Data Spaces Radar

Faster IDS breakthroughs are within range

The Data Spaces Radar Report

The first Data Spaces Radar Report of 2024 highlights the new radar and its enhanced features. In particular, it presents the crucial role of the DSSC and its vibrant Community of Practice – a community of data spaces on its way to become operational and changing the way data is shared in different domains. Take a look inside:

The enhanced Data Spaces Radar

More than two years back, the International Data Spaces Association (IDSA) introduced the groundbreaking Data Spaces Radar, a tool that swiftly gained acclaim and found its place within the dynamic landscape of data spaces. Today, we are excited to unveil the evolution of this pioneering asset – the newly enhanced Data Spaces Radar.

The Data Spaces Radar serves as the central repository for all data space endeavors. It is an accessible tool designed to provide a comprehensive view of various data space initiatives worldwide. Offering insights into the 18 different sectors, global expansion, technical transparency and new stages of development of the data spaces featured in the radar.

Explore the new Data Spaces Radar

Bring data spaces to life

Only the coolest new platform for finding use cases to help you bring data spaces to life, our Data Spaces Radar maps all our data spaces in one easy-to-use tool. The radar covers use cases of different degrees of maturity from the phase of creating a business case to real data spaces. From planned to pilot to fully operational, across industries and functional domains — the use cases that align with your business goals are on the radar.

The Data Spaces Radar

Version 4 | March 2024

3.34 MB

The Data Spaces Radar

Version 3 | October 2023

2.72 MB

The Data Spaces Radar

Version 2 | July 2023

8.29 MB

The Data Spaces Radar

Version 1 | March 2023

3.83 MB

Frequently asked questions

What is the Data Spaces Radar?

The Data Spaces Radar is a tool to give visibility to all data space endeavors out there, transparency on their achievements and identify the most promising ones, to foster evolution and matchmaking.

Why should I bring my use cases/data spaces to the Data Spaces Radar?

The Data Spaces Radar is the only tool that showcases your data space. The radar has also been acknowledged by the European Commission as a valuable source of information regarding data spaces, making it the ideal platform for your endeavors.

Is the Data Spaces Radar only for members of IDSA?

No, the Data Spaces Radar is open to everyone who would like to showcase their use cases or data spaces.

Is Data Spaces Radar only for IDS-based endeavours?

No, if you have a data-sharing use case that is not yet implementing IDS but is part of your plans, feel free to bring it to the radar. However, to achieve higher maturity levels (pilot and live), IDS components should be implemented and operational.

How can I join?

By filling in this form. It is pretty easy to fill in and takes just about 10 minutes!

Are there more ways to disseminate my use cases or data spaces once I register them on the Data Spaces Radar?

Yes, IDSA features the data spaces from the radar under #DataSpacesTuesday on LinkedIn. Members of IDSA can also present their data spaces during our weekly Ecosystem Building Call or at our events and live sessions.

Not a member? Become a Member – International Data Spaces

The maturity of my use case/data space has changed, how can I update this on the radar?

You can update your entries by using the same registration form and selecting ‘I want to update an existing entry’.

What is a cross-domain use case/data space?

This is a use case or data space where partners from different domains (e.g., health and agriculture) share data with each other.

Is the Data Spaces Radar only for European endeavors?

No, the Data Spaces Radar welcomes use cases and data spaces from all around the world. IDSA encourages individuals to create projects based on the IDS Standard and submit them to the radar.

Contact Carlos

Any questions? Contact us!

Your contact person:
Carlos González Ruiz
Ecosystem Operations Manager

Join the data spaces radar

Bring your own use cases and data spaces based on the IDS standard on our radar and let others get inspired.

Join

Post-Platforms for Smart City

Post-Platforms Sciences | Po Startinblox | Digita Digentity SolidLab | City of Amsterdam | City of Rio de Janeiro

CHALLENGE:

Various actors, from public services like Police and City planning to private companies in the transport, garbage processing, construction, and utilities, currently use hundreds and thousands of databases, platforms, apps, and systems, creating probably the biggest data silos ever, with an incredible amount of outdated records and data conflicts.

SUCCESS:

In our Web 3.0 Data Space solution, we place all data concerning each respective building, every road, as well as every significant part of the electricity, pipe, gas, and other networks on dedicated PODs.

Now every authorized entity, public or private, can work (read and write) with the very same “data at the source”, which is always correct and always up to date. This is the same approach as working with a shared document: every user works on the same original record and can see all changes in real-time.

We believe and can prove that a similar approach is totally realistic even for the biggest urban agglomerations.

BENEFITS:

Life quality improvement due to better data-based and citizen-centric policy making Better commuting thanks to optimized itineraries and real-time data on population and road infrastructure 100% correct and always up-to-date official records, used by each and every public service or by authorized private organizations Tax, address, and other public systems automation based on available data on every element of city infrastructure

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Post-Platforms for Manufacturing

Post-Platforms Sciences | Po Startinblox | Digita Digentity | SolidLab

CHALLENGE:

Every large corporation nowadays suffers from too many poorly interconnected IT systems, databases, and platforms. It’s even more challenging for large manufacturing companies where the number of systems may reach ~1000.

Even from the end-user perspective, this situation is quite stressful and energy-consuming: human resources are used in a non-optimal way because of all the files exchange, related paperwork, unautomated communications; etc. But if we look at it holistically, we’ll see large business performances considerably impacted by these dozens or even hundreds of balkanized platforms and systems with their respective databases.

Lack of interoperability is the most apparent issue. Still, there is another one behind it: data silos, multiple copies of similar data without a clear understanding of which version is the most recent. These data silos automatically imply that there is no control over data quality and that your technical teams spend lots of effort to interconnect all these often almost incompatible systems and to coordinate their incoherent ontologies. Last but not least, it negatively affects data transmission outside the company, including both communications with its clients and all interactions with its suppliers and contractors, which is especially crucial for the manufacturing sector.

All these issues constantly keep too many human resources busy, consume too much energy, and result in the underperformance of the whole business.

SUCCESS:

Corporate data doesn’t have to fit Procrustean beds of a multitude of different databases with different ontologies and data formats. Instead, it can be stored in a universal and fully machine-readable Linked Data format on separate secure virtual servers – we call them PODs – for each object you interact with.

Each machine or piece of equipment you use, each client or contractor you are connected with, can have such a POD with every single piece of data related to them stored there.

BENEFITS:

Transparent access to all relevant ship related data
Secure, robust and efficient communication between ship and shore
Simplified provision of trusted services for ship operation
Interoperability and data sovereignty for all involved parties

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Post Platforms for Renewable Energy

Post-Platforms Sciences | Po Startinblox | Digita Digentity | SolidLab

CHALLENGE:

Lack of coordination for distributed energy generation: there’s no single system to automatically monitor the real-time performance of each energy-generating device

- Lack of coordination for installation funding and energy purchase: individuals and organizations don’t have access to up-to-date information regarding funding and other financial options available

- Lack of information for other available incentives: regional, national, and European renewable energy support programs often communicate quite poorly with their target audience and need to make their programs and incentives available to each and every user

- Lack of structured data regarding energy output, new and existing installations, etc., makes existing statistics imprecise and not always accurate, as a consequence impacting also the policy-making, construction of unnecessary new grids, creating non-optimized financial services, etc.

SUCCESS:

All data from every installation is stored on PODs, making their data instantly available (and fully machine-readable) for any authorized platform, including off-takers, providers, maintenance teams, etc.

The same abundant and well-structured data can now be analyzed by research institutions, University labs, policymaker's offices, etc., helping to improve their respective recommendations and decisions.

On the other hand, every public or financial institution also publishes their programs and projects on their own PODs, so that they are accessible to every interested individual or organization.

BENEFITS:

Transparent access to all relevant ship related data
Secure, robust and efficient communication between ship and shore
Simplified provision of trusted services for ship operation
Interoperability and data sovereignty for all involved parties

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Post-Platforms for Automotive

Post-Platforms Sciences | Po Startinblox | Digita Digentity | SolidLab

CHALLENGE:

The automotive industry is one of the most complex manufacturing industries ever since it uses thousands of components made by hundreds of suppliers, and then handles the maintenance of millions of vehicles of hundreds of different makes and models.

Such large corporations nowadays suffer from too many poorly interconnected IT systems, databases, and platforms. It’s even more challenging for automotive companies where a number of systems may easily overpass ~1000.

At the same time, the automotive industry is tightly connected to such complex niches as infotainment, cartography, itineraries, etc., where cars can and shall both receive road information from external sources and share the data the car records itself with other systems and vehicles.

SUCCESS:

Our solution is pretty straightforward. We connect a dedicated server - a POD - to each vehicle and its key components. Each POD stores all the telemetric data in real-time, and allows access and processing of this data via any authorized platform. These are the same IoT and smart vehicles we already know but on a totally new level of specification and accessibility.

Integrations with other systems, including geopositioning, itineraries, hotel bookings, charging stations, etc., become seamless since every vehicle and every respective entity or spot can now automatically exchange data through any platform selected by the manufacturer or by the owner.

BENEFITS:

Transparent access to all relevant ship related data
Secure, robust and efficient communication between ship and shore
Simplified provision of trusted services for ship operation
Interoperability and data sovereignty for all involved parties

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Tidy City

Sintef | Logimade Lda. (Logistics company) | Transbag (Logistics company) | IL Technologies | Lda (Software Studio) | Promerch (Advertising Company) |Sicaprep (installation and maintenance of electric, electronic, telecommunications, and energy infrastructures) | Madeira Waste Recycling (management, monitoring, collection, transportation, treatment and elimination of all types of industrial, commercial or residential waste) | Smart Islands Hub (European Digital Innovation Hub)

SUCCESS:

The Tidy City experiment proposes to equip vehicles with mobile devices to take pictures and later process them to automatically detect and classify problems in publicly visible infrastructures. To reduce pollution and CO2 emissions, street-level images will be collected by a wide range of vehicles that already travel the city streets daily, such as waste collection trucks and express delivery vehicles.

The collected images are sent to a server for analysis and classification based on AI models. Within the scope of this experiment, the system will be able to detect and record the GPS location of damages in outdoor advertising, lightning, and electricity supply infrastructures, and improper waste disposal situations (e.g., waste outside containers, tires, old appliances, and furniture).

The detected occurrences data will be shared with each corresponding partner for integration and operations optimization. To comply with the RGPD and other European and National legal requirements, all personally identifiable information (e.g., people’s faces and license plates) will be removed from the images through the same privacy by-design processes already used by Google Street View.

BENEFITS:

The Data Space will allow for multiple interested parties to access detailed and treated information (AI applied to image frames does detect anomalies) regarding various kinds of occurrences detectable from the public streets.

COMPONENTS:

This use case is part of the i4Trust second call for experiments, It will use FIWARE's Orion Context Broker protected with the gateway proxy Kong (open source) for the data sharing. The Identity Management will be done using Fiware's Keyrock (IDM) while applying iShare's specifications (rules of access in an Authorization Registry and parties validation in an iShare Satellite). The data offer will be made available in an instance of the i4trust Marketplace.

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EdgeDS

Intracom Telecom

SUCCESS:

This use case addresses the emerging need for secure, trustworthy, and sovereign data

exchange among diverse stakeholders in edge computing ecosystems.

This approach integrates mechanisms for trustworthy and sovereign data exchange, into Multi-access Edge

Computing (MEC) environments, by extending the ETSI MEC Architectural Framework with

IDS components and enriching Edge Computing applications with data space capabilities in

an as-a-service paradigm.

BENEFITS:

This work highlights the feasibility and usability of incorporating an IDS Connector-as-a-Service within the MEC Platform, towards creating a data ecosystem that enables trustworthy and sovereign data exchange and intercommunication of multiple domains and applications that are hosted at the Edge.

The proposed architecture provides the capability of utilizing and composing Dataspace-enabled MEC Applications, where any MEC App can act as a data service provider (potentially under some pricing scheme) towards other MEC Apps. This is not restricted to the supply of data but also extends to data processes (e.g., ML models, data analytics workflows, etc.). Moreover, the MEC Platform itself can offer such value-added services, in addition to secure data exchange services, which translate to additional revenue streams for the Communication Service Provider - CSP (who is operating the MEC Platform).

Last but not least, third-party data solutions providers can offer (B2B2C) such data processes to the CSPs to enrich their services on their MEC Platforms, without the need for third-party providers to run as MEC Apps, but rather by just providing the data processing models/software. To showcase the benefits of data-driven collaboration across systems and actors, we employ a motivating example use case from the Autonomous Driving domain. We envision different scenarios for autonomous, connected vehicles on a highway, which are powered with advanced safety, traffic routing, and other features through the enactment of data service ecosystems.

For instance, we consider the ‘see-through’ case of a vehicle that intends to pass a truck and is temporarily provided access to a video stream of the car preceding that truck, which is equipped with a camera. Similar scenarios are applicable, such as the ‘platooning’ of vehicles that can drive in a coordinated manner as a group, sharing sensing information, or the exchange of safety or traffic alerts between vehicles on the highway.

COMPONENTS:

This Use Case proposes the extension of the ETSI MEC architecture, by introducing the “IDS- Connector-as-a-service”, instilled directly into the MEC mechanisms.

The prototype implementation of the proposed architecture includes the integration of the Dataspace Connector, implemented by Fraunhofer. In the introduced architecture, extending the MEC Architecture, each MEC Application (MEC App) can act as a data provider/consumer, in accordance with IDS roles distinction.

By introducing the concept of IDS Connector-as-a-Service among the functionalities provided by the MEC Platform, each application is capable of obtaining its own connector—which exists within the MEC Platform as a MEC Platform-offered service instance—and can exchange data with any application that has a registered connector inside or outside of the MEC host.

In the scenario of two MEC Applications exchanging data, we denote MEC App1 the application that attempts to receive data, and as MEC App2 the one that provides the desired data. After the completion of the instantiation of both applications and the assignment of a certified IDS connector to each of them, the connectors’ information is available through the MEC Platform’s relevant API for service discovery and availability. While data services that are not IDS enabled are registered directly on the MEC Platform, MEC App2 registers the data resources it provides on its own connector. In order to consume the desired data services, MEC App1 receives the information of MEC App2’s connector. Subsequently, MEC App1 performs a request to its own connector, encapsulating the information of the other connector, along with the identifiers of the targeted resources. Finally, if the usage policies attached to the contract of the requested resource are accepted, then data transfer from the provider to the consumer is followed as defined by IDS.

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Solar Charge API

SUCCESS:

Solar Charge API will deploy a big data stack to generate smart charging suggestions based on data provided by multiple Grid Stakeholders. The smart EV charging suggestions and proposed daily charging schedule per region will be made available via API calls through NGSI-LD API to ensure that the smart charging schedules are accessible and comprehensible by other nodes.

Entities that subscribe to the API will need to go through user authentication via FIWARE key rock before accessing the Solar Charge API service

BENEFITS:

Transparent access to all relevant ship related data
Secure, robust and efficient communication between ship and shore
Simplified provision of trusted services for ship operation
Interoperability and data sovereignty for all involved parties

COMPONENTS:

Historical data of transactions in EV charging station data from eMSPs
Grid operation data from open data repositories ( i.e ENTSO-E)
Energy production data from independent solar producers, and renewable energy project assets managers. Our data provider Helios RES LP belongs to these groups.
Building consumption data from smart meters in residential households that feature rooftop solar installations. Namely, P1 Link and My Energy Community platform, developed by GridOne enables real-time data fetching from PV and smart meters. The solutions by GridOne will be integrated to SolarCharge API and will enable ICENT to access data and develop predictive models for daily solar energy production from rooftop PV and residential building consumption.
The service then groups and analyzes the data per region and generates a day-ahead charging schedule proposal for each region. Then eMSPs and other electricity grid stakeholders can access the daily charging schedule for their region via API calls through Orion LD Context broker and incorporate them in their applications by displaying messages/ action prompts to their users.

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Green Deal Dataspace

Advaneo GmbH | IDSA

CHALLENGE:

The frequency of global crises such as pandemics, wars, and disasters has increased, and building shared solutions using data connections is crucial for dampening their effects and becoming more sustainable and resilient. The PAIRS and SPELL platforms are examples of prominent use cases that will be part of the Green Deal Dataspace.

The PAIRS platform, in particular, allows for transparency in the supply chain by identifying crises and their effects on individual participants. However, finding and using data in a sovereign way remains a core challenge. Interested parties need to know how to find services to become more resilient while ensuring data privacy and sovereignty. Additionally, creators of such services need to find initial partners to build the required networks.

SUCCESS:

The solution to the challenge of finding and using data in a sovereign way lies in using established and independently certifiable standards for data sharing, such as IDSA and GAIA-X.

These standards are integrated into a unified system that allows for offering, finding, and accessing relevant data sources and services related to resilience and sustainability. The IDS solution and its corresponding connectors are basic technologies that enable sovereign data exchange within the Green Deal Dataspace.

BENEFITS:

Companies and organizations as users of the Green Deal Dataspace benefit from our data-based approach to digital infrastructure to integrate decentralized information in a protected virtual space. With this infrastructure, users are either able to apply already implemented services or to develop new services supporting our users in order to gain new insights and knowledge.

The variety of data sources which are part of the Green Deal Dataspace also facilitates cross-over domain approaches for services as also will be implemented inside the PAIRS-Plattform. Especially the supply chain use case as a cross-over domain service utilizes the different data sources coming from different.

By additional search and finding functionalities inside the Green Deal Dataspace partners can connect to build research projects, exchange in a sovereign way data, and make use of the existing Dataspace infrastructure. In the end, this enables users to seamlessly build their own trustworthy resilience and sustainability ecosystems.

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Data Space Radar: Resilience Data Space (HERAKLION)

Sintef |

CHALLENGE:

The aim of HERAKLION is a demonstrator for a scalable Resilience Data Space. This is developed on the basis of pandemic and extreme weather scenarios (lead use cases), which take up the needs of municipal users and implement them conceptually.

The Resilience Data Space is associated with the Resilience and Sustainability Data Space (RSDS) and is developed in close cooperation with it. A bottom-up approach is pursued in the HERAKLION project, which culminates in a demonstrator for quantifying municipal resilience using data space functionalities. In contrast, the RSDS follows a top-down approach and is operated live immediately in order to integrate various projects and services.

SUCCESS:

BENEFITS:

The innovation of HERAKLION is the provision of a functional Resilience Data Space and the associated analysis services, which function individually or together as a digital ecosystem in which data can be managed decentrally and used multilaterally in compliance with strict sovereignty standards.
The standardized infrastructure of data space ensures a low threshold for municipal actors.
The data, analytical methods, and simulation tools for the quantification of municipal resilience will be made available as a decision support system for three user groups: 1) municipalities, 2) SMEs and large companies, 3) as well as authorities and organizations with security tasks

COMPONENTS:

A process and template for a "Data Space Requirements Specification (DSRS)" is being developed for the special boundary conditions in data space development, in which use cases and requirements are initially unclear, even for the end users. On the basis of this DSRS, the technical implementation is carried out and IDS components are selected via incremental prototyping and reviewing with the end users.

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The Data Spaces Radar #3

MONDRAGON ASSEMBLY EGOKIA

MONDRAGON ASSEMBLY - an international firm specializing in the development of automatization and assembly solutions for various sectors. It operates 6 production plants around the world and is part of the largest cooperative group in the world | IKERLAN Technical research center and member of IDSA

CHALLENGE:

EGOKIA solution allows collaborative learning and knowledge sharing between geographically distributed plants, integrating headquarters in Basque Country and domain experts. Thanks to the data space, data, and AI assets can be securely shared throughout different corporate sites and a new knowledge-based economy emerges.

SUCCESS:

Deploys an architecture based on IDSA connectors, linking Mondragon Assembly’s data and AI platforms from different corporate sites. With this new reliable data space, we extend the lifecycle of artificial intelligence models, enhance their capabilities, and facilitate trusted access and use of its assets by EGOKIA participants.

BENEFITS:

NEW BUSINESS MODEL: A new business model based on AI services and a knowledge-based economy. RELIABLE AI SOLUTIONS: A "standardized", flexible, and secure solution to break data silos to share and complete AI assets and processes between trusted organizations and production plants. Measurable benefits can be listed as: Up to 30% quality on models thanks to the application of federated learning techniques, reduce inversion and time to market on IA-based solutions or lower communications loads. STANDARIZED DATA SPACE – The organization is ready to take part in the knowledge economy with other entities, domain experts, and technology providers.

COMPONENTS:

Data Space connectors 8.0.2 Metada Broker 5.0.3 Identity Provider 1.6.0

I4.0 data space and app marketplace for connected factories and service providers

Ikerlan

(1) i2CAT Foundation: technical partner responsible for the implementation and deployment of the IDS-compliant data space solution, App Store prototype, and integration of the data apps into the App Store. (2) CIM UPC Foundation: industry research partner with an experimental pilot factory floor with machinery and deployed IoT sensors where the collected data originates. (3) Universitat Politècnica de Catalunya (UPC) and their Motion Control and Industrial Applications (MCIA) and Advanced Control Systems (SAC) research groups: development of the data analytics and ML applications.

CHALLENGE:

The scenario brings up several challenges:

1. This data is susceptible, and timely, related to core production processes in the factory. Secure data transmission and agility are key, and traditional sharing methods are inadequate.

2. Factories must avoid lock-in situations to service providers, requiring interoperable approaches that allow them business flexibility in a competitive market of third-party services. This is equally important on the other side of the market, where SME service providers need an equal playing field for competing for that factory’s business.

3. New and developing regulations, such as the Data Governance Act and Data Act, change the market dynamics of data exploitation, requiring a scalable solution for data sharing that is built around core principles such as data sovereignty.

SUCCESS:

The i2CAT Foundation in Barcelona has implemented an IDS-compliant data space and marketplace prototype in the regional Industry 4.0 project, Looming Factory. It addresses those aforementioned challenges via the following:

1. A minimal viable data space (MVDS) approach that securely connects the project’s pilot factory floor machinery with developed predictive analytics services through a connector-based solution. The factory maintains strict usage control over its data, transmitted over a secure system.

2. An IDS App Store prototype implementation that allows those certified third-party providers’ services to be discovered by the factory and deployed in their secure, connector-based environment.

3. Third-party predictive analytics services for the marketplace proof of concept developed by Looming Factory project partners included predictive maintenance, operational cost estimation, production time cycles, and energy efficiency. These acted as demonstrators for the proposed solution for industry actors outside of the R&D project.

The Looming Factory project was co-funded by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program for Catalonia 2014-2020.

BENEFITS:

Enabling secure, sovereign data sharing in an ecosystem of I4.0 data services: IDS-compliant trusted environment for data sharing for secure, controlled exchange of sensitive production data between factories and third-party service providers. The factory is connected to a potential ecosystem of third-party data services that optimize their production processes: higher efficiency and lower OpEx.
Empowering business flexibility in the marketplace of competitive services: App Store prototype hosts and deploys innovative third-party data apps in an interoperable data space architecture. Factories are not locked into a single provider and have a selection of competing solutions, while SMEs can use the AppStore as an onboarding platform to provide their services to factory customers in an extensible data space.
Scalable solution for data regulatory compliance: I4.0 data service providers can deploy their solutions in an IDS-framework designed for future data regulation and evolving market dynamics between data and service providers.

COMPONENTS:

i2CAT has implemented the solution following the IDS-RAM 3.0 architecture and based on the Open Source implementations of the different components provided by IDSA. In particular, the solution includes the following components: (1) Dataspace Connector v8.0.0; (2) App Store v2.0.0; (3) DAPS (the Fraunhofer test certification authority was used, and specific digital certificates for the pilot were previously requested and issued.) These Open Source solutions have been modified and adapted to the specific needs of the use case, especially in terms of the connectivity between the Dataspace Connector and the App Store. The App Store has also been significantly improved with a new GUI and several services to connect it with a private docker image registry.

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FutureForest

Freie Universität Berlin | Technische Universität München | M.O.S.S Computer Grafik Systeme GmbH

CHALLENGE:

Climate change makes the adaption of forests a very high-priority issue for forest owners and management companies. Without reliable data, it is very hard to make decisions in a fast-changing environment. Not acting will lead to economic and ecological losses. Traditionally, forest owners and practitioners rely little on data and have had no access to the data of others at all. This limits the discovery and adoption of best practices.

SUCCESS:

In our data space, forest research organizations, state forests, forest management companies and forest practitioners can access a common pool of relevant data, such as climate data, soil data, tree species distribution and tree health information, as well as in situ sensor data. It is well-defined who can access which data what for. As an example, the whole pool can be used to train AI models.

With this central, interoperable data pool, any new organization coming on board can quickly deploy state-of-the-art solutions to help in their decision-making, all the while retaining control over the data that they contribute.

BENEFITS:

Through the data space, risks related to climate change can be mitigated and revenue can be protected or enhanced, especially taking into account carbon capture and other incentiuves. Other ecosystem services can be enhanced, and as such, the value of the decision support given exceeds economic returns. The forestry data space also contributes to biodiversity and to the social and recreative functions of forests.

COMPONENTS:

Eclipse EDC Connector v0.0.1-milestone-8, MVD, extended Re3gistry as a vocabulary provider

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Introduction

IKERLAN is a leading knowledge transfer technological centre providing competitive value to companies. We seek for excellence in R&D&i, thanks to the continuous adaptation to the needs of our customers and the proximity with the business reality. Faithful to our mission, we have been working daily since 1974 to develop solutions that allow our customers to become more and more competitive. We are a cooperative member of the MONDRAGON Corporation and the Basque Research and Technology Alliance (BRTA).

Business Expertise

Thanks to a unique cooperation model, which combines technology transfer activities, internal research and training of highly qualified personnel, IKERLAN is currently the trusted technological partner of major companies in the country. To meet our goal, we are structured into two technological specialization units:

ELECTRONICS, INFORMATION AND COMMUNICATION TECHNOLOGIES
ENERGY AND MECHATRONICS

IKERLAN is a center that is dynamic and open to the world. We are an accredited agent of the Basque Network of Science, Technology, and Innovation and of the Spanish Federation of Technology Centres. We have a major cooperation network integrated with renowned European centers and universities, with which we conduct activities of research and training of researchers.

Technical Expertise

Mission: To solve the technological challenges of the companies, improve their competitiveness and collaborate with the sustainable social and economic development of the environment, all of that from a position of technological leadership and with differential abilities in their areas of expertise.

Vission: Technological center, cooperative and non-profit, known as the European leader in its areas of specialization, with an exceptional cohesive human team, that provides value to the companies and society.

Contact Details

Santiago Charramendieta
scharramendieta@ikerlan.es

Website
https://www.ikerlan.es/

iGreenPort

CHALLENGE:

The quality of seawater is crucial to ensure the sustainability of ports. Coastal waters are deteriorating due to pollution and eutrophication, which is expected to increase by a further 20% by 2050. For this reason, the digitalization of port processes needs to consider the environmental perspective.

The combination of seawater quality data with information about ships characteristics and position is crucial for identifying the ships that could cause water pollution. iGreenPort addresses the real need of the Spanish Port of Palma de Mallorca to digitize the control of the seawater quality following the European Sea Ports Organization’s SDG 14 Environmental Code of Conduct, which instructs port administrations to develop tools to manage environmental problems.

SUCCESS:

iGreenPort is a cutting-edge initiative that provides port authorities and other port agents with environmental management capabilities. It offers a Data Space for sharing and accessing environmental and operational data, combining two types of data:

1) Seawater quality data, starting with turbidity among 15 indicators mandatory by law.
2) AIS data from ships, which provides information about the vessels every 3-6 seconds, including their characteristics and position. This data can be cross-referenced with the seawater quality data to determine their involvement in contaminated areas. The solution enables the authorities to make faster and more informed decisions that promote the efficiency and environmental sustainability of their ports.

BENEFITS:

Port Authorities are responsible for the prevention and control of marine pollution emergencies in their service area (Zone 1) and are investing in specialized surveillance to allow for rapid action in the event of pollution incidents. iGreenPort provides a cutting-edge tool for monitoring seawater quality in near real-time and identifying ships that could cause water pollution.

COMPONENTS:

Several DSBA-based FIWARE components are used in the iGreenPort Data Space, such as a marketplace, security component, and the storage of large amounts of real-time data. Additionally, iShare is used for multinational electronic identification

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HUAWEI Data Space

Huawei | Fraunhofer ISST

CHALLENGE:

• Data exchange economy needs a trust mechanism for cross-subject data flow for different data sharing scenarios (B2B, B2C, G2C and G2B)

• To achieve trusted framework a data usage control mechanism needs to be implemented to manage and monitor the entire process of data exchange

• Automated cross-entity data usage control policy is required with contracts and effective performance with blockchain technology

Sovereign Control should enable data owners to decide how data is used:

• Construct an ecosystem with Multi-Party Trust, for performing trustworthy authentication on organizations, individuals, and technical components through qualification assessment and certificate issuance, establish a unified trust mechanism, and ensure that participants' identities and platform environments are trusted

• Create composable policies to control data access, and set policies based on data use (ie. validity period, number of viewing times or downloads, access rights). Control use of data to ensure that data is used in compliance with laws and regulations based on data sovereignty and control

• Support data provider to verify and trace user access, and exempt consumers can be exempted from the certificate. Provide reliable and visible audit tracing services throughout the process, support providers to verify and trace, and if needed to revoke certificates from consumers, and provide corresponding audit information for third-party supervision

SUCCESS:

IDS-RAM and Eclipse Dataspace Components are at the core of a Huawei Data Space solution, that has been created to address business challenges listed above, and has been developed in compliance with and according to IDS specification (with new IDS components to be included)

BENEFITS:

Global economy consists of a variety of data suppliers and consumers in the upstream and downstream industry chains. To promote the rapid development of a data-based economy and to improve production efficiency, data must be effectively shared and data sovereignty must be guaranteed. Huawei Data Space solution provides key service value streams such as data provision, data consumption, and data operation supervision and control.
Based on an IDS Data Space technology it ensures that data flows are trusted, controllable, and verifiable. Currently, Huawei Data Space supports 16 participants, 6 business scenarios, and 21+ use control policies. 5,000+ data assets have been uploaded, and 10,000+ data exchanges have been performed, effectively supporting the in-depth business collaboration of ecosystem partners in the computing industry in R&D, manufacturing, and product services.

COMPONENTS:

Huawei Data Space uses standard open-source components, known by enterprises to ensure fast adaptability. Developed Glue-code will be made available as open source as well. It uses the following components:

1) Keycloak for Identity Federation
2) Apache Atlas as a federated service catalog
3) ELK-Stack for compliance monitoring
4) EDC v.0.2.1 (Eclipse Dataspace Connector) for policy-based Data Exchange
5) Web-UI for easy end-user access
6) Integration and Deployment code for easy deployment

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The ENES Data Space

Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) | Institut Pierre Simon Laplace (IPSL) | Centre National de Recherche Scientifique (CNRS)

CHALLENGE:

The European Network for Earth System (ENES) modeling community was launched in 2001 comprising a network of about 50 groups including public, academic, and industrial partners who agreed to work together and cooperate to discuss strategies to accelerate progress in climate, Earth system modeling and understanding.

This community is a key player in the assessments of the Intergovernmental Panel on Climate Change (IPCC) and provides the multi-model climate projections on which EU mitigation and adaptation policies are built.

The ENES community is facing new challenges as a result of the increased model complexity and the availability of emerging computing platforms. Moreover, new multi-disciplinary audiences need access to the ever-increasing volumes of data for addressing climate change societal challenges.

SUCCESS:
Data, services, and tools represent the three fundamental components of the ENES Data Space ecosystem. The data offering is at the core of the data space. However, it is important to remark that data alone would not be enough without a comprehensive ecosystem, including a wide set of tools and services enabling scientists to develop applications, analyze data, visualize results, reproduce analyses, share code, and publish new products. Through the seamless integration of these different aspects, the ENES Data Space aims to support challenging climate-related analyses and applications. IDS would play a key role in this allowing the ENES Data Space to adopt or be compliant with standards in the field, thus enabling increased data sharing based on trustworthy technology and interoperable formats.

BENEFITS:

The ENES Data Space aims to provide climate scientists with a complete ready-to-use research environment enabling them to perform scientific analysis on large climate datasets. Providing scientists with large ready-to-use datasets and software solutions closely integrated with the computing infrastructure can almost completely eliminate the setup time and dramatically increase productivity. Moreover, the possibility of easily reusing applications and sharing the research outputs represents a key aspect in the scientific analysis process towards Open Science and a more sustainable, effective, and FAIR use of data. Overall, the ENES Data Space can democratize climate data analysis by supporting new user groups and communities that do not currently have access to solutions capable of addressing such large-scale analysis.

COMPONENTS:

The ENES Data Space architecture consists of the following functional components: a) Gateway Interface and Authentication/Authorization (Identity Provider) b) Data Science Environment including i) Analytics engines ii) Data cataloging utility and related domain-specific Data Reference Syntax, controlled vocabularies, and conventions c) Cloud-Based Computing Platform; d) Data Access and Sharing services

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CADS - Carbon Agri Data Space

CHALLENGE:

One of the biggest challenges in agriculture today is the use of heterogeneous data for smart farming technologies, improving soil fertility, and food quality, and reducing the impact of agricultural technologies on climate change.

Today, numerous sources of data are collected and not leveraged as much as they could be. Potential applications are huge, such as decision-support tools taking into account not only scientific recommendations but also information about the experience of using various agricultural additives for specific climatic and environmental conditions. Carbon measurement and estimation are promising applications to improve the existing systems, but also to provide new value streams for farmers.

SUCCESS:

The idea is a service for the assessment of the carbon footprint of agricultural products in the process of growing as well as tools for sound adjustment of agro-technological, organizational, and management decisions by food producers. Thanks to a data-sharing ecosystem, we will provide the opportunity for farmers (through data service providers interacting with the decentralized data-sharing infrastructure), to leverage the use of the data they already produce, combined with other data sources such as external and open data.

It will provide them with tools that will help the farmers to come up with tangible proof of their carbon impact. Also, dedicated stakeholders of the ecosystem will find go-to-market opportunities for these proofs, bringing back value for the whole ecosystem.

BENEFITS:

Data sharing will demonstrate benefits for many participants – in optimizing existing products, valorizing bi-products, and making data space partners more attractive to downstream users in selecting new primary producers for new product lines within the carbon-negative economy. Also, some outputs of the data space are valued by the market, and this value will be distributed among contributors, according to a fair business model driven by the rising price per tonne of CO2-e in the market as EU-wide sequestration targets drive large-scale investors to increase the volume of carbon-negative market products becoming available at scale (including on-farm soil carbon sequestration and long-cycle productization).

COMPONENTS:

Apollo 0.0.6
Keyrock 8.3.3 with iShare plugin
Kong 0.5.3 with iShare plugin
Orion-ld Context broker 1.5.0

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Increased visibility of order delivery process

VTT | Wärtsilä | Uwira

CHALLENGE:

The use case revolves around expediting and enhancing transparency between a focal company of a manufacturing ecosystem (OEM) and its supplier in their production order management processes. The existing communication methods have proven inadequate in facilitating efficient and adaptable exchanges between the two entities. By facilitating transparency and fostering a more seamless integration between the IT systems of both companies, the management of product orders can be streamlined, resulting in heightened efficiency and a reduction in errors.

SUCCESS:

The objective is to facilitate a reliable and seamless flow of data between the OEM and its supplier by establishing a dedicated data space. The developed solution will be seamlessly integrated with pre-existing IT infrastructures of both companies and the solution is grounded in the framework of the IDS reference architecture.

The OEM can selectively disclose data from their production environment to the supplier without the fear of data leakages. Respectively, the supplier receives only the data that are essential for them and there is no need to locally extract meaningful insights and valuable information from big data sets.

BENEFITS:

The established data space solution has the potential to significantly enhance transparency between the OEM and the supplier. This gives rise to several potential benefits, including:
Effective Communication: Transparent communication helps in conveying accurate information about product specifications, requirements, changes, and timelines.
Risk Management: Sharing information about potential risks, such as changes in demand or design modifications, allows suppliers to proactively address these issues. Furthermore, in times of disruptions, such as supply shortages or unexpected market shifts, transparent communication helps both parties respond more effectively.
Cost Efficiency: Transparent communication allows both parties to work together to find cost-effective solutions.

COMPONENTS:

IDS connectors - serve as the communication interface linking the two companies and their existing IT systems. With IDS connectors, a data provider can define the rules and conditions (usage policies) under which data are shared with a data consumer.
DAPS - enables connectors to authenticate themselves using X.509 certificates. After successful authentication, the DAPS issues OAuth2 access tokens for connectors, who need these tokens to access the services and data of other connectors.
Metadata Broker— stores information about the data end-points offered by the participants. The broker provides a query interface for connectors and can hence be considered as the search engine in this use case.

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TRUSTEE - Trust and privacy preserving computing platform for cross-border federation of data

SUCCESS:

In a data-driven world, interdisciplinary and geographically dispersed data repositories naturally emerge. These repositories may not always adhere to established interdisciplinary data representation standards or participate in data federation initiatives. As a result, researchers often face limited access to valuable data, and maintaining integrity, privacy, and security during data exchanges can be exceptionally challenging, if not impossible.

The EU-funded TRUSTEE project aims to address these challenges by delivering a green, secure, trustworthy, and privacy-aware framework. This framework will aggregate data from multiple interdisciplinary repositories in sectors such as healthcare, education, energy, space, automotive, and cross-border domains. Additionally, TRUSTEE will integrate with other European data federation spaces and transnational initiatives, including IDS and Gaia-X.

This integration between the TRUSTEE framework and IDS/Gaia-X initiatives will create a synergy where additional data providers can participate, allowing IDS/Gaia-X data providers to leverage TRUSTEE's capabilities. Simultaneously, TRUSTEE users will gain access to the data hosted on e.g., IDS connectors, fostering collaboration and data sharing across domains.

COMPONENTS:

In the TRUSTEE framework, the IDS connector serves as the bridge connecting IDS data spaces to TRUSTEE, facilitating seamless data exchange between these entities. The dynamic attributes provisioning service (DAPS) enables connectors to authenticate themselves using X.509 certificates received from the Certificate Authority (CA). In TRUSTEE the metadata broker service can be utilized as an additional metadata repository enabling e.g., the TRUSTEE compatible IDS connector to discover data resources that other IDS connectors can offer for TRUSTEE platform users.

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Digital assets and tools for circular value chains and manufacturing products

SUCCESS:

The EU-funded DaCapo will design human-centric digital tools and services for improving the adoption of Circular Economy (CE) strategies along both manufacturing value chains and products lifecycles (design and engineering, manufacturing, use phase and End of Life). These tools and services will greatly improve both sustainability and efficiency in manufacturing, towards digital-enabled industrial sustainability and resilience.

Digital Product Passport (DPP) stores and shares all relevant information along the product lifecycle. The data content of DPP will evolve and expand during the manufacturing value chain and provide information to the cognitive decision support systems for various human actors. Data space infrastructure's technical and organizational components (e.g., IDSA connectors) are used for ensuring the secure and trusted exchange of product-related information across stakeholders.

COMPONENTS:

IDS Connector – a test, demonstration, evaluation, and adoption of Data Spaces that can be used as a method to access/share/exchange data in the Value Chain (additional information to that included in the DPP). The solution will also utilize the TRUE (TRUsted Engineering) Connector for trusted data exchange. IDS Broker for data resource discover service IDS DAPS for identity management IDS Clearinghouse

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Making the Dataspace Protocol an international standard

This publication details the specification path of the Dataspace Protocol, a significant step towards standardizing data space interoperability.

Key takeaways

- Data Spaces: Digital environments designed for trusted data sharing and utilization, enabling efficient implementation of advanced services and solutions.
- International Standards: The publication underscores the critical role of international standards in providing organizations with the confidence to invest in new data space technologies.
- Dataspace Protocol (DSP): A standardized framework developed by IDSA to integrate key processes common to all data spaces, ensuring interoperability and trust.
- European Union’s Data Act: Set to enter into force in September 2025, this legislation will raise global standards for data flow and sovereignty.
- Standardization path of the Dataspace Protocol: The publication provides detailed steps of the standardization process and a status update

Strategic impact of the Dataspace Protocol

The Dataspace Protocol is poised to revolutionize data sharing, much like the Internet Protocol (IP) and GSM standards did for the internet and mobile communications. The IDSA’s efforts in standardizing this protocol aim to unlock new opportunities for collaboration and innovation across various sectors.

The publication details the standardization path for the Dataspace Protocol, moving through development by the IDSA Working Group Architecture, handling by the Eclipse Dataspace Working Group, and final standardization by the ISO/IEC Joint Technical Committee 1.

This is a milestone in the journey towards a data-driven future, where data sharing is based on trust and data sovereignty. The IDSA’s commitment to international standardization sets the stage for a new era of data management and innovation.

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Frequently asked questions

What is the Data Spaces Radar?

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Is the Data Spaces Radar only for members of IDSA?

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Are there more ways to disseminate my use cases or data spaces once I register them on the Data Spaces Radar?

The maturity of my use case/data space has changed, how can I update this on the radar?

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Post-Platforms for Supply Chain

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Post-Platforms for Smart City

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Post-Platforms for Manufacturing

Post-Platforms Sciences | Po Startinblox | Digita Digentity | SolidLab

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Post Platforms for Renewable Energy

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Post-Platforms for Automotive

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Carbon Capture Audit Trail (CAST / Trust Trail)

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Tidy City

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ManuSpace

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Data spaces for smart energy

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Data Space for Multimodal Passenger Mobility

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The Smart Building Dataspace

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EdgeDS

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IDEAS - IntegrateD Engineering dAta Sharing

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Solar Charge API

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GlobShare

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Green Deal Dataspace

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Data Space Radar: Resilience Data Space (HERAKLION)

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