Data-driven Solutions for the Smart City Hamburg (D²S²C)

• Type of event: Seminars
• Institution: Faculty of Mathematics, Informatics and Natural Sciences
• Funding period: 01.04.2022 to 31.03.2023
• Short title: D²S²C

Extract from the funding application: "Due to the ongoing digitalisation of all areas of life, the demands on citizens to find their way independently in a rapidly changing world permeated by information have increased."

The Smart City Hamburg project

In the "Data-driven Solutions for the Smart City Hamburg (D²S²C)" project, students analyse real-life challenges in the smart city sector as part of the course and develop prototype solutions. To this end, they are working together with HOCHBAHN, HSV/Future Dock and the State Office for Geoinformation and Surveying, thus facilitating a transfer between theory and practice.

The "Smart City" concept describes the development and networking of countless stakeholders in an intelligent and innovative city in a multi-layered way, in which the aim is to create a community with a high quality of life and sustainable use of resources. In the course, students worked with various methods from the fields of requirement engineering, project management, business intelligence, process management, data science and artificial intelligence. These were used by the students to develop practicable solutions in cooperation with the organisations and companies. This included the analysis and visualisation of data and processes in order to generate information and knowledge. In addition, the use of artificial intelligence can also enable predictions and thus automation, so that work steps can be omitted or operational optimisations made possible.

Review and results

A hybrid and innovative learning and teaching environment was successfully developed in the project and then tested and further developed over the course of two semesters with two different groups of 17 and 12 students from over ten degree programmes. The concept was based on innovative technologies that were introduced and deepened, particularly at the beginning and in the first three weeks. These relate to methods of agile project management according to Scrum, iterative software development, data science and machine learning as well as aspects of group organisation and supporting tools. The intensive group and development phase then began. At the beginning of this phase, the real use cases of the partner companies and organisations were discussed and concretised in order to gain a deep understanding of the domain and the problems and challenges and to specify the need for a solution. This was pursued in the form of prototypes, which were developed and regularly evaluated by the students in groups and using both provided and publicly available data.

The project has promoted data literacy education in relation to different working methods and complements the MIN faculty's programme with a practical format that motivates students to develop innovative solutions. In addition, a profitable networking with external partners took place. This distinguishes the format from existing and theoretical programmes, on which it builds directly and whose content is deepened through application. In addition to promoting data literacy, problem-based learning, user-centred development, critical thinking, group work and the agile development of solutions, analytical skills and aspects of interdisciplinary and transdisciplinary collaboration were also promoted.

The analyses of the surveys and feedback from the students show that the seminar is of great interest and that the skills are successfully taught. This applies in particular to data literacy and problem-based work and the development of solutions. The partner companies and organisations are also impressed and interested in the format, as they are faced with complex challenges whose solutions are unclear. Data is usually available, both structured and unstructured, and can be utilised in different ways to generate information and ultimately knowledge for decision-making.

Tips from lecturers for lecturers

Teaching was carried out in hybrid mode and various technologies were tried out over the semesters in order to find optimal ways to support both organisation and teaching. The experience gained made an important contribution to the continuation of the programme, as compatibility with external systems is important in order to interlink tools. It also became clear that on-site appointments fulfil an important non-functional task, especially at the beginning and in between. This gives students and teachers a better impression of each other and makes it easier for them to exchange information at a low threshold, which promotes the formation of a group as a unit and complements digital teaching. This has a positive effect on collaboration, exchange and reliability within the group of students.

Persons involved

Prof. Dr. Eva Bittner

Leader of the Research Group on Information Systems, esp. Socio-Technical Systems Design (WISTS)

Focal points:

• Collaboration Engineering
• Human-Machine Collaboration
• Hybrid Intelligence
• Knowledge Work and Knowledge Management
• IT Innovation Management and Co-Creation/Social Innovation

Contact

Marten Borchers

Research assistant in the Business Informatics, Socio-Technical System Design working group

Main research areas:

• Smart City
• Smart Mobility
• Participation and artificial intelligence

Activities:

• Design of human-computer/AI interactions
• Prototyping and development of intelligent systems and machine learning models

Contact