normal satellite imagery because it has to be in stereo. This project funded by industry partner addresses the scalability of single-scene SAR imagery and VGI building footprints; and the comprehensibility of historical building attribute data and land use data for the creation of 3D city models.

A climate event portal for knowledge discovery

Contact: Liqiu Meng, Andreas Divanis

Partners: Bayerische Klimaforschungsnetzwerk (BayKlif): Prof. Dr. Annette Menzel, Technische Universität München, Prof. Dr. Dieter Kranzlmüller, Leibniz-Rechenzentrum, Prof. Dr. Susanne Jochner-Oette, Katholische Universität Eichstätt-Ingolstadt, Prof. Dr. Jörg Ewald, Hochschule Weihenstephan-Triesdorf, Prof. Dr. Wolfgang W. Weisser, Technische Universität München, Prof. Dr. Ulrike Ohl, Universität Augsburg, Prof. Dr. Arne Dittmer, Universität Regensburg, Prof. Dr. Henrike Rau, Ludwig-Maximilians-Universität München

The PhD or post doc researcher will be working with multidisciplinary teams in a Research Cluster on “Bavarian Synthesis Information Citizen Science Portal for Climate research and Scientific Communication” (BAYSICS - Bayerisches Synthese-Informations-Citizen Science Portal für Klimaforschung und Wissenschaftskommunikation).

Project webpage: https://www.bayklif.de/verbundprojekte/baysics/teilprojekt-3/

Geospatial Information Services for Smart Cities Driven by Big Data

Contact: Edyta Bogucka, Linfang Ding

Partners: Yangtze River Delta Science Data Center, Changshu Fengfan Power Equipment Co., Ltd

Within this cooperation, Chair of Cartography TUM conducts a research on integrating multiple sources of geo-referenced urban data to derive valuable geospatial services for smart city applications. As a result, an open geo-collaborative portal with a set of interactive services will be developed. The portal will contain an interactive user interface, an extendable visualization toolkit and an analytical toolkit. The anticipated components will serve as descriptive, diagnostic, predictive and prescriptive tools for city management. The functionalities of the portal will be developed during the series of workshops and user tests with three target groups – urban citizens, domain experts and decision makers. Each target group will participate in the knowledge construction process in a two-fold role – as information receiver and data contributor.