Public Data and Industrial Data Opportunity Guide – Norway · BusinessNorway.ai

Introduction

Norway’s economy and society are undergoing a data‑driven transformation. As one of Europe’s most digitalised countries, Norway views data as a fuel for innovation, economic growth and high‑quality public services. The Norwegian Government’s 2024 white paper The Digital Norway of the Future defines a new data policy anchored in the principle that data should be open when possible and protected when necessary. It emphasises that public datasets must be accessible, usable and comparable with other data and that they should add value for both the public and private sectors. Norway also recognises that public data is a prerequisite for developing high‑quality artificial‑intelligence (AI) solutions. This guide synthesises Norway’s national data strategies, the legislative and institutional frameworks, and the opportunities for value creation through public and industrial data. It provides context, examples, edge cases and concrete actions for public agencies, researchers and businesses – especially foreign firms and small and medium‑sized enterprises (SMEs) – seeking to harness Norway’s data resources responsibly.

Norway’s digital and data policy landscape

“The Digital Norway of the Future” strategy

In March 2024 the Ministry of Digitalisation and Public Governance released the white paper The Digital Norway of the Future. It builds on earlier strategies such as the 2019 digitalisation strategy and the 2020 National Strategy for Artificial Intelligence (AI) to provide a comprehensive roadmap to 2030. The white paper sets out three overarching data principles:

Open when possible, protected when necessary. Public data should be shared openly by default, but personal data and sensitive information must be protected. The paper emphasises that data must be shared in a way that respects fundamental rights and Norwegian societal values. It recognises that agencies need to become better at using their own and others’ data to renew services and support AI development.
Accessible and usable. Data should be accessible, retrievable, and comparable so that different actors can combine datasets and create new services. The Digitalisation Circular requires every agency to have an overview of its data holdings and to register datasets at data.norge.no. The National Audit Office found that coordination of data sharing remains inadequate, so the strategy prioritises improving governance.
Value‑adding. Data must be shared and used in ways that generate value for businesses, the public sector and society at large. The Government plans to establish a national prioritisation council for data sharing to identify high‑value datasets and advise on strategic data investments. It will draw on international models like Ireland’s Open Data Governance Board.

The strategy acknowledges the importance of European alignment. Norway participates in the EU Digital programme and contributes to the development of European data spaces, particularly the European Health Data Space. It is preparing to implement the EU’s Open Data Directive, Data Governance Act and Data Act. These instruments will introduce new obligations around high‑value datasets, data intermediaries and fair access to non‑personal data. Norway also plans to follow up the 2024 Norwegian Official Report on data sharing (NOU 2024: 14 Med lov skal data deles) and adopt comprehensive legislation on the re‑use of public data.

National Strategy for Artificial Intelligence (2020)

The 2020 AI strategy provides further context. It identifies open public data as a foundation for AI development: virtually all information lawfully published on public websites can be made accessible as open data. Personal data exempt from disclosure must remain protected, but the Government urges agencies to share as much non‑personal data as possible to stimulate innovation. The AI strategy outlines sectors with high potential for data reuse – culture, research and education, public expenditure, transport and communications, and geodata – and notes that specific data‑sharing strategies exist for each. The Freedom of Information Act and the Digitalisation Circular require agencies to make machine‑readable data available and to publish data in the National Data Directory and on data.norge.no.

The AI strategy also highlights Nordic cooperation. The Nordic Council of Ministers has formed a working group to identify datasets that can be exchanged between Nordic countries and create added value for enterprises while respecting ethical norms. Norway is committed to exploring data sharing across borders and to leveraging European data spaces.

Principles for research, business and industrial data

Norway differentiates between public data, research data and business data. The AI strategy sets out three principles for publicly funded research data: research data should be as open as possible and as closed as necessary; data must be curated to maximise its value; and decisions about archiving and curation should be made within the research community. Publicly funded research is expected to benefit the entire society; thus, data should be accessible to other researchers and businesses, subject to data protection and intellectual‑property considerations. This aligns with international movements towards open science and FAIR (Findable, Accessible, Interoperable, Reusable) data.

For business data, the strategy notes that companies own their own data and decide how to use it within data protection laws. Yet many companies lack awareness of the value of data sharing and have poor data governance. The government provides examples of voluntary data sharing:

Diskos National Data Repository – a joint venture established by the Norwegian Petroleum Directorate and oil companies to pool exploration and extraction data from the continental shelf. Members can access this repository, promoting efficient exploration while allowing competition in interpretation. Diskos shows how industry‑level collaboration can produce a shared data infrastructure that reduces costs and accelerates innovation. The underlying legal framework defines membership rights, confidentiality obligations and costs.
Norway Digital and Geonorge – a cooperation programme between municipalities, counties, national agencies and private enterprises to share geospatial information. The platform geonorge.no provides open access to maps, property boundaries, meteorological data and more. Industry participants such as telecom and power companies benefit from common geodata standards, enabling integration across value chains.

The government encourages voluntary sharing, but acknowledges that data is sometimes too valuable to remain siloed. It sets four principles for data sharing from the business sector:

Voluntary sharing between parties with mutual interest is preferable.
Facilitated sharing of low‑value data. Authorities can help businesses share data that companies see no value in, if sharing benefits society.
Mandatory sharing in the public interest. Data may be required to be shared when it supports public interest or essential services.
Control and privacy. Data should be shared in ways that let individuals and businesses retain control and protect privacy.

The Government is considering imposing data‑sharing requirements as part of public contracts or licensing conditions in sectors such as fisheries, energy and telecommunications. This signals a shift from purely voluntary collaboration towards regulated data access where public benefit outweighs commercial secrecy.

Data infrastructure and tools

National Data Directory and data.norge.no

At the centre of Norway’s open data ecosystem is data.norge.no, the national portal for open public data. It hosts metadata about datasets from ministries, agencies, municipalities and other public bodies, and allows users to search for and download datasets. According to a 2025 article on the European Union’s data portal, data.norge.no stands out because of its AI‑powered search function that interprets natural language queries and returns relevant datasets. This semantic search helps non‑experts discover data without needing technical terminology. The portal also offers interactive features: the Data Hunter tool enables citizens to request the release of unpublished datasets, while discussion forums allow users to exchange ideas and provide feedback. By lowering entry barriers and promoting dialogue, the portal supports a more inclusive and transparent data ecosystem and aligns with EU open data priorities.

Agencies are required to register their datasets in the National Data Directory and data.norge.no, which ensures that metadata is publicly available and helps avoid duplicate data collection. The once‑only principle mandates that citizens and businesses supply information only once to the public sector, and that information is shared internally across agencies. To implement this, agencies must maintain accurate registries and share data in real time via application programming interfaces (APIs). The Brønnøysund Register Centre and the Norwegian Digitalisation Agency coordinate the development of registries such as the National Population Register and the Central Coordinating Register for Legal Entities. The National Data Directory offers information on dataset ownership, licensing terms and sharing restrictions. Public agencies are required to publish machine‑readable data through open APIs, enabling private developers to build applications.

The AI strategy proposes several methods to make data sharing simpler and safer:

Data lakes provide a central repository for storing raw data in various formats. They allow data analysts and AI developers to retrieve structured and unstructured data for training models and performing analyses.
Data trusts are legal structures in which a third party manages data sharing on behalf of the data owners. The trust decides who can access data and for what purpose, ensuring compliance with the agreed objectives.
Anonymisation interfaces, like the Remote Access Infrastructure for Register Data (RAIRD), enable researchers to run analyses on personal data without seeing identifiable information. RAIRD’s model is publicly available and can be replicated by other institutions.
Synthetic data can mimic the properties of real datasets while removing identifiers. The strategy notes that synthetic data allows sensitive datasets to be openly accessible for research and innovation.
Common open APIs allow real‑time access to data sources and are essential for AI applications requiring up‑to‑date information.

The strategy encourages the adoption of these methods across sectors and emphasises the need for standards. For example, geodata and property data must adhere to the INSPIRE directive’s standards to ensure cross‑border interoperability; health data must comply with the forthcoming European Health Data Space; and industrial data sharing may leverage the International Data Spaces framework. The Government also highlights the potential of synthetic data and privacy‑preserving techniques to unlock value from personal data while maintaining compliance with the General Data Protection Regulation (GDPR).

Data protection and ethical considerations

While Norway advocates open data, it stresses privacy and ethical safeguards. The Digital Norway white paper warns that sharing data for AI must respect fundamental rights and freedoms. The GDPR is emphasised as both a guardrail and an enabler of trusted data sharing. Agencies and businesses must incorporate data protection impact assessments (DPIAs), apply the principle of data minimisation, and adopt privacy‑by‑design. The Norwegian Data Protection Authority (Datatilsynet) operates a regulatory sandbox where developers can test AI solutions under the guidance of privacy experts. This sandbox aims to encourage innovative use of data while ensuring compliance and building public trust.

For industrial data sharing, confidentiality and intellectual‑property rights remain critical. The government’s principles require that data sharing mechanisms preserve business secrets and give companies control over their data. This can be challenging when combining datasets from multiple sources. Data trusts and federated learning are proposed as methods to allow AI models to learn from dispersed datasets without exposing raw data. Synthetic data can also reduce privacy risks by generating plausible datasets for training while protecting real customer or patient data.

Ethical considerations extend beyond privacy. Norway’s AI strategy highlights fairness and the avoidance of discrimination as essential. High‑quality AI solutions require high‑quality data; bias in public or industrial datasets can produce unfair outcomes. The strategy urges agencies to adopt processes for identifying and mitigating bias, including diversity in training data and transparency in algorithms. Norway is also aligning with the EU AI Act, which introduces risk‑based requirements for AI systems and prohibits certain high‑risk uses. Compliance with the AI Act will require robust documentation and human oversight, particularly when deploying AI solutions that rely on public data.

Energy and natural resources

Norway is a major energy producer and has developed pioneering data-sharing initiatives in this sector. The Diskos repository demonstrates how a national data repository can facilitate exploration by pooling seismic and drilling data from both state and private operators. Because the repository is accessible only to members, it preserves competitive advantages while ensuring industry‑wide efficiency. Foreign oil and gas companies participating in Diskos must abide by joint venture rules and national security provisions; for example, sensitive data on critical infrastructure or strategic reserves may be protected. The model could be extended to renewable energy: sharing offshore wind resource data, grid information and environmental impact studies could accelerate the green transition.

Transport and logistics

Geonorge’s geospatial datasets power applications such as route planning, autonomous driving and drone logistics. Public–private collaborations under Norway Digital provide geodata to telecom and power companies, enabling infrastructure planning and real‑time network management. For new entrants – such as mobility platforms or logistics start‑ups – the availability of accurate, up‑to‑date geodata reduces market entry barriers. However, datasets may have to be updated frequently and integrated with dynamic data (traffic flows, weather) to support AI‑driven decision making. Open APIs and open standards (for example, the European ITS standards) will be essential for interoperability.

Health and life sciences

Norway participates in the European Health Data Space (EHDS) and invests in health data infrastructure. Public health data – such as registries for births, diseases, prescriptions and hospital admissions – are valuable for research and AI but are highly sensitive. The digital Norway strategy emphasises data sharing while preserving privacy, referencing anonymisation interfaces like RAIRD. Synthetic data can enable innovation by providing training data for AI algorithms without risking patient confidentiality. Norway also collaborates with Nordic countries to share health data ethically and may adopt secure data spaces under EHDS. Start‑ups working on AI medical diagnostics should therefore explore collaborations with health authorities and abide by strict confidentiality and ethical guidelines.

Manufacturing and Industry 4.0

The Norwegian research institute SINTEF has introduced International Data Spaces (IDS) to Norwegian industry. IDS provides a standardised infrastructure and data sovereignty controls that allow companies to share industrial data while keeping control. For example, manufacturers can exchange machine data with equipment suppliers for predictive maintenance without disclosing all operational details. As Norway expands its industrial AI applications (e.g., predictive maintenance for offshore rigs, machine learning for fish farming), adoption of IDS will facilitate collaboration across supply chains. The government is considering requiring data sharing in licenses or contracts to encourage adoption.

Urban development and smart cities

Norwegian municipalities collect data on traffic, energy use, waste management and public services. Combining these datasets across agencies can improve urban planning, reduce emissions and enhance citizen wellbeing. The once‑only principle encourages municipalities to share data rather than repeatedly ask citizens for the same information. Yet municipalities vary in capacity; some may lack resources to curate data or navigate privacy laws. The planned national prioritisation council could help identify municipal datasets with the greatest public value. Smart city initiatives should align with European Smart City standards and ensure interoperability with cross‑border platforms.

Public data as a foundation for AI solutions

High‑quality AI systems require large quantities of diverse, accurate and representative data. The digital Norway white paper highlights that data is a prerequisite for high‑quality AI solutions for the public sector. However, government agencies often under‑utilise existing data because of inadequate coordination and fear of breaching privacy rules. The Government intends to strengthen coordination, adopt clear guidelines and develop training to ensure that agencies understand how to anonymise or synthesise data appropriately and how to balance openness with data protection.

Data quality and metadata standards

AI models are highly sensitive to the quality of training data; errors or biases in public data can propagate through AI systems. The National Audit Office and the Norwegian Digitalisation Agency emphasise order in your own house – agencies must maintain comprehensive inventories of data, document data structures and maintain data quality. Metadata standards such as Dublin Core and DCAT-AP are required for datasets published on data.norge.no. Agencies should also adopt domain‑specific standards (INSPIRE for geodata, HL7 FHIR for health, International Data Spaces standards for industrial data). The national prioritisation council may develop best practices for metadata and quality assurance.

High‑value datasets and EU data spaces

The EU’s Open Data Directive classifies certain datasets as high‑value datasets that must be available for free, in machine‑readable form and via APIs. The white paper notes that Norway will identify particularly important datasets and prioritise their publication. In 2025 the EU adopted implementing rules for high‑value datasets in categories such as geospatial, earth observation, meteorological, statistics, companies and mobility data. Norway is preparing to align with these rules. Participation in European data spaces, including health, industrial and public procurement data spaces, will enable Norwegian organisations to access cross‑border data and contribute national datasets. Such integration can foster innovation in AI applications, but also requires compliance with European interoperability standards and data governance frameworks.

Balancing openness and security

Open data policies must balance innovation with national security and personal privacy. Data about critical infrastructure (energy grids, communications networks, defence facilities) and sensitive public services may not be openly shared. The white paper emphasises that data must be protected when necessary and that agencies need good information management to decide which data can be shared and which must be restricted. The National Audit Office warns that agencies often struggle to assess privacy and security risks early in development projects. To avoid delays, agencies should conduct privacy and security assessments in parallel with legal, technical and functional evaluations. The GDPR and national security laws (e.g., the Security Act) provide frameworks for classification and handling of sensitive data.

Challenges and edge cases

Fragmented data governance – Norway’s digitalisation strategy acknowledges that national governance and coordination of data sharing are inadequate. Agencies develop their own systems and metadata standards, making it difficult to integrate datasets. The national prioritisation council and the resource centre for data sharing aim to unify efforts, but progress may be slow.
Compliance costs for SMEs – Small organisations often lack resources to implement data sharing and privacy safeguards. They may view open data obligations as burdensome. Government grants and standardised tools could help, but there is a risk that stringent requirements deter new entrants.
Balancing privacy with innovation – Public agencies are cautious about violating privacy laws, but this can lead to missed opportunities. Misinterpretation of GDPR may inhibit data sharing even when anonymisation or synthetic data could mitigate risks. The digital Norway strategy encourages a proactive approach: leverage the GDPR’s flexibility and consult the Data Protection Authority’s sandbox.
Incentivising industrial data sharing – While voluntary data sharing is encouraged, companies may be reluctant to share proprietary data due to competition concerns. Without incentives or regulatory requirements, industrial data spaces may remain underused. The Government’s proposal to impose data sharing through licences or public contracts could face resistance from industry.
Data quality and bias – Low‑quality public data can harm AI models. Incomplete or biased datasets from the public sector may produce discriminatory algorithms. Agencies must adopt quality assurance, bias detection, and diversity measures. There is also an open question about liability for AI outcomes based on flawed public data.
Legal uncertainties – Implementation of the EU Data Act and Data Governance Act will introduce new rights and obligations for data holders and users. Businesses may need legal advice to navigate data access requests, data sharing contracts, and compensation models. Over‑regulation could stifle innovation, while under‑regulation could lead to market concentration or privacy breaches.

Actionable recommendations

For public agencies:

Conduct data inventories and classify datasets according to sensitivity and potential value. Register datasets and metadata in the National Data Directory and data.norge.no. Use open formats and APIs to ensure accessibility.
Develop data management plans that embed the principles of “open when possible, protected when necessary”. Provide clear justifications for withholding data and implement risk‑mitigation techniques such as anonymisation and synthetic data.
Prioritise publication of high‑value datasets that support AI development. Work with the prioritisation council to identify national datasets that would benefit the economy and society.
Train staff in data protection, anonymisation, and AI ethics. Use the Data Protection Authority’s sandbox to test innovations and build capacity.
Engage with European data spaces and standardisation initiatives. Align with EU interoperability frameworks and ensure cross‑border compatibility.

For researchers and academic institutions:

Adopt the open research data principles: open as possible, closed as necessary; curated for maximum value; and community‑driven decisions on archiving.
Share datasets, code, methods and models in open repositories when possible. Use data trusts or anonymisation interfaces to share sensitive data. Explore synthetic data to create open training datasets for AI research.
Collaborate across Nordic and European networks to build shared data infrastructures and share domain expertise.

For businesses and SMEs:

Assess your data assets and identify potential for sharing or utilising public data. Consider joining industry data repositories or consortia like Diskos or Norway Digital for geospatial data.
When developing AI products for the Norwegian market, incorporate publicly available datasets into training pipelines, but ensure compliance with data licences and attribution requirements.
Evaluate participation in data trusts or International Data Spaces. These frameworks provide data sovereignty controls that might make sharing attractive. Use data intermediaries to broker data access without giving up ownership.
Stay informed about the EU Data Act and Data Governance Act. Prepare for new rights to access IoT data and obligations to share certain datasets under fair, reasonable and non‑discriminatory terms.
Collaborate with public agencies to propose pilot projects that leverage open data. Use features like Data Hunter on data.norge.no to request datasets and engage with the portal’s forums.

For policy makers and regulators:

Finalise comprehensive legislation on data sharing based on the recommendations from NOU 2024: 14. Provide clarity on public data reuse and align domestic law with the Open Data Directive, Data Governance Act and Data Act.
Establish the national prioritisation council and develop transparent criteria for prioritising datasets. Draw on international models like Ireland’s Open Data Governance Board.
Expand the regulatory sandbox and provide resources for SMEs to test data‑driven innovations. Publish guidance on anonymisation, synthetic data, federated learning and data trusts.
Create incentives for industrial data sharing, such as tax benefits or public recognition for companies that participate in open data spaces. Use public procurement and licensing conditions strategically to require data sharing where it serves the public interest.
Promote education and training in data literacy across the public sector, academia and industry. Data governance should be integrated into digital skills programmes.

Conclusion

Norway envisions a society where data flows freely and responsibly to fuel digital transformation and high‑quality AI solutions. The digital Norway white paper crystallises this vision with the principles of openness, accessibility, usability and value creation. The Government recognises that data is a prerequisite for high‑quality AI and public services, yet acknowledges the challenges of governance, privacy and coordination. By strengthening national data governance, aligning with EU directives, investing in infrastructure like data.norge.no and the National Data Directory, and fostering voluntary and regulated data sharing in industry, Norway aims to unlock the full potential of public and industrial data.

The path forward requires balancing openness with protection, encouraging voluntary collaboration while imposing requirements when necessary, and ensuring that data quality and ethics guide AI development. Public agencies, researchers, businesses and policymakers each have a role in building this data ecosystem. Through coordinated efforts, Norway can transform its wealth of public and industrial data into a foundation for innovation, sustainability and societal well‑being.

Sources

The Digital Norway of the Future (Ministry of Digitalisation and Public Governance, 2024) – Sets out principles that public data should be open when possible, protected when necessary, accessible, usable and value‑adding. It notes that data is a prerequisite for high‑quality AI solutions and that agencies must improve data sharing. It proposes a national prioritisation council for data sharing and references EU regulations such as the Open Data Directive, Data Governance Act and Data Act. The document emphasises cross‑sector standards, open APIs and prioritising high‑value datasets.
National Strategy for Artificial Intelligence (Ministry of Local Government and Modernisation, 2020) – Discusses open public data, the Freedom of Information Act and the Digitalisation Circular requiring machine‑readable formats. It highlights sectors where open data has high economic value and describes research data principles. It notes that companies own their data but often lack data awareness, and provides examples like the Diskos repository and the Norway Digital geodata collaboration. It describes the International Data Spaces framework and the government’s principles for business data sharing.
Norway enhances data discoverability with AI-powered search (data.europa.eu, 2025) – Describes the AI‑powered search function of data.norge.no, which interprets natural language queries to help users find datasets and provides interactive tools like Data Hunter and discussion forums. It notes that the portal’s user‑first design lowers entry barriers and advances the goals of Europe’s open data strategy.