Introduction

Sharing data can accelerate research impact. However, significant data—especially industry data—that could be shared under controlled access are not being made available due to concerns over trust and loss of control once shared. Dataspaces provide a blueprint to share restricted access data more widely by ensuring control over the data even after it has been shared.

A dataspace is digital infrastructure that enables participants to find, access, and use data based on the governance framework of that dataspace. The vision for dataspaces is to create trusted, secure ecosystems for data exchange where all participants follow agreed rules. Data providers set the usage policies for their data and control over that data can persist even after it is shared.

Key characteristics of dataspaces include the ability to maintain control, establish trust, discover data, negotiate data sharing contracts, orchestration of data sharing, observability of actions, and interoperability. 

The Four Pillars of Dataspaces

Dataspaces provide a mechanism for data at all levels of sensitivity to be shared across multiple systems and sources. A dataspace is built on four pillars:

• Identity Each participant remains in control of their identity, but a common identity model allows all participants to be identified and authorised.

• Trustworthiness Dataspaces provide a common framework for participants to assert their trustworthiness by only accessing and using data as required by the provider.

• Sovereignty Participants negotiate the conditions for sharing data, and the dataspace ensures compliance with those agreements.

• Interoperability Each participant remains in control of their deployment, but data exchange standards and dataspace connectors ensure interoperability.

A technical connector component is used to participate in a dataspace and supports these four pillars. Connectors are often open source, allowing anyone to inspect the code or, with the right skills, create their own connector for certification. 

Evolution and Adoption

The fundamentals of dataspaces have emerged over decades but have recently been consolidated and matured by the International Data Spaces Association (IDSA).

• The work of IDSA has been adopted in the most recent European Data Strategy, with the European Union establishing the Data Spaces Support Centre (DSSC) to coordinate and drive adoption of the dataspaces approach.

• The IDSA and DSSC together provide a flexible set of policies, guidance, and protocols to support the implementation of dataspaces.

• A number of IDSA use cases highlight how dataspaces are being used, and there are over 150 dataspaces on the IDSA radar in various stages of development including europeana, the European Health Data Space and a new dataspace hub in Japan. 

• successful operational dataspaces include Catena-X,  the Mobility Data Space, the Skills Dataspace, and the Green Deal Dataspace 

In its simplest form, a ‘minimum viable dataspace’ only requires at least one data owner and one data consumer. However, the full benefit of dataspaces will result from the ‘network effect’ of adoption by as many participants as possible. 

Further Information

• Visit the Data Spaces Support Centre and read their 101 introductory material.

• Read about the Data Spaces Reference Architecture Model.

• Explore the ARDC’s work on Australian dataspaces through the Planet Research Data Commons for earth and environment science research.

ARDC and Australian Dataspaces

Through the Australian Dataspaces activity of the Planet Research Data Commons for earth and environment science research, the ARDC is currently conducting exploratory work around establishing a dataspace capability in Australia. This initiative aims to investigate the feasibility and value of establishing dataspaces and support for dataspaces in Australia. Learn more and register your interest in our work.

• Join the Australian Dataspaces Community: A collaborative hub for individuals interested in exploring and discussing the evolving landscape of dataspaces in Australia. Includes the Australian Dataspaces Implementers Network, which meets monthly.

• Watch: Introduction to the Australian Dataspaces activity, recorded at the December 2024 meeting of the Australian Sensitive Data Interest Group:

• The ARDC is a member of the International Data Spaces Association (IDSA), contributing to the development of the ISO standard, conducting trials, and advocating for the approach to ensure Australian researchers have a competitive advantage through data.

Defining a Dataspace: IDSA Perspective

Dataspaces are understood as a governance framework and supporting services to build trustworthiness and enable the sharing of data through an agreed set of policies, semantic models, protocols, and processes. 

Key Components

• Governance Framework & Rulebook:
  Defines rules, policies, and procedures that govern how contract data is handled within the data space. It ensures trustworthy data sharing by defining who can access what data, under what conditions, and how it can be used. The governance framework is enforced by a data space governance authority.

• Supporting Services:
  Enable data sharing from the discovery of data to the negotiation of data sharing contracts including the main aspects of establishing trust and maintaining control over data.

• Building Trustworthiness:
  Trusted data sharing is achieved via commonly defined governance frameworks, protocols, and transparency measures.

• Enabling Data Sharing:
  Dataspaces focus on setting up the conditions for successful data sharing (e.g., trustworthiness, contract negotiation), not the orchestration of sharing itself.

• Agreed Policies, Semantic Models, Protocols, and Processes:
  Functional components that must exist to form a data space.

Dataspaces glossary of terms

IDSA glossary

DSSC glossary

Who Should Consider Establishing a Dataspace?

A dataspace is established by a community with specific use cases that require data from multiple owners with requirements around data sovereignty, security, and governance (i.e. the data owners cannot or do not wish to make all the data open).  Standardisation and interoperability within a dataspace make it a cost-effective, efficient solution for data sharing across:

• Geographic boundaries

• Sectors such as industry, research institutions, government, healthcare, and NGOs

Why Move Towards a Dataspace Solution?

• Enable Interoperability:
  Seamless, efficient data interoperability across organisations and domains while maintaining sovereignty with data owners

• Extend Data Connections:
  Enables consumers and suppliers to expand their network beyond bespoke solutions, while retaining control over data access and use.

• Enforce Rules and Agreements:
  Provides recognition of data sharing rules, enforcement of contracts, and retention of data sovereignty.

• Foster Collaboration:
  Supports collaborative undertakings with confidence in data security and compliance.

• Support Business Models:
  A key building block of each dataspace is the collaborative development of a business model where the different parties involved collaborate towards shared objectives while considering each dataspace participant’s incentives and business models.

Advantages of a Dataspace

• Maintain Control Over Data:
  A dataspace provides data suppliers with the ability to maintain control over data after it is shared. This is done by providing mechanisms that ensure data consumers use and access data as required. Examples of these mechanisms include consumer compliance systems and communication of rule violation consequences.

• Scalability:
  High levels of standardisation within dataspaces enable easy scaling to additional data owners and data consumers, fostering broader data economies and eliminating the need for costly, bespoke bilateral agreements.

• Secure Interoperability:
  A dataspace provides seamless and secure interoperability among data suppliers, data consumers and intermediaries by creating an interconnected network of participants enabled through technologies and processes that can facilitate interoperability across different jurisdictions and cloud providers.

• Build Trust:
  A dataspace provides a comprehensive solution to building trust among participants through standardised policies and agreements that transparently establish rules and compliance mechanisms for all.

• Accelerate Data Sharing:
  A dataspace accelerates sharing of high-quality data assets that could be shared under appropriate conditions but are currently not.

Key Organisations Working on Dataspaces

International Data Spaces Association (IDSA)

International Data Space Association (IDSA) develops and promotes the International Data Spaces model for secure and sovereign data sharing, ensuring interoperability and trust among diverse stakeholders. It is a nonprofit organisation based in Germany that was founded in 2016. Its aim is to provide a secure, privacy-preserving, and trustworthy scheme for data exchange, known as the International Data Spaces (IDS).

Data Spaces Support Centre (DSSC)

The Data Spaces Support Centre (DSSC) supports the implementation and scaling of dataspaces, especially across Europe, by providing guidance, tools, and resources to ensure adherence to best practices and standards.

International Organization for Standardization (ISO)

The International Organization for Standardization (ISO) is an independent NGO that develops and publishes international standards across a wide range of industries, including data management, security, and interoperability. The ISO is developing a standard for dataspaces concepts and characteristics (ISO/IEC AWI 20151), to which the ARDC is contributing.

These standards provide guidelines and best practices to ensure that products, services, and systems are safe, reliable, and of good quality. Some of these standards can be certified, and some are important components of dataspaces, such as the ISO 27001 security standard.

International Electrotechnical Commission (IEC)

The International Electrotechnical Commission (IEC) is a global organisation that prepares and publishes international standards for electrical, electronic, and related technologies. These standards ensure the safety, efficiency, and interoperability of systems, including those used in dataspaces. For example, standards such as IEC 62443 are foundational in some dataspace certifications.

Cloud service providers (CSPs)

Cloud service providers or CSPs (e.g. Microsoft Azure, Google Cloud, and Amazon Web Services) offer the infrastructure and tools necessary for deploying and operating secure and scalable dataspaces, supporting data storage, processing, and security.

Gaia-X

Gaia-X is a European initiative that aims to create a federated data infrastructure for secure and interoperable data sharing across Europe, industries and different cloud service providers.

FIWARE Foundation

The FIWARE Foundation provides an open-source platform and tools for building interoperable and scalable digital services, including those involving dataspaces across various sectors.

Eclipse Foundation

The Eclipse Foundation governs the Eclipse Dataspace Components (EDC) Framework, a comprehensive framework providing a basic set of features (functional and non-functional) that dataspace implementations can reuse and customise by leveraging the framework’s defined APIs and ensure interoperability by design. It is powered by the specifications of the Gaia-X AISBL Trust Framework and the IDSA Dataspace protocol.

The EDC is designed for developers who want to build dataspace implementations on an existing, standards-based framework and to adopt and adapt it with their own solutions. Developers use the EDC to build data-sharing services for their customers.

Big Data Value Association

The Big Data Value Association is an industry-driven research and innovation organisation that supports the European big data economy by promoting data-driven innovation and coordinating efforts in establishing data sharing frameworks and infrastructures.

MyData Global

MyData Global is a non-profit organisation that advocates for ethical data use and personal data sovereignty, developing frameworks and standards for managing personal data within dataspaces.

Data flow through Dataspaces