Hamburg, the gateway to the future: the IT Planning Council recently met in the Hanseatic city’s venerable town hall to clarify pressing issues relating to the digital transformation.
The Hanseatic city, which is setting standards with its mobility turnaround and innovative strength, provided the perfect setting for this intensive exchange.
But how can a common digital future be created in a federal system with different data silos?
The work of the IT Planning Council shows: Digitalization is not a sure-fire success, but a balancing act between technical innovations, legal requirements and federal diversity. However, the determination of the players to set clear standards and break new ground gives hope for a future-proof administration.
Representatives from the federal government, federal states, local authorities and experts from various disciplines came together to discuss the progress and challenges of data-related administrative work.
Thanks to the Hamburg Transparency Act, the event was broadcast publicly via livestream.
Digital transformation: from visions to concrete solutions
The focus was on data governance, interoperability and future viability through the use of artificial intelligence (AI).
- Interfederal data exchange: development of uniform standards and regulations.
- Cooperation between public and private players: use of existing data resources for joint projects.
- Future-oriented applications: Use of modern technologies such as AI and geodata for specific solutions.
Annual review 2024 – Source: IT Planning Council
Hamburg on course for the future: mobility transition, energy transformation and digitalization in harmony
With its digital approaches, the IT Planning Council also provides impetus for intelligent mobility solutions, which are optimally complemented by Hamburg’s clear focus on sustainability and digitalization.
With over half a billion euros in federal and EU funding, Hamburg is demonstrating a clear commitment to the mobility transition and investing specifically in sustainable, digital and future-oriented transport services.
This is not the only reason why I feel completely at home in Hamburg.
Digitization of administration: success through clear standards and high-quality data
The atmosphere was characterized by ambitious goals and a clear insight: the digitalization of administration stands and falls with the standards used and the quality and availability of data.
How the next federal government can strategically drive change
Digitalization is a key federal policy priority, but has only been partially implemented in practice to date. For the next government, it is important to prepare the relevant topics at an early stage and introduce them strategically in order to ensure continuity and progress.
But how can these demands be reconciled with the federal structures?
The path to data-based management
The central aim of the IT Planning Council is to make data-related processes within the administration more efficient, transparent and secure.
Two main directions were formulated:
- Promoting discourse on data-related topics and providing impetus.
- Creating synergies and developing concrete products.
This vision is underpinned by projects that offer both short-term impetus and long-term solutions.
Digital twins and the role of data protection in data-based management
A central component of the data-based administrative work is the 2021 cooperation project on digital twinswhich is being developed in collaboration with Leipzig and Munich. With the support of the federal government, the project aims to create compatible modelsthat can be used nationwide.
Data as a strategic asset – competitiveness and data-based acceleration
These models should not only speed up and simplify planning and approval procedures, but also enable the use of large data sets and modeling to avoid the need for separate expert reports.
However, the challenge remains to convince political and administrative players of the long-term benefits of these approaches.
Early involvement of the data protection officer: data protection in focus
Data protection also plays a central role in data-based administration. At the most recent conference of digital ministers, the exchange with the new Federal Data Protection Commissioner was intensified in order to promote a uniform federal approach.
Hamburg is leading the way here by involving the data protection officer in the digitalization steering group at an early stage. This model of constructive cooperation makes it possible to design AI systems in compliance with data protection regulations by working together on technological and legal issues.
With projects like these, the IT Planning Council shows how technological innovation and legal responsibility can go hand in hand – an important step towards modern and trustworthy administration.
Insights into concrete progress
1. the data map: a “point of truth” for data
One highlight is the “Data map” project. The aim is to create an overview of data stocks and their use. The aim is not only to make data stocks visible, but also to analyze their use in various administrative areas.
This was illustrated using examples from Hamburg: key figures such as annual school costs or fire department deployment times appear in various reports, but it remains unclear whether the same data is being used. The data map is intended to create clarity here and promote consistent data usage.
2. high value datasets and action guidelines
The impulse paper High Value Datasets was developed against the background of legal requirements. This offers authorities practical support in the provision of data and shows how it can be used effectively.
The Data Governance Action Guide, one of the team’s first products, has already been very well received. It offers municipalities and federal states orientation in an often misunderstood topic that is essential for the digital transformation.
3. preparation for the AI Regulation
Another key topic was preparing for the upcoming EU AI Regulation. A testing scheme was developed that administrations can use to classify AI applications and assess their risks. In addition, there are guidelines for the introduction of AI governance that enable legal requirements to be met efficiently.
These tools are not only important for administration, but also a step towards the trustworthy use of AI.
Challenges along the way
Despite these successes, the road ahead remains rocky. Data governance is still in need of explanation and is not clearly defined in many administrations. Responsibilities are often unclear and the federal structures make it difficult to harmonize standards.
Another problem is the lack of interoperability. Different data collections and standards lead to silos that hinder the exchange between authorities. Semantic interoperability is seen as the key to breaking down these barriers.
Interoperability
- Need for uniform standards and automated retrievals.
- Focus on information security and cross-federal cooperation.
- Link with European perspectives to maximize benefits.
Standards and governance
- Clarification of responsibilities: Who is responsible for data quality and retrieval? Which data is required and who is authorized to use it?
- Development of central structures for data models and processes without taking responsibility away from specialist departments.
- Harmonization of register structures and definitions while maintaining decentralization.
- Focus on metadata: Introduction of data catalogs and metadata platforms to make existing data visible and accessible. Goal: Increased efficiency through the reuse of existing data.
- Balance between central governance and decentralized responsibility. Close cooperation with specialist ministries required.
- Integration of the user perspective (citizens and administration).
Data culture and transparency
Promotion of data literacy:
- Legislative bodies and specialist departments need training to understand and design data structures and models.
- Linking data management with change management and cultural change.
Transparency and open data:
- Mandatory provision of publicly funded data via transparency laws and platforms such as urban data platforms.
- Clear rules for delimiting sensitive data (e.g. police data).
Federal digital strategy
- Linking the five key topics (data protection, AI, data governance, register modernization, data use) with an overarching framework.
- Goal: Concrete products and processes instead of pure theory.
- Success model through joint work and igniting initiatives.
- National-Once-Only-Technical-System (NOOTS)
Technology and infrastructure
- Development of an information technology infrastructure for the interdepartmental exchange of verification data through the NOTS system (Once-Only-Technical-System).
- Challenges: Silo structures from 40 years of administrative digitization, development of uniform data governance and standardization, integration of federal and local self-government into the digital infrastructure.
Practical examples
- Data-based building applications: Use of data to optimize construction processes (e.g. resource planning and traffic management).
- LLMoin (AI in Hamburg): Example of a pragmatic approach: With the launch of the AI solution, benefits have already been generated before all the details have been finalized.
AI competence team – IT Planning Council – Source: IT Planning Council
A look ahead: plans for 2025
The IT Planning Council’s competence team has outlined a clear roadmap for 2025:
- Expansion of the data map: creation of a central access point for register-relevant data that can be used federally.
- Focus on the data lifecycle: integration of data governance solutions in all phases of data management.
- AI and interoperability: Promotion of technical standards and development of further guidelines to support administrations in the use of AI.
Semantic interoperability
Semantic interoperability describes the ability to exchange data between systems and organizations in such a way that their meaning is uniformly understood.
This is essential to ensure technical interoperability, which can vary greatly due to different laws and definitions at federal, state and local level.
Challenges in federal data exchange
The exchange of data between the federal government, federal states and local authorities is made considerably more difficult by different data definitions, collection methods and legal bases. Local interpretations of laws lead to inconsistencies, particularly in municipalities and territorial states, which hinder the uniform use and processing of data. This fragmentation not only undermines the efficiency of administration, but also makes it difficult to create interoperable systems.
Solution approaches for a standardized data landscape
In order to meet these challenges, federally coordinated semantic standards are to be developed that create clear guidelines for data usage. In addition, the introduction of mechanisms is planned to harmonize semantic differences in existing and new projects. A central component is the digital check, which systematically checks the data and process interoperability of new laws and projects. These measures aim to establish a coherent and efficient data landscape that respects federal structures and modernizes them at the same time.
The anchoring of the federal digital strategy, which forms the framework for these projects, will be particularly exciting.
Process diagrams and data models as standard in draft legislation
In order to make legal requirements clearer and more comprehensible, every draft bill should contain a mandatory process diagram and data model. These visualizations create transparency about how data is used and processed within the framework of a law and enable more precise implementation in the administration.
However, the introduction of such standards poses challenges: There is currently a lack of uniform specifications for the integration of process images and data models into the legislative process, and the creation and adaptation of such models is often complex and resource-intensive.
The provision of central platforms that make it possible to flexibly create and adapt process images and data models could serve as a solution. In addition, non-functional requirements should be defined in order to efficiently implement changes to processes and models.
The advantages are crystal clear: inconsistencies in the implementation of legislation are reduced and the administration can more easily understand and adapt legal requirements, which contributes to greater efficiency in the long term.
Conclusion: A balancing act between vision and reality
The work of the IT Planning Council impressively demonstrates how complex, but also how necessary, data-based administrative work is. With projects such as the data map, action guidelines and AI tools, the team is providing important impetus.
The IT Planning Council is striving for greater centralization and standardization of identification solutions in order to increase efficiency and user-friendliness in the administration. A standardized identification solution, such as the Bund-ID, is to be used in future not only for public administration processes, but also for sector-specific areas such as statutory health insurance (SHI). The aim is to avoid redundancies in identification systems and make it easier for citizens to access administrative services.
The IT Planning Council relies on central guidelines and structures that are to be provided by institutions such as the FITKO. These guidelines are intended to promote standards and best practices in order to ensure the smooth integration of the federal ID into all administrative areas. It is also emphasized that implementation depends on clear leadership at the highest political level, especially from prime ministers and department heads. The demand is to avoid parallel developments and to create clear guidelines for the use of the federal ID.
My view of the IT Planning Council’s proposals
The desired standardization and centralization is understandable for reasons of efficiency, but it does pose some challenges and risks. The idea of establishing the federal ID as a central identification solution is technically and politically ambitious. However, the discussion often neglects the necessary flexibility for sector-specific requirements, such as those required by the SHI system or other institutions.
A blanket introduction of the federal ID could unsettle citizens, as it may be perceived as a central data repository, which is problematic in terms of data protection and technology. So far, there has been a lack of greater consideration of modern technologies such as zero-knowledge evidence or selective disclosure, which is firmly provided for in the EUDI wallet and would allow only relevant attributes to be shared selectively and anonymously. Such technologies could not only strengthen citizens’ trust, but also better meet the requirements of the General Data Protection Regulation (GDPR).
In my opinion, the focus on central guidelines and specifications also falls short. Such guidelines must be more than theoretical instructions – they should include practical implementation strategies and pilot projects that take into account sector-specific requirements such as social insurance. In my view, there is a lack of differentiated consideration of how federal structures and sector-specific characteristics can be harmonized.
The proposed measures have far-reaching implications for the IT architecture of our administration. As was also made clear in the discussion round, complete standardization always entails the risk that sector-specific requirements will be overlooked, which could lead to inefficient solutions and additional adaptation costs in the long term. There is also a risk that citizens will lose trust in such centralized systems if data protection concerns are not seriously addressed.
From my perspective, a practicable way forward is a modular, federated architecture that enables basic compatibility between federal ID and sector-specific solutions such as a health ID. Technologies such as zero-knowledge evidence or selective disclosure would serve as a bridge in data transfer to ensure interoperability while maintaining the respective data protection levels. This would allow us to reap the benefits of trusted identification solutions without losing sector-specific flexibility.
In addition, pilot projects should be carried out with selected administrative sectors to test the practicability and acceptance of the federal ID. Other sectors – including the telematics infrastructure – should also be taken into account.
The IT Planning Council should focus on cooperative approaches in order to integrate the perspectives and needs of citizens and institutions at an early stage.
The IT Planning Council’s approach to standardizing identification systems is a step in the right direction towards more efficient administrative processes. Nevertheless, implementation should take greater account of the technical possibilities of modern identity solutions and the specific requirements of individual sectors. Only through the use of flexible technologies and participatory development can a uniform solution be created that is not only efficient, but also data protection-friendly and trustworthy.
Success will therefore depend on how well federal hurdles can be overcome and a common data culture established.
It is foreseeable that this digital transformation is a large-scale project that will take several years to complete. It is therefore all the more pleasing that the importance of prototypical, iterative approaches and minimum viable products (MVPs) are firmly anchored in the process.
Involving citizens and obtaining validated feedback are essential building blocks to ensure that our digital solutions are not only technically innovative, but also practical and needs-oriented.
This approach creates room for flexibility, continuous learning and fast results – a decisive advantage in such a complex and dynamic project.
I invite you to share your perspectives and experiences – let’s create a digital infrastructure together that is trustworthy, efficient, sustainable and secure.
#together
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