TUHH: WG2

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WG 2 – Architecture & Technical Platform

What is it about?

Artificial intelligence can support studying, teaching, research and administration at Hamburg University of Technology in many ways. To ensure that AI applications can be used securely, reliably and sustainably, suitable technical infrastructure is required. The WG 2 therefore develops a scalable, secure and future-proof architecture for AI-based applications at Hamburg University of Technology.

The focus is on technical platforms, interfaces, operating models, and requirements for data protection, information security, availability and user-friendliness. The objective is a technical foundation that enables the responsible use of AI while remaining flexible enough to accommodate future developments.

If you have any questions or are interested, please contact Julien Wegner, Data Centre, at: julien.wegner(at)tuhh(dot)de

Objectives & Approach

The architecture is developed step by step and in close coordination with stakeholders from IT, teaching, research, administration and the other Working Groups. Technical requirements are identified at an early stage and transferred into a viable platform and operating concept.

Existing systems and processes are taken into account to avoid duplicate structures and to enable the smoothest possible integration into the IT landscape of Hamburg University of Technology; new requirements arising from the use of AI are systematically incorporated into the architecture planning. WG 2 proceeds through four consecutive phases:

Phase 1: Requirements Analysis and Stocktaking

Identify existing IT systems, platforms and interfaces
Collect and review technical, organizational and legal requirements
Identify needs from studying, teaching, research and administration
Analyze relevant AI application scenarios

Phase 2: Establishment of an Experimentation and Test Environment

Procure and set up initial hardware infrastructure
Select and provide suitable AI tools and platform components
Conduct initial technical tests with selected application scenarios

Phase 3: Development of Prototypes

Support the Working Groups in developing prototypes for selected use cases
Define interfaces to existing systems
Take roles, permissions and access concepts into account
Analyze performance, scalability and resource requirements
Derive requirements for a future production platform architecture

Phase 4: Rollout and Further Development

Provide the platform step by step
Inform and involve user groups
Establish technical support services
Evaluate experience from use

Current: Establishment of an Experimentation and Test Environment

The current focus is on establishing a technical foundation on which AI applications, platform components and potential integration scenarios can initially be tested in a protected environment.

A central part of this phase is the procurement and commissioning of initial hardware infrastructure. This creates the prerequisites for testing AI applications under controlled conditions, verifying technical requirements and gaining initial experience with operation, performance, scalability and resource requirements.