Motivation & Background

The "Knowledge4Retail" project is a winning project of the "Künstliche Intelligenz als Treiber für volkswirtschaftlich relevante Ökosysteme" programme funded by the Bundesministerium für Wirtschaft und Klimaschutz (BMWK). 

The project is motivated by the fact that little data is available on the movement of products or the customer interaction with a product in a store. However, the availability of such data would enable new services, e.g., the optimization of store layouts, the support of store employees, and an augmented shopping experience for customers. 

Thus, the goal of the Knowledge4Retail project is the design and implementation of a data platform providing standardized data formats, interfaces, and solutions as a basis for AI-supported services. The platform is based on semantic digital twins - digital models of real shops that combine different data of a retail outlet. The project will develop a data format for the digital representation of the structure and processes of retail stores. The innovative aspect of this project is that the data is not only collected but also linked semantically. For example, the digital twin can link data from a store's ERP system, sensors in the store, the digital product catalogue, but also geodata or weather data. 

The Knowledge4Retail project additionally designs and implements four prototypical applications based on the developed data model. These prototypes comprise intelligent intralogistics, strategic retail marketing for the establishment of customer-specific branches, service robotics for the support of store employees, and the Internet of Things (IoT) connection of an intelligent refrigerator. 

As part of the K4R project, the sebis chair is responsible for the analysis, development and consolidation of the Knowledge4Retail ecosystem. The goal of the ecosystem analysis is to identify relevant partners and their pains, which could be addressed by the Knowledge4Retail platform and thus to enable the platform to be used beyond the duration of the project. 

More information about the project can be found here. 

 

Work on ecosystems and Knowledge4Retail

2022

Schopf, Tim; Dresse, Kilian; Matthes, Florian Towards AI Platforms for Stationary Retail 5th International Conference on Artificial Intelligence for Industries (AI4I), Laguna Hills, USA, 2022

2019

Faber, Anne; Riemhofer, Maximilian; Huth, Dominik; Matthes, Florian Visualizing Business Ecosystems: Results of a Systematic Mapping Study Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS, Crete, 2019

Faber, Anne; Matthes, Florian; Rehm, Sven-Volker; Goel, Lakshmi Tool-Supported Collaborative Modeling and Visualizations of Business Ecosystems 7th Collective Intelligence, Carnegie Mellon University, Pittsburgh, USA [tbp]

Faber, Anne; Riemhofer, Maximilian; Rehm, Sven-Volker; Bondel, Gloria A Systematic Mapping Study on Business Ecosystem Types 25th Americas Conference on Information Systems - New Frontiers in Digital Convergence (AMCIS) [tbp]

2018

Faber, Anne; Rehm, Sven-Volker; Hernandez-Mendez, Adrian; Matthes, Florian Modeling and Visualizing Smart City Mobility Business Ecosystems: Insights from a Case Study Information 2018, 9(11), 270; doi.org/10.3390/info9110270

Faber, Anne; Hernandez-Mendez, Adrian; Sven-Volker Rehm; Matthes, Florian Visualizing Business Ecosystems: Applying a Collaborative Modelling Process in Two Case Studies 29th Australasian Conference on Information Systems (ACIS), Sydney, Australia, 2018

Braun, Daniel; Faber, Anne; Hernandez Mendez, Adrian; Matthes, Florian Automatic Relation Extraction for Building Smart City Ecosystems using Dependency Parsing 2nd Workshop on Natural Language for Artificial Intelligence

Faber, Anne; Riemhofer, Maximilian; Hernandez-Mendez, Adrian; Matthes, Florian Visualizing an Emerging Mobility Business Ecosystem 5th Internation IEEE Congress on Information Science and Technology (CiSt 2018), Marrakech, Morocco, 2018

Hernandez-Mendez, Adrian; Faber, Anne; Bondel, Gloria; Matthes, Florian Towards an Ontology-Based Information System for Smart City Ecosystems Proceedings of the 24th Americas Conference on Information Systems, New Orleans, 2018

Faber, Anne; Hernandez-Mendez, Adrian; Rehm, Sven-Volker; Matthes, Florian An Agile Framework for Modeling Smart City Business Ecosystems Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS, Funchal, Madeira, Portugal, 2018

Faber, Anne; Huth, Dominik; Matthes, Florian State-of-the-practice in analyzing enterprises' business ecosystems Multikonferenz Wirtschaftsinformatik (MKWI) 2018, Band 2

2017

Rehm, Sven-Volker; Faber, Anne; Goel, Lakshmi Visualizing Platform Hubs of Smart City Mobility Business Ecosystems Thirty Eighth International Conference on Information Systems (ICIS), Seoul, South Korea, 2017

Faber, Anne Towards a Visual Language Approach for Modeling Business Ecosystems Proceedings of the Doctoral Consortium and Industry Track Papers presented at the 10th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modelling (PoEM), Leuven, Belgium, 2017

Hernandez-Mendez, Adrian; Faber, Anne; Matthes, Florian Towards a Data Science Environment for Modeling Business Ecosystems: The Connected Mobility Case.  Proceedings of the 21 Databases and Information Systems (ADBIS) - 1st International Workshop on Data Science: Methodologies and Use-Cases (DaS) 2017

Amini, S.; Beckers, K.; Böhm, M.; Busch, F.; Celikkaya, N.; Cozzolino V.; Faber, A.; Haus, M.; Huth, D.; Kemper, A.; Kipf, A.;  Krcmar H.; Matthes, F.; Ott, J.; Prehofer, C.; Pretschner, A.; Uludağ Ö.; Wörndl, W. Informatikforschung für digitale Mobilitätsplattformen: Am Beispiel des TUM Living Lab Connected Mobility, Informatik-Spektrum (40):2, pages 180-191, 2017.

Faber, Anne; Hernandez-Mendez, Adrian; Matthes, Florian Towards an Understanding of the Connected Mobility Ecosystem from a German Perspective.  Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS) - 1st International Workshop on Advanced Enterprise Modelling (AEM) 2017