The LDT4SSC Methodology
Workshop Overview
| # | Workshop | Phase | Duration |
|---|---|---|---|
| 1.1 | Mapping your Use Case | EXPLORE | 3h |
| 1.2 | Questioning The Purpose of your LDT Project | EXPLORE | 3h 15min × 3 |
| 1.3 | Implementing Sustainable Digital Design | EXPLORE | 2h |
| 2.1 | Co-Creating Effective Visualisation Dashboards | VALIDATE | 3h 15min |
| 2.2.1 | Understanding Data Governance and Setting the Goal | VALIDATE | 2h |
| 2.2.2 | Mapping Stakeholders' Legitimacy and Authority | VALIDATE | 1h 30min |
| 2.2.3 | Designing your Data Governance Roadmap | VALIDATE | 2h 5min |
| 2.2.4 | Complementing your Data Governance Roadmap with a Legal Framework | VALIDATE | 2h 30min |
| 2.2.5 | Refining your Legal Framework for Data Governance | VALIDATE | 1h 30min – 2h |
| 2.3 | Inventorying your LDT Projects' Data | VALIDATE | 1h 40min |
| 2.4 | Identifying Levers, Obstacles and Objectives for Interoperability | VALIDATE | 2h |
| BONUS | Lego® Serious Play | VALIDATE | 2h 20min |
| 3.1 | Prototyping a Use Case with a Context Broker | DEFINE | — |
| 4.1 | Onboarding & Acculturation in Digital Projects | IMPLEMENT | 1h 10min |
| 4.2 | Designing a Structured Action Plan | IMPLEMENT | 1h 30min |
| 4.3 | Designing a Sustainable Business Model | IMPLEMENT | 1h 15min |
| 4.4 | Refining the Business Model | IMPLEMENT | 2h 10min |
| 4.5 | Completing your Data Cooperation Canvas | IMPLEMENT | 2 days |
Phase 1 – Ideation (EXPLORE)
Many digital projects begin with predefined solutions (dashboards, apps, algorithms) rather than user needs, risking misalignment, irrelevant data use, and stakeholder disengagement. The LDT4SSC Methodology requires a dedicated EXPLORE (Ideation) step to define clear needs and shared use cases, identify relevant data and anticipate impacts, and secure stakeholder alignment and ethical sustainability.
The Ideation step generally lasts from four to eight weeks, depending on the level of maturity and complexity of the project. It does not follow a strict linear path, but is essential for the strategic grounding of the project. Some workshops are however essential, in particular the use case mapping via iterative workshops (1.1 Mapping your Use Case).
📋 Prerequisites
- A clear understanding of the project's broader goals (e.g., smart city objectives, climate adaptation).
- Stakeholder identification and initial engagement (local authorities, experts, citizens, private sector).
- Basic data and resource availability to explore feasibility.
- Alignment with public policies (e.g., digital transformation, sustainability strategies).
- Workshop materials and facilitation tools (e.g., templates, visual aids).
🎯 Objectives
- Identify challenges and opportunities for the Local Digital Twin (LDT) project.
- Define and prioritise use cases aligned with public policy and sustainability goals.
- Engage stakeholders to understand roles, needs, and governance dynamics.
- Assess costs, benefits, and impacts (economic, social, environmental).
- Lay the foundation for validation and detailed planning in later steps.
👥 Stakeholders to Involve
- Project Coordination Roles (Project Coordinators, etc.) – They facilitate structured ideation, stakeholder alignment, and documentation of exploratory outputs.
- Domain Expertise Roles (Use-Case Owners, Subject-Matter Experts, Researchers, Field Agents, etc.) – They define real-world challenges and opportunities, grounding ideation in practical, context-specific needs.
- Decision Roles (Elected Officials, Deputy Chief Executives, Directors, Heads of Departments, etc.) – They ensure strategic alignment with policy priorities and secure high-level buy-in for project direction and resource allocation.
- End-Users or representatives of civil society (Citizens, Citizens' Associations or Panels, etc.) – They ensure use cases reflect citizen priorities and societal impact, fostering inclusivity from the outset.
- Technical Roles (IT Department Staff, External Service Providers, Technical Experts, etc.), if available – They provide early feasibility insights to avoid unrealistic assumptions and ground ideation in technical possibilities.
- Other Local Authorities facing similar issues – They offer peer-learning opportunities and best practices to accelerate problem-solving and innovation.
EXPLORE Resources
1.1 Mapping your Use Case: Visualising Processes, Pinpointing Challenges, and Co-Designing Data-Driven Solutions
This workshop helps teams to visually map the current use case, data flows, and challenges. It fosters a shared understanding of the project's scope and identifies gaps between the current and ideal states. The outcome is a collaborative foundation for the project, adaptable as it progresses.
Workshop 1.1: Mapping your Use Case: Visualising Processes, Pinpointing Challenges, and Co-Designing Data-Driven Solutions
PDF coming soon — contact the project team in the meantime.
1.2 Questioning The Purpose of your LDT Project: Iterative Mapping of the Multi-Dimensional Costs and Benefits
This workshop clarifies the project's objectives and expected impacts across operational, user, strategic, economic, and socio-environmental dimensions. It supports iterative mapping of costs and benefits to justify the project and prioritise functionalities. The result is a clearer project vision, aiding decision-making and resource allocation.
Workshop 1.2: Questioning The Purpose of your LDT Project: Iterative Mapping of the Multi-Dimensional Costs and Benefits
PDF coming soon — contact the project team in the meantime.
1.3 Implementing Sustainable Digital Design: Assessing and Integrating Social, Environmental, and Economic Impacts in Digital Projects
This workshop evaluates the project's relevance, sustainability, and alignment with responsible digital principles. It encourages a collective reflection on ecological, social, and economic impacts throughout the project lifecycle. The output is a matrix of positive and negative impacts, guiding responsible decision-making processes.
Workshop 1.3: Implementing Sustainable Digital Design: Assessing and Integrating Social, Environmental, and Economic Impacts in Digital Projects
PDF coming soon — contact the project team in the meantime.
✨ Achievements at the end of the stage
At this stage of the method, the following elements have been completed or identified:
- Clear project objectives and alignment with public policy goals.
- Shared and prioritised use cases reflecting stakeholder needs and challenges.
- Stakeholder maps outlining roles, legitimacy, and influence in data governance.
- Sustainability and impact assessments (economic, social, environmental).
- Initial cost-benefit framework to guide decision-making.
- Collective understanding of the project's purpose and strategic direction.
➡️ Next: Phase 2 – Specifications (VALIDATE)
Phase 2 – Specifications (VALIDATE)
At the end of the Ideation phase, we have a better idea of the need we are meeting, why we are doing the project, with whom and with what data — but we don't know exactly how. The VALIDATE (Specifications) step provides the link between the vision that emerges from the Ideation step and the actual implementation of the project. It involves translating a use case into technical and functional requirements, taking into account the real constraints of its environment (data, architecture, users, security, etc.).
This step helps to avoid misunderstandings between the business and technical teams, and prepares a solid basis for development. It is also an opportunity to ensure that the principles of interoperability are integrated from the outset. It further ensures that pilots work on the following topics:
- The personas, i.e. the future users of the solution.
- Their functionalities in relation to users.
- The indicators and dashboards in relation to the personas.
- The desired simulations.
- The data and its governance.
📋 Prerequisites
- Completed outputs from the EXPLORE step (clearly-defined use case, stakeholder maps, sustainability assessments, main data requirements and available resources, etc.).
- Access to technical, legal, and operational expertise for feasibility assessments.
- Stakeholder commitment and availability for validation discussions.
- Clear criteria for evaluation (e.g., impact metrics, compliance requirements, resource constraints).
- Workshop tools and templates (e.g., validation frameworks, decision matrices).
🎯 Objectives
- Test and refine use cases, hypotheses, and assumptions from the EXPLORE step.
- Assess technical, legal, and operational feasibility of the proposed LDT solutions (define terms of access, base documents for prototyping, etc.).
- Validate stakeholder roles and governance structures to ensure alignment and accountability.
- Prioritise actions and resources based on feasibility, impact, and strategic alignment.
- Develop a validated roadmap for transitioning into the DEFINE phase.
👥 Stakeholders to Involve
- Project Coordination Roles (Project Coordinators, etc.) – They are vital to align stakeholders, manage timelines, and ensure seamless integration of validated outputs into the project's strategic roadmap.
- Domain Expertise Roles (Use-Case Owners, Subject-Matter Experts, Researchers, Field Agents, etc.) – They ensure the real-world relevance and accuracy of use cases, validating technical and operational assumptions against domain-specific knowledge.
- Data Roles (GIS Specialists, Data Engineers, Open Data Officers, Data Scientists, etc.) – They confirm data feasibility, quality, and interoperability, validating whether proposed data sources and processes meet project requirements.
- Technical Roles (IT Department Staff, External Service Providers, Technical Experts, etc.) – They assess feasibility, validate technical requirements, and ensure alignment between proposed solutions and operational realities.
- End-Users or representatives of civil society (Citizens, Citizens' Associations or Panels, etc.) – They provide user-centric validation, ensuring solutions align with actual needs, usability, and societal impact.
- Legal Roles (Data Protection Officers, Legal Experts, Intellectual Property Managers, etc.) – They are critical to ensure compliance with regulations, mitigate risks, and align data governance with legal and contractual obligations.
VALIDATE Resources
2.1 Co-Creating Effective Visualisation Dashboards: Translating User Needs into Functional Indicators and Visual Prototypes
This workshop guides participants in designing tailored indicators and dashboards that align with the diverse needs of users ensuring clarity, relevance, and alignment with strategic objectives. By adopting the perspectives of different personas, teams define persona-specific indicators, detailing the required data, sources, calculations, and visualisation formats, while mapping the journey from raw data to actionable insights. The process bridges the gap between data and real-life usage, preventing overly complex or irrelevant dashboards, and produces practical deliverables such as indicator sheets, dashboard mockups, and action plans. These outputs empower stakeholders and pave the way for prototyping or deployment.
Workshop 2.1: Co-Creating Effective Visualisation Dashboards: Translating User Needs into Functional Indicators and Visual Prototypes
PDF coming soon — contact the project team in the meantime.
2.2 Implementing data governance
To support the implementation of data governance, pilots are guided via targeted workshops: identifying stakeholders' roles (Workshop 1.1), focusing on governance (Workshop 2.2), defining responsibilities (Workshop 2.3 and 2.4), clarifying legal frameworks (Workshops 2.2.4 and 2.2.5) that together benefit sustainability and stakeholder alignment.
A focus on data governance
Workshop 2.2.1: Understanding Data Governance and Setting the Goal: From Vision to a First Actionable Roadmap
This workshop clarifies data governance by exploring its political, legal, organisational, and technical dimensions, building a shared strategic vision for the local authority or region. Through prospective analysis, participants envision ideal governance scenarios, identify levers and obstacles, and translate insights into a timeline-based action plan — embedding governance into all data projects and defining the roles, processes, and conditions for data quality, sharing, and collective skill growth.
PDF coming soon — contact the project team in the meantime.
Workshop 2.2.2: Mapping Stakeholders' Legitimacy and Authority to act in Data Governance: Understand Roles, Responsibilities, and Hierarchical Influence
Through a role-playing exercise, participants impersonate future users (e.g., operational agents or decision-makers) to simulate a typical day, uncovering challenges and imagining improvements to tools, processes, and interactions. Functional requirements are collectively listed, prioritised, and assessed for usefulness, feasibility, and originality. The workshop produces a visual stakeholder map, insights on power dynamics and governance gaps, and actionable inputs for future governance workshops.
PDF coming soon — contact the project team in the meantime.
Workshop 2.2.3: Designing your Data Governance Roadmap: From Data Officer Mission Statement to Action
This workshop systematically guides participants through the development of a structured governance framework, beginning with the definition of a Data Officer's mission statement and culminating in a detailed, actionable roadmap that aligns roles, responsibilities, and operational stages with organisational objectives. Its primary outputs include a finalised mission statement, a prioritised action plan with assigned timelines and responsibilities, and a visual roadmap outlining short-, medium-, and long-term governance actions, ensuring clarity, accountability, and strategic alignment in data management initiatives.
PDF coming soon — contact the project team in the meantime.
Workshop 2.2.4: Complementing your Data Governance Roadmap with a Legal Framework: From Mapping Legal Phases to Action
This workshop empowers participants to draft robust contracts with providers and partners at every project stage —from LDT creation to interconnection— by identifying essential clauses and leveraging adaptable contractual frameworks (e.g., standard agreements for Proof of Concepts or operational contracts). It focuses on mitigating risks of technological or contractual lock-ins, ensuring seamless interoperability with local authority ecosystems, and equipping teams to negotiate effectively with suppliers while formalising interoperability requirements. Through a structured review of interoperability dimensions (technical, semantic, organisational, legal, and political), participants analyse their project's key stages, using provided resources (clauses, standard contracts, case studies, …) to address critical questions. By the workshop's conclusion, participants (with legal teams) gain clarity on long-term legal actions, IP management, and contract terms for procurement, subcontracting, and co-creation, ensuring the twin's sustainability and value retention in public-private partnerships.
PDF coming soon — contact the project team in the meantime.
Workshop 2.2.5: Refining your Legal Framework for Data Governance: Deep dive into legal and contractual requirements
The legal framework is an essential aspect of data governance. To ensure control, avoid fragmentation and secure usage, local authorities must rely on robust contractual clauses and appropriate internal processes. The aim of this workshop is to enable participants to identify their regulatory needs, formulate concrete proposals for clauses or actions, and compare these needs with existing resources.
PDF coming soon — contact the project team in the meantime.
2.3 Inventorying your LDT Projects' Data: Unlocking Interoperability, Listing and committing to share data among partners
This workshop refines and expands the use case designed in 2.2.1 Understanding Data Governance and Setting the Goal by identifying data sources, lifecycle stages, and the roles of stakeholders in data management, with a focus on ensuring interoperability through APIs like Next Generation Service Interface with Linked Data (NGSI-LD) for future reuse. Participants —including technical and domain expertise roles— build on the initial use-case diagram (Workshop 1.1 Mapping your Use Case) to map data flows, transformations, and tools, while also addressing storage, integration, and potential open data publishing.
Workshop 2.3: Inventorying your LDT Projects' Data: Unlocking Interoperability, Listing and committing to share data among partners
PDF coming soon — contact the project team in the meantime.
2.4 Identifying Levers, Obstacles and Objectives for Interoperability: From Awareness to Actionable Strategies for LDT Projects
This more technical workshop introduces participants to interoperability and highlights its importance from the outset of a data project, helping them in identifying obstacles, levers and levels of interoperability (technical, syntactic, semantic, governance). Through a collective diagnosis using the visual exercise known as 'Speed-Boat' (anchors = brakes, sails = levers, island = objectives), teams prioritise needs, share feedback and define concrete short-term actions. The workshop anticipates interoperability issues (data silos, incompatible formats, lack of governance) and equips teams to avoid them by building a shared vision between business lines, technical teams and decision-makers. It facilitates the integration of requirements into specifications and prepares additional actions to ensure usable, interconnected and sustainable data in the following stages.
Workshop 2.4: Identifying Levers, Obstacles and Objectives for Interoperability: From Awareness to Actionable Strategies for LDT Projects
PDF coming soon — contact the project team in the meantime.
BONUS Lego® Serious Play: A Transversal Tool to Unblock and Deepen Data Governance Challenges
The Lego® Serious Play workshop transforms abstract governance and project challenges into tangible, visual models, fostering shared understanding and creative problem-solving among diverse stakeholders. By moving beyond traditional formats, it unlocks original solutions and highlights gaps or unresolved issues before implementation. Teams can tackle challenges like: Designing governance frameworks (internal/external); Building IT architectures (e.g., hypervisors); Prototyping ideal user journeys or training action plans; Aligning cross-territory partnerships for shared data use cases. The hands-on approach ensures flexibility and clarity, making complex ideas adaptable and actionable.
Workshop BONUS: Lego® Serious Play: A Transversal Tool to Unblock and Deepen Data Governance Challenges
PDF coming soon — contact the project team in the meantime.
✨ Achievements at the end of the stage
At this stage of the method, the following elements have been achieved or identified:
- Validated use cases with tested assumptions and feasibility assessments.
- Technical, legal, and operational constraints documented and addressed.
- Refined stakeholder roles and governance structures with clear responsibilities.
- Actionable roadmaps for data governance, legal compliance, and business models.
- Prioritised action plans with timelines, resources, and risk mitigation strategies.
- Stakeholder buy-in and alignment on validated outputs.
➡️ Next: Phase 3 – Prototyping (DEFINE)
Phase 3 – Prototyping (DEFINE)
Prototyping is the stage that transforms a still theoretical project into concrete proof of feasibility. It is not yet a question of producing a finished service, but of rapidly testing a solution on a restricted perimeter, using real data, confronting ideas with technical, functional, and human reality.
This is not a compulsory stage. The previous stages can show that solutions on the market do indeed meet the needs identified, and that prototyping is not a required necessity. Nevertheless, an experimentation stage can always be useful before large-scale deployment.
In the LDT4SSC methodology, the aim of prototyping is twofold: to demonstrate that the idea works, and to check that it has real value for users. It is an iterative, experimental, and frugal approach, which should enable you to learn quickly without committing to heavy investment. The aim is also, from this stage onwards, to rely on a scalable infrastructure, so that you don't have to start from scratch during the deployment phase.
📋 Prerequisites
- Validated use cases, stakeholder maps, and feasibility assessments from the VALIDATE step.
- Technical and operational expertise to define system architecture, data flows, and integration requirements.
- Stakeholder consensus on governance structures, roles, and decision-making processes.
- Access to necessary tools and templates (e.g., system design frameworks, governance charters, project management software).
- Clear strategic alignment with public policies, sustainability goals, and organisational objectives.
🎯 Objectives
- Experiment with concrete solutions using real data and representative users.
- Validate organisational hypotheses.
- Confirm technical feasibility (data access, processing, flow integration, result display, etc.).
- Confirm or refine design choices based on practical feedback.
- Prepare the conditions for future deployment (technical, organisational, legal).
👥 Stakeholders to Involve
- Project Coordination Roles (Project Coordinators, etc.) – They orchestrate cross-functional alignment, timelines, and resource allocation for definition outputs.
- Domain Expertise Roles (Use-Case Owners, Subject-Matter Experts, Researchers, Field Agents, etc.) – They refine use-case specifications and technical requirements, ensuring alignment with operational realities.
- Data Roles (GIS Specialists, Data Engineers, Open Data Officers, Data Scientists, etc.) – They design data architectures and workflows, validating interoperability and quality standards.
- Innovation / Smart City Roles (Smart City Experts, UX/UI Designers, Innovation Laboratories, etc.) – They drive user-centric, innovative design and ensure solutions align with smart city standards and emerging best practices.
- Legal Roles (Data Protection Officers, Legal Experts, Intellectual Property Managers, etc.) – They embed legal and ethical guardrails into governance frameworks and data-sharing agreements.
- End-Users or representatives of civil society (Citizens, Citizens' Associations or Panels, etc.) – They validate user experience and accessibility of proposed dashboards or tools.
- Technical Roles (IT Department Staff, External Service Providers, Technical Experts, etc.) – They provide early technical validation of system integration or scalability constraints.
DEFINE Resources
3.1 Prototyping a Use Case with a Context Broker: A Step-by-Step Technical Guide for LDT4SSC Pilots
These slides are an optional but practical resource for pilots who want to technically implement a use case using a context broker, completing the PROTOTYPING–DEFINE phase of the methodology. They walk through four steps: (1) accurately defining needs (purpose, data inventory, functionalities); (2) modelling and contextualising data using existing standards, ontologies, and a cross-functional repository; (3) integrating data into a platform via ETL pipelines, converting to NGSI-LD format; and (4) exploiting the data through dashboards, business applications, open data publications, or inter-system reuse. The approach is illustrated with the energy consumption use case from the City of Paris, and is transferable to any use case.
Methodology. Prototyping your Use Case with a Context Broker: A Step-by-Step Technical Guide for LDT4SSC Pilots
PDF coming soon — contact the project team in the meantime.
✨ Achievements at the end of the stage
At this stage of the method, the following elements have been produced or identified:
- A prototype that meets the use case.
- Reusable knowledge model(s).
- The code used to produce the algorithms or models.
- Documentation of the prototype.
It is then about expanding user testing, in a logic of progressive test/iteration, to arrive at a validation (or not!) from the community on scaling up. At that moment, we are at T0 of the cost-benefit analysis method (see workshop 1.2 Questioning the Purpose of your LDT Project).
➡️ Next: Phase 4 – Deployment (IMPLEMENT)
Phase 4 – Deployment (IMPLEMENT)
Deployment is the final stage, marking the transition from experimentation to implementation. Having demonstrated the feasibility of a project through a prototype, it is now a question of getting it used by all the end users within the organisation. This phase involves stabilising the prototype, making it reliable, and putting in place maintenance so that it becomes a long-term tool.
During this phase, the project's technical infrastructure, its economic model, and the legal framework for its use will be finalised, and a deployment action plan will be drawn up, involving in particular the acculturation, training, and onboarding of all staff.
Ideally, most of the subjects covered in this stage (business model, legal framework, staff familiarisation) may already have been addressed upstream, so the aim here is to formalise the concrete elements arising from these discussions.
This stage may also enable the project to be scaled up, either within the same region, or through re-use or pooling with other local authorities.
📋 Prerequisites
- Finalised project blueprint from the DEFINE step, including technical specifications, governance models, and action plans.
- Secured resources (budget, technology, personnel) for deployment and operation.
- Stakeholder readiness and commitment, including trained teams and clear communication channels.
- Established monitoring and evaluation frameworks to track progress and measure impact.
- Compliance with legal, ethical, and regulatory requirements, including data protection and interoperability standards.
🎯 Objectives
- Deploy the Local Digital Twin (LDT) platform based on the defined architecture, governance frameworks, and action plans.
- Execute operational workflows, ensuring seamless integration of data sources, tools, and stakeholder processes.
- Monitor and evaluate performance against established KPIs, adjusting strategies as needed for optimal outcomes.
- Ensure stakeholder engagement and capacity-building to support adoption, training, and long-term sustainability.
- Document lessons learned and best practices for scalability, replication, and continuous improvement.
👥 Stakeholders to Involve
- Project Coordination Roles (Project Coordinators, etc.) – They oversee implementation timelines, stakeholder communication, and risk management.
- Data Roles (GIS Specialists, Data Engineers, Open Data Officers, Data Scientists, etc.) – They manage data pipelines, quality control, and real-time monitoring of the LDT system.
- Technical Roles (IT Department Staff, External Service Providers, Technical Experts, etc.) – They execute platform deployment, integration, and troubleshooting, ensuring operational readiness.
- Legal Roles (Data Protection Officers, Legal Experts, Intellectual Property Managers, etc.) – They ensure ongoing compliance with data protection, licensing, and contractual obligations.
- Domain Expertise Roles (Use-Case Owners, Subject-Matter Experts, Researchers, Field Agents, etc.) – They support field-level validation and troubleshooting of use-case-specific issues.
- End-Users or representatives of civil society (Citizens, Citizens' Associations or Panels, etc.) – They provide feedback on usability and impact, enabling iterative improvements post-deployment.
- Other Local Authorities facing similar issues – They enable cross-city knowledge exchange and replication of successful deployment strategies, fostering scalability and shared learning.
IMPLEMENT Resources
4.1 Onboarding & Acculturation in Digital Projects: Engaging Stakeholders, Defining Training Paths, and Building a Sustainable Adoption Plan
This workshop fosters staff and stakeholder commitment to data projects by clarifying their roles, benefits, and required engagement levels, while tailoring awareness-raising and training initiatives to create a collaborative, data-driven culture. Participants map stakeholders into three tiers —stakeholders directly contributing to the project, the ones indirectly involved and citizens— defining tailored knowledge, key messages, and engagement methods (e.g., training, demos, interactive tools), culminating in an operational action plan for sustainable adoption. By embedding the human dimension early, it aligns technical teams, business units, and decision-makers, ensuring shared understanding and skills development. The outputs —audience maps, messaging frameworks, and action plans— serve as a blueprint for community engagement, reinforcing project resilience against organisational or regulatory shifts.
Workshop 4.1: Onboarding & Acculturation in Digital Projects: Engaging Stakeholders, Defining Training Paths, and Building a Sustainable Adoption Plan
PDF coming soon — contact the project team in the meantime.
4.2 Designing a Structured Action Plan: From Ideas to Execution for Your Use Case
This workshop helps participants develop a practical action plan for implementing their use case, whether during deployment or earlier planning stages. Using insights from prior workshops (e.g., Lego or Use-Case Mapping), teams identify key steps around the four dimensions: legal, technical, organisational, and political and organise them into a timeline with parallel actions and dependencies. Participants then script three implementation scenarios, balancing constraints and opportunities while preserving the project's core objectives. The process clarifies priorities, anticipates obstacles, and provides decision-makers with clear, adaptable options to align expectations and streamline execution.
Workshop 4.2: Designing a Structured Action Plan: From Ideas to Execution for Your Use Case
PDF coming soon — contact the project team in the meantime.
4.3 Designing a Sustainable Business Model: Funding, Valuation, and Deployment Strategies for Your Project
This workshop helps participants identify and structure financial levers —such as cost savings, subsidies, partnerships, or data-driven services— to ensure the sustainability and deployment of their project (experiment, data service, or digital infrastructure). Teams explore economic models, map resources, partners, and funding sources, and assess legal, technical, and organizational feasibility to define viable revenue-sharing and risk-management strategies. By integrating financial planning early, it secures project viability, aligns funding with objectives, and fosters public-private collaboration. The outputs —model mappings, feasibility analyses, and cost estimates— provide a compelling case for decision-makers and investors.
Workshop 4.3: Designing a Sustainable Business Model: Funding, Valuation, and Deployment Strategies for Your Project
PDF coming soon — contact the project team in the meantime.
4.4 Refining the Business Model: Designing, Testing, and Refining Your Strategy with a Canvas
This workshop enables participants to iteratively develop and validate a robust business model using the Business Model Canvas, ensuring that all strategic, operational, and financial dimensions are aligned with project goals and stakeholder needs. Its key outputs include a fully populated and refined Business Model Canvas, a prioritised set of actionable strategies with clear responsibilities and timelines, and a documented validation process incorporating stakeholder feedback, thereby providing a structured, adaptable, and implementation-ready framework for sustainable project deployment.
Workshop 4.4: Refining the Business Model: Designing, Testing, and Refining Your Strategy with a Canvas
PDF coming soon — contact the project team in the meantime.
4.5 Completing your Data Cooperation Canvas (DS4SSCC): Developing Multi-Stakeholder Data Cooperation
This workshop aims to unlock the power of collaborative data-sharing through a hands-on, interactive experience designed to help participants define, structure, and implement multi-stakeholder data initiatives with clarity and purpose. Over two and a half days, participants will map objectives, identify key partners, design data flows, and build actionable governance models, turning abstract ideas into a tangible roadmap for trustworthy and sustainable data cooperation. Whether they are tackling smart city challenges, public sector innovation, or cross-organisational projects, this workshop equips them with the tools, frameworks, and stakeholder alignment needed to transform data into shared value.
Workshop 4.5: Completing your Data Cooperation Canvas (DS4SSCC): Developing Multi-Stakeholder Data Cooperation
PDF coming soon — contact the project team in the meantime.
✨ Achievements at the end of the stage
At this stage of the method, the following elements have been achieved or identified:
- An action plan to scale up the project (acculturation, adoption, next steps, links to other use cases, etc.).
- A list of funding and revenue sources to ensure the project's long-term viability and the foundations of the business plan.
- A clear vision of the collaborations to be established with new partners around data for future use cases.
- Deployed LDT platform with integrated data sources and operational workflows.
- Functional dashboards and tools tailored to end-user needs.
- Established data pipelines ensuring quality, interoperability, and real-time monitoring.
- Trained stakeholders (staff, partners, end-users) with capacity-building initiatives.
- Documented lessons learned and best practices for scalability and replication.
- Ongoing evaluation framework to measure impact, user feedback, and continuous improvement.
➡️ See also: Cost-Benefit Analysis | Legal Guidance