Now that the business model of one specific skills data space use case has been described, a more general approach is presented to understand the value, costs and benefits that skills data space use cases bring to any participant.
In the dynamic skills data space, understanding the business and value exchange in any use case is essential both strategically and ethically. According to the Data Space Support Centre (DSSC), ‘Business models that consider the value propositions of all involved actors are crucial for adopting and sustaining the data spaces. Paying attention to all these value propositions is also important from an ethical and sovereignty perspective to ensure a fair value distribution.’
This section delves into the experiences of all different data space roles. Each comes with unique activities, requirements, and value propositions influencing their journey through the data space. For example, a service provider offering skills analytics must not only attract new customers but also collaborate with new data providers to enhance their service. By joining the data space, they can leverage data space features like marketplaces and discovery to expand their reach. Two representative roles’ journeys (individual end user and service provider) are also depicted in a graph to visually illustrate a participant’s journey and reveal all its key life stages.
Rather than merely focusing on a transactional or one-sided approach, the emphasis here is on a co-creative business and value exchange. Each role—whether it’s a data provider, a service provider, or an end-user—brings in a unique set of value propositions that contribute to the overall value of the data space. Aligning these value propositions with each role’s journey through the data space is essential for both business sustainability and ethical governance.
By aligning these value propositions with each actor’s distinct journey through the data space, it positions the effort to build sustainable, ethical, and equitable data spaces. The co-creative lens adopted goes beyond mere value creation, aiming for fair value distribution across all participants.
The Business Model Radar has been introduced in [DSSC-starterkit, Business model radar] and it serves as an effective tool for adopting this co-creative approach. It helps to explore three key areas:
- Value proposition for each role: Outlines the unique value each role brings and why they should join the use case.
- Role co-production activity: Details the activities each role undertakes to deliver their value proposition.
- Costs and benefits: Enumerates both financial and non-financial costs and benefits incurred or gained by each role from participating in the use case.
The Business Model Radar’s content is further elaborated in the subsequent tables, detailing each role. These interactions highlight the interdependence of various roles within the data space, where each contributes to the creation, sharing, and maintenance of value. The table presents the value propositions, interactions with other roles, and the benefits and costs associated with each role. This model is filled from the perspective of the EU-DUNE use case, encompassing all participating roles, as introduced at the beginning of this chapter
5.4.1. Individual end user #
An individual end user becomes a part of the data space use case. For instance, consider an individual seeking job opportunities in a foreign country. This person joins the data space use case, establishes an account through their Personal Data Intermediary (PDI), provides consent, and initiates the job search service. The individual has the flexibility to view and update their profile and consent settings at any time, and they can also explore new services offered in the catalogue, such as training programs. In cases where a service incurs charges, the individual must ensure the availability of payment methods and make regular invoice payments.
During their usage of the platform, this individual may encounter queries or disputes related to invoices, prompting them to request clarification. In instances where the resolution of the request does not meet their satisfaction, they might choose to exit the data space use case. Exiting entails the closure of all ongoing activities and the deletion of their data.
Hence, it is of utmost importance to identify and define all potential exit points for end users and establish procedures to detect and prevent participant attrition.
Interaction model with other actors:
- With service providers: individuals get value by specialized services that meet their needs (skills matching, analytics, etc). They might pay for the service.
- With data providers: individuals get value from data products like trainings.
- With infrastructure providers: individuals utilize infrastructure services to connect with the data space and to access and utilize data products or share their personal data.
| Role name (Actor, Stakeholder) | End users and customers of the data space use case; individuals | |
| Value propositions | Data space use case’s value proposition for the Role | Empower individuals: Access to a tool for skills-related data management and tools, services and data for personal growth via data control.
Human-centric control, trust and fairness: Individuals control their data for their benefit and data sharing is transparent and equitable.
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| Role’s value proposition for other data space use case stakeholders | Individuals are both the end-users and primary clients for other roles.
Anonymized and synthesized end-user data is highly valuable for organizations, policymakers, and service providers, enabling effective planning, simulations, and trend analysis. EU-DUNE: Individuals serve as the primary users and fuel for all roles, especially for service providers. |
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| Monetary benefits | Bonuses, salary, allowances | |
| Non-monetary benefits | Personalized skill development, enhanced career planning, time efficiency, job satisfaction, improved opportunities, skill validation, greater control, lifelong learning, career advancement, personal growth. | |
| Costs/Risks | Costs | Potential cost of services, insights, results (not everything is freemium). |
| Risks | Limited number of services, poor data quality, high costs, and a complex system can all negatively impact the network effect, making it difficult for the data space use case to grow and improve. | |
| Models | Business | End users as clients don’t have business models |
| Pricing | End users as clients don’t have pricing models | |
Table 1: Summary from business perspective why an individual end user would join skills data space
5.4.2. Organisational end user #
Consider, for example, an organization aiming to consistently enhance its employees’ skills or anticipate future skill requirements. They can browse the catalogue/marketplace and find suitable use cases they want to join. This organization becomes part of a data space use case by signing data space use case agreements that define the services and data they get and the conditions to access them.
From this point onward, the process closely parallels that of individual end-users. Maintaining high satisfaction for both the organization and its employees (end users) throughout this journey is of utmost importance, as them exiting the data space use case could potentially harm the reputation and impede the growth of the data space and data space use case.
Notably, if the organization for example wants to upskill their employees, they need to connect their employee’s data in which case, they become a data provider with all needed policies and procedures to follow (see Data Provider user journey).
Interaction model with other actors:
- With service providers: they get value by specialized services that meet their needs. They pay for the service.
- With data providers: they get value from data products like trainings, skills insights, analytics. They pay for the data product.
- With infrastructure providers: end users utilize infrastructure services to connect with the data space and to access and utilize end products or share their personal data. They pay for the service.
- With orchestrator: they pay for usage of the use case.
| Role name (Actor, Stakeholder) | End users and customers of the data space use case; organisations | |
| Value propositions | Data space use case’s value proposition for the Role | Get valuable insights and recommendations to futureproof individuals and organizations at the labour market.
Access skills data for informed planning and decision-making. Utilize data-driven insights to shape effective policies and strategies. Trust and fairness: Data sharing is transparent and equitable. Access to valuable skills data sources, services resources to enhance your services. Bolster research capabilities and offer trend analysis to better serve your clients. Platform for skill-related data management. EU-DUNE: DigiFutUX: Get valuable insights and recommendations to futureproof their employees. IntelliAITraining: New leads and customer acquisition, access to data and services to provide better and more focused trainings and services, and enhanced visibility. |
| Role’s value proposition for other data space use case stakeholders | Organisational end users are the main clients of the data space use cases.
EU-DUNE DigiFutUX serve as the primary client and financial contributor for all roles, particularly service providers. IntelliAITraining is a client for services and data providers, uses the system and pays for it. |
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Monetary benefits | Reduced cost of manual work and management time of verifying skills, searching insight, and foresight into skills and trainings. |
| Non-monetary benefits | Enhanced employee performance, increased employee satisfaction, improved talent retention, competitive advantage, stronger employer brand, employee empowerment etc. | |
| Costs/Risks | Costs | Cost of services, insights, results. |
| Risks | Limited number of services, poor data quality, high costs, and a complex system can all negatively impact the network effect, making it difficult for the data space use case to grow and improve. | |
| Models | Business | Give data for the data space use case, get back services provided and pay for the services.
E.g.: Transaction, freemium, subscription model, |
| Pricing | End users as clients don’t have pricing models | |
Table 2: Summary from business perspective why an organisational end user would join skills data space
5.4.3. Orchestrator #
Let’s consider an example of an orchestrator looking to establish a new data space use case, specifically focusing on skills within a country with stringent data privacy laws.
They will need to register their organisation with the data space and adhere to all governance, terms and conditions, and technical requirements of the data space, set by the Data Space Governance Authority. Subsequently, they proceed to describe the use case as well as the data and services they need. They also need to develop the governance rules for the data space use case, define technical requirements (including building blocks and standards), outline business and pricing models, all while adhering to the data space’s prerequisites.
Their use case is then featured in the data space catalogue(s). They can subsequently be matched with appropriate service and data providers. They can then identify a suitable data and service providers and invite them to join their use case.
This onboarding, description, contracting and matching process can be executed in either of the following ways:
- Using a Data Intermediary service, certified by the DSGA, that operates the data space building blocks and provides such data space enabling services (such as matching with other providers and use cases, catalogue, contractualization, billing, etc).
- Operating the data space building blocks provided by the DSGA themselves and getting certified. This makes them effectively a trusted data intermediary as well, serving only their own organisation.
The data space use case thus enters the operational phase of its lifecycle, witnessing the inclusion of new participants, the consumption of data products, and the issuance of invoices. The orchestrator sells the use case to end users and actively fosters the growth of the data space use case through advertising and other strategic efforts.
However, if the operational costs outweigh the income generated, the orchestrator may contemplate discontinuing their business within the data space use case. In discussions with the data space administrators, they may identify a new orchestrator willing to assume their role. This transition process involves a thorough assessment of their obligations, the preparation of procedural handover measures, notifications to all end users, the signing of exit documents, and the execution of the handover procedures.
Interaction with other actors:
- Data space Governance Authority: Orchestrators may consult the DSGA to acquire knowledge about best practices, regulations, or other relevant topics. They may use the DSGA’s building blocks to operate them themselves if they don’t go through a data intermediary.
- Service and data providers: the orchestrator gets the value provided by these providers to propose to end users.
- End users: the orchestrator get paid by the end users for usage of the use case.
Data intermediaries: the orchestrator gets data space enabling services from data intermediaries to put its use case into place.
| Role name (Actor, Stakeholder) | Orchestrator | |
| Value propositions | Data space use case’s value proposition for the Role | The orchestrator sets up the use case. He is serving the end users and need to combine providers in order to provide better value to end users, he can find and combine thanks to the data space.
EU-Dune: – SkillsFast as the orchestrator can combine SKillProfiX and SDAI to provide an augmented and powerful app to end users. |
| Role’s value proposition for other data space use case stakeholders | The orchestrator takes care of the business and governance operations of the data space use case.
EU-Dune: – SkillsFast commercialises EU-DUNE and brings more business to all the use case participants. |
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Monetary benefits | Gets paid for services they provide for the use case, governance model, portal, marketing etc. |
| Non-monetary benefits | Societal impact – faster, cost-effective and new innovations for employment, skills mismatch problem.
Recognition, awards |
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| Costs/Risks | Costs | E.g.: Operational, marketing, data space use case management |
| Risks | No engagement and interest from users, service/data providers, inability to generate value for stakeholders and attract more users and services. | |
| Models | Business | E.g.: Transaction (sell reports), Subscription (portal access), Freemium |
| Pricing | E.g.: Usage-based, Data-based, Value-based, Availability based | |
Table 3: Summary from business perspective why an orchestrator would join skills data space
5.4.4. Service Provider #
Consider a skills analytics service provider looking to expand their business by becoming part of a data space.
They will need to register their organisation with the data space and adhere to all governance, terms and conditions, and technical requirements of the data space. They then need to describe and list their services and products as well as their usage policies, business and pricing models.
They can then identify a suitable data space use case, assess the value proposition, and evaluate the associated costs. To gain approval, they diligently adhere as well to all governance, terms and conditions, and technical requirements outlined at the use case level.
Upon receiving approval, the provider undertakes the task of implementing all necessary building blocks, such as data and service connectors.
This onboarding, description, contracting, matching and integration process can be executed in either of the following ways:
- Using a Data Intermediary service, certified by the DSGA, that operates the data space building blocks and provides such data space enabling services (such as matching with other providers and use cases, catalogue, contractualization, billing, reference business and governance models, etc).
- Operating the data space building blocks provided by the DSGA themselves and getting certified. This makes them effectively a trusted data intermediary as well, serving only their own organisation.
Their service is then available to be used in that specific use case under the conditions agreed upon with the data space use case orchestrator.
They can also choose to use the data space to develop a new product by combining their service with other service and data providers, which makes them an Orchestrator (see below).
However, should they find themselves facing insufficient business prospects, they may make the decision to exit the data space. This involves a comprehensive process, including reviewing their obligations, notifying their end users and orchestrators, executing all relevant documentation, purging all associated data, and ultimately closing their account.
Interaction model with other actors:
- With end users: Service providers deliver value to end users by offering specialized services that meet their needs. They get paid by them for service usage, sometimes directly, sometimes through the orchestrator, depending on the business model the orchestrator has set for the use case.
- With data providers: Service providers rely on data from data providers of the use case to power and enhance their services.
- With service providers: Service providers may incorporate other services from services providers of the use case to their service to power and enhance their services.
- With infrastructure providers: Service providers utilize infrastructure services to connect with the data space and to access or share data products in the use case. They pay for the service.
- With the orchestrator: Service providers communicate with the orchestrator to define their role and scope within the data space, to get instructions regarding rules and policies and building blocks they need to implement. They can get paid by the orchestrator, depending on the model.
- With the DSGA: Service providers may consult the DSGA to acquire knowledge about best practices, regulations, or other relevant topics. They may use the DSGA’s building blocks to operate them themselves if they don’t go through a data intermediary.
| Role name (Actor, Stakeholder) | Service Providers | |
| Value propositions | Data space use case’s value proposition for the Role | New customer acquisition, access to unique data sets, enhanced visibility
Empower service providers to expand their business, improve their offerings, and establish a competitive advantage. The data space use case serves as both a marketplace and a marketing channel, extending their reach and bolstering credibility. EU-DUNE: SkillProfiX, SDAI The use case “EU-Dune” uses SkillProfiX and SDAI services, they get paid for that. It’s also enables them to get new leads and clients and connect and collaborate with data providers and other service providers to create more comprehensive solutions together. |
| Role’s value proposition for other data space use case stakeholders | For the data space use case, the inclusion of service providers specializing in areas like skills matching or analytics adds significant value by diversifying the range of services available to participants. These specialized services not only attract a broader audience but also encourage higher engagement within the data space use case. By integrating services that meet specific needs, such as analytics, the data space use case becomes more robust, versatile, and appealing, thereby fostering its overall growth and sustainability.
EU-DUNE: SkillProfiX, SDAI SkillProfiX uses Matilda’s and DigiFutUX data to precisely assess Matilda’s strengths and weaknesses against current UX skills and propose her the most interesting areas and skills to improve for her. Matilda can share, with her consent, her skills data results from SkillProfiX to SDAI to get training and learning recommendations. SDAI can access different data sources connected to Fire-X (FindTraining, YourTraining) to match Matilda with the right one. Both use the services and pays for those. |
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Monetary benefits | Gets paid for services.
Service providers benefit from easy access to high-quality data, resulting in lower costs, faster time to market, and improved service |
| Non-monetary benefits | Access to data space and users: being part of a data space use case provides service providers with a ready audience, opening doors to user engagement and potential business.
Increased user base and brand visibility: inclusion in a data space naturally amplifies brand recognition and extends the service provider’s reach, benefiting from economies of scale. Reduced marketing and customer acquisition costs: a collaborative data space can serve as a shared platform for marketing, thereby reducing individual customer acquisition costs for service providers. Access to diverse data sources: membership in a data space use case grants service providers access to a variety of data sources, enriching their service capabilities. Shared marketing costs: marketing expenses can be distributed among multiple stakeholders in the data space use case, making promotional efforts more cost-effective. Lower development costs: the standardization of data interoperability, compliance, and governance within a data space can reduce the costs associated with developing new services and integrating new data space use cases. Innovation opportunities: service providers have the chance to continuously improve, iterate, and even create entirely new services based on emerging needs and insights from the data space. |
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| Costs/Risks | Costs | Pays for own & DS operational costs.
Pays for costs of their data product (e.g., data usage, other services included). |
| Risks | Limited number of consumers, paying customers, data sources, limited engagement and interest from users, service/data providers, inability to generate value for stakeholders. | |
| Models | Business | E.g.: Transaction, freemium, subscription model, |
| Pricing | Various models e.g., Usage-based, Data-based, Value-based, Availability based | |
Table 4: Summary from business perspective why a service provider would join skills data space
5.4.5. Data Provider #
Consider an organization that possesses data they are willing to share for potential monetary or nonmonetary benefits. This data could be for an instance an anonymised list of all people from one country who finished university in one period or a list of job vacancies.
They will need to register their organisation with the data space and adhere to all governance, terms and conditions, and technical requirements of the data space. They then need to describe and list their datasets as well as their usage policies, business and pricing models. They can then identify a suitable data space use case, assess the value proposition, and evaluate the associated costs. To gain approval, they diligently adhere as well to all governance, terms and conditions, and technical requirements outlined at the use case level. Upon receiving approval, the provider undertakes the task of implementing all necessary building blocks, such as data and service connectors.
This onboarding, description, contracting, matching and integration process can be executed in either of the following ways:
- Using a Data Intermediary service, certified by the DSGA, that operates the data space building blocks and provides such data space enabling services (such as matching with other providers and use cases, catalogue, contractualization, billing, reference business and governance models, etc).
- Operating the data space building blocks provided by the DSGA themselves and getting certified. This makes them effectively a trusted data intermediary as well, serving only their own organisation.
Their dataset is then available to be used in that specific use case under the conditions agreed upon with the data space use case orchestrator.
However, if the organization encounters limited business prospects or decides to discontinue their participation, they may choose to exit the data space use case. This entails a comprehensive process, involving a review of their obligations, notifications to end users, execution of all relevant documentation, agreeing with ODI upon data purging, and ultimately the closure of their account.
Interaction model with other actors:
- With end users: Data providers deliver value to end users by allowing their specialised datasets to be used in the use case. They get paid by end users for data usage, sometimes directly, sometimes through the orchestrator, depending on the business model the orchestrator has set for the use case.
- With service providers: Data providers provide data to the service providers of the use case to implement it.
- With infrastructure providers: Data providers utilize infrastructure services (Data Intermediaries) to connect with the data space and to access or share data products in the use case. They pay for the service.
- With the orchestrator: Data providers communicate with the orchestrator to define their role and scope within the data space, to get instructions regarding rules and policies and building blocks they need to implement. They can get paid by the orchestrator, depending on the model.
- With the DSGA: Data providers may consult the DSGA to acquire knowledge about best practices, regulations, or other relevant topics. They may use the DSGA’s building blocks to operate them themselves if they don’t go through a data intermediary.
| Role name (Actor, Stakeholder) | Data Providers | |
| Value propositions | Data space use case’s value proposition for the Role | A data provider joins the data space to find a use case that can leverage the provided data and attract diverse data users on its data set.
EU-DUNE Personal data providers: SkillProfiX, DigiFutUX, UXlife, UXschool, Organisational data providers: JobRightNow, Jobijob and Jobo, NewJob, FindTraining, YourTraining, IntelliAITraining EU-DUNE is a service that needs, uses and leverages all data providers data for upskilling use case, for skills analysis and for job and training recommendations. Data providers get paid for their data. EU-DUNE is also a service that can scale their data for new users, enable new use case around the data and monetize it in different ways. |
| Role’s value proposition for other data space use case stakeholders | The data provided serves as a fundamental resource, or “oil,” that powers activities, insights, and value generation across all other roles with the possibility of accessing, combining, and comparing it with other sources in the data space use case.
EU-DUNE: Provide Matilda’s personal data for the data space use case: – DigiFutUX HR system (position, skills, etc), from her past employer (UXlife) and from her university (UXschool). Provide organisational data space use case: – jobs data; JobRightNow, Jobijob and Jobo, NewJob – Training catalogues: FindTraining, YourTraining – Trainings in LMS: IntelliAITraining Different data providers are needed in EU-DUNE upskilling use case in order to provide the service, skills analysis and personalised recommendations for upskilling. Together with other stakeholder a more comprehensive Match use case can be created and delivered. |
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Monetary benefits | Opportunity to monetize their data.
Gets new services build based on data shared. |
| Non-monetary benefits | Ability to share open data with broader stakeholders.
Saves times (less admin overhead). . |
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| Costs/Risks | Costs | Pays for data space operational costs e.g., membership fee |
| Risks | Limited number of consumers, paying customers, limited engagement and interest from users, service/data providers, DS inability to generate value for stakeholders. | |
| Models | Business | E.g.: Transaction, freemium, subscription model, |
| Pricing | Various models e.g., Usage-based, Data-based, Value-based, Availability based | |
Table 5: Summary from business perspective why a data provider would join skills data space
5.4.6. Data Intermediary #
The data intermediary needs first to be approved by the data space as data intermediary to propose their services within the data space. The data intermediary will describe which services and building blocks listed by the DSGA it provides. It will need to be certified to appear as a trusted service provider. The data intermediary will need to provide services that comply with the Data Space Governance Authority decisions and services that allow to implement the building blocks described by the DSGA. Participants then select the data intermediaries they would like to work with to connect to the data space. The data intermediary will then need to ensure integration of its services with the relevant use case participants and ensure those services. The participants can decide to change data intermediaries, as all data intermediaries in a data space rely on same standards the data intermediaries this interoperability is facilitated.
Interaction model with other roles:
- End users: end users do not need to use data intermediaries as they can get the value of the use case without technically connecting to the data space, if they are as well data providers then they can use a data intermediary to connect to the data space.
- Data space Governance Authority: the data intermediaries get certified by the DSGA, incorporate the building blocks prescribed or developed by the DSGA and can then be advertised towards data space use cases.
- Orchestrator: the data intermediaries are selected by the orchestrator to use their services in their use case and are potentially paid by them.
- Data and service providers: the data intermediaries are used by data and service providers and potentially paid by them.
| Role name (Actor, Stakeholder) | Infrastructure providers:
· Organisational Data Intermediary · Personal Data Intermediary |
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| Value propositions | Use case’s value proposition for the Role | All use cases need infrastructure services, joining use cases allows the data intermediaries to generate business.
EU-DUNE: – EU-Dune needs a data intermediary to operate. – SkillsFast, SDAI, SkillPRofiX, IntelliAITraining and all job boards and training catalogs pay a subscription to InfraTrust services. – InfraTrust gets building blocks and certifications from Fire-X to operate a trusted data intermediary service. |
| Role’s value proposition for other data space use case stakeholders | Data Intermediaries provide data space enabling services to use case participants (such as identity, authorisation management, interoperability, catalogue, matching). They allow the use case to easily share data while implementing the data space building blocks.
EU-Dune: – InfraTrust, Personal and Organisational Data Intermediary provides Personal and Organisational Data sharing services to ensure EU-Dune is compliant with all regulations and data can flow between all players, compliant with the rules set out by Fire-X. |
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Monetary benefits | Gets paid for services |
| Non-monetary benefits | Gets requirements to improve their services.
Gets digital commons to operate |
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| Costs/Risks | Costs | Pays for Data space operational costs |
| Risks | Limited number of consumers, paying customers, data sources, limited engagement and interest from users, service/data providers, inability to generate value for stakeholders. | |
| Models | Business | E.g.: Transaction, freemium, subscription model, |
| Pricing | Various models e.g., Usage-based, Data-based, Value-based, Availability based | |
Table 6: Summary from business perspective why a data intermediary would join skills data space
5.4.7. Data Space Governance Authority #
A data space governance authority can be set up by a collective of organisations seeing the value of data spaces and data space use cases as well as the need to mutualise efforts and resources to make them happen. They can have a specific governance and business model ideas for their data space that is not yet implemented by another data space.
They will set up the organisation and its operations. They will need to set up groups and committees to decide the rules and building blocks of their data space. They will need to define their architecture, business and governance model of their data space.
They will need to find data intermediaries to operate their building blocks and participants to come develop use cases on top of their data space. They will need to implement mechanisms to ensure evolutions needed for the data space are heard and participants can be involved in the decisions of the DSGA. They will need to promote their approach and advantages to all these players and ensure interoperability with other data spaces.
Interaction model with other roles:
- Data intermediaries: the DSGA can get paid by data intermediaries for the certification it provides to ensure these data intermediaries truly operate building blocks and services that are compliant with the DSGA’s rules.
- Service providers, data providers, orchestrators: the DSGA gets adoption from these players on their data space.
| Role name (Actor, Stakeholder) | Data Space Governance Authority | |
| Value propositions | Use case’s value proposition for the Role | DSGA needs use cases to spread its infrastructure, governance and business models.
EU-Dune: – The EU-Dune participants adhere to the Fire-X governance and policies, thus augmenting the network effect of that data space. – InfraTrust pays for the certification provided by FIRE-X to operate its services in the data space |
| Role’s value proposition for other data space use case stakeholders | The DSGA provides the data space and data space use cases with digital commons such as: building blocks, reference implementations, template data and service usage policies, etc that can serve all data space use cases and help them gain time.
EU-DUNE: – Fire-X provides EU-DUNE and its participants with building block open-source implementation to implement a human-centric data sharing architecture and InfraTrust takes this code to operate it for EU-DUNE |
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Monetary benefits | Gets paid for their services; governance model, building blocks. |
| Non-monetary benefits | Gets recognition in the domain and across data spaces, gets more influence, visibility, and power.
Gets requirements from concrete use cases to provide the right/better digital commons |
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| Costs/Risks | Costs | Operational, management and development costs (e.g., building blocks) |
| Risks | A critical mass of engagement and usage of the authorisation framework has to be achieved and soft infrastructure set up in order to make the Skills Data Space up and running, and in the long run a sustainable business for all stakeholders. | |
| Models | Business | Non-profit organization and business model. At the beginning a public and private partnership comes of a great importance when guaranteeing the sufficient funds for the functioning of the skills data space.
Later different business models could be used to sustain itself. |
| Pricing (revenue model) | E.g., memberships, usage fee for open-source implementations of building blocks | |
Table 7: Summary from business perspective why DSGA would join skills data space
To make these intricate business models operational, attention should be directed toward their essential building blocks—those fundamental units that enable the practical implementation and functioning of the overall system.
