Co-Creation Method
1. Summary
Developing a data space is complex—balancing business and organisational aspects, as well as technical aspects while ensuring sustainability. The Co-Creation Method provides a structured, step-by-step approach to help data space participants navigate these challenges, ensuring informed decision-making and efficient collaboration. The Co-Creation Method will guide data space initiatives through the different stages of the development cycle, which is relevant for the evolution of the data space.
2. Purpose of the Co-Creation Method
The Co-Creation Method is a collaborative approach that ensures all participants in a data space's development process have their interests aligned and voices heard. It addresses the business and organisational, and technical-related questions that arise, which are interdependent and require coherent answers.
The Co-Creation Method guides participants through a sequence of questions directly connected to the building blocks, helping to determine the most appropriate implementation. Blueprint v2.0 includes flowcharts and explanations of development processes, as well as the purpose of each development process, which are then divided into steps that contain the co-creation questions.
3. Why use the Co-Creation Method?
Do you run into the following questions whilst developing your data space:
How should I integrate all of these different components in a single data space?
How do I balance business and organisational aspects with technical aspects?
Where should I start in the first place when developing a data space?
How do I create an inclusive process in which all relevant stakeholders can make decisions together?
These types of questions are answered in and through the co-creation method. You will get an idea on what questions you need to answer, at what point in time. Additionally, the co-creation method helps you to determine when to make a decision on a specific point. This helps you to continue in the process of developing a data space.
You can use the co-creation method both when you are developing a data space (together with partners) or when you are guiding other parties to help develop their data space.
4. Different starting points of the data space
There are different reasons as to why a data space is developed: a way to quickly scale your services to your clients, or a way to achieve sovereign data sharing. Whatever the reason or starting point for the data space is, the DSSC is of the opinion that each data space requires clarity on a multitude of topics. We believe we have found the optimal order in which these topics should be addressed, however that might not be the order in which you (want to) address these topics.
Reasons why a data space could be a good option are (but not limited to):
There are several use cases for which a party needs to consistently share data and services with other parties;
The problem requires me to share data with a large number of stakeholders;
I need a scalable infrastructure to provide my services;
I want to create a platform which creates an level playing field;
I want to avoid a vendor lock-in;
I want to retain data sovereignty.
4.1 Starting Point
Perhaps you have already developed some business and organisation or technical aspects before you started reading the Co-Creation Method. That is no problem, and the Co-Creation Method could still be helpful in your journey to setting-up a data space.
If you have already worked-out (parts of) the governance structure:
You will probably go more quickly through development processes 1 and 3 (Align Stakeholders on the Data Space Scope and Establish Organisational Form respectively). It might still be good to go through them as a checklist to see if you have forgotten anything.
Focus on development processes 2 and 4 (Develop Use Cases and Identify Functional Requirements and Functional Analysis and Data Space Design respectively). In particular, make sure your chosen governance structure properly facilitates the use cases and technical infrastructure which you need to make the data space work.
If you have already worked-out (parts of) the technical infrastructure:
You will probably go more quickly through development process 4 (Functional Analysis and Data Space Design).
Focus mainly on the other development processes (1 through 3 and 5). Make sure to continuously check whether there is a clear business model for each of the stakeholders. Additionally, ensure your technical solution, supports the required use cases.
If you already have defined the exact use case you want to start from:
You will probably go more quickly through development process 2 (Develop Use Cases and Identify Functional Requirements).
Spend additional time on the first process (Align Stakeholders on the Data Space Scope) to make sure the group of stakeholders you are working with is the right group to further develop the data space. Make sure you are not missing an important stakeholder.
If you already have a clear idea of what offerings you want to provide:
Make sure to spend enough time on development processes 1 and 2 (Align Stakeholders on the Data Space Scope and Develop Use Cases and Identify Functional Requirements respectively). As this will help you define the group of stakeholders which are most relevant to you. Furthermore, this will help you define the business model and business case for your offerings.
4.2 Do your research
Setting-up a data space can in some ways be a lot like setting up a regular company. Therefore it is good to check a number of things upfront before engaging in a potentially costly endeavor:
What is the problem I want to solve, and why is the data space the right solution?
If you can resolve the problem by establishing a single API for example, it is most likely not worth it to set-up a data space, unless there are additional reasons.
Is there already a data space available which I could join to achieve my goals?
Making a quick calculation, is there enough value/a high enough margin for the infrastructure of a data space to be financed?
Is the issue that the data space is addressing important enough for the stakeholders I want to involve (as a rule of thumb, if it is outside of the top 3 problems for a stakeholder, it might be difficult to convince them to join the effort)?
4.3 Necessary before starting with the Co-Creation Method
To start with the Co-Creation Method it is generally recommended to have the following in place:
Coalition of the willing: A group of stakeholders that are interested in sharing data, preferably a group with different types of stakeholders, that are willing to put time and effort in.
Orchestrator: There needs to be one party which guides and coordinates this process from beginning to end. Preferably that is a third party which helps and guides the stakeholders through the process. It is easier for a third party to be independent. However, it can also be one of the parties that will be part of the data space. This party could eventually become (part of) the governance authority, although it does not have to. Other responsibilities for the orchestrator might involve:
Facilitating collaboration between different participants;
Ensuring compliance with legal and technical standards.
5. Data space processes
The Co-Creation Method defines two types of data space processes: Data Space Development Processes and Data Space Operational Processes. We use the following definitions for these processes:
Development Processes: The development processes are designed to guide stakeholders through the essential steps required to establish and continuously develop a data space. During the development processes operational processes are designed.
Operational Processes: A set of essential processes a data space participant goes through when engaging with a functioning data space that is in the operational stage or scaling stage. The operational processes include attracting and onboarding participants and publishing and matching use cases, the data space offering, data requests and, eventually, data transactions.
The combined data space processes provide an overview of what steps and actions must be taken to set up, and further develop a functioning data space. Data spaces face inherent uncertainties from unvalidated hypotheses and external factors, requiring an iterative deployment approach to quickly get feedback from practice.
6. Future topics
We still want to develop the Co-Creation Method. Currently, it explains what to consider in the Blueprint but does not touch upon how to choose between the different steps. Therefore, in future versions, we aim to expand the Co-Creation Method in the following manner:
KPIs and Metrics: These will allow us to measure performance, track progress, and identify areas for improvement. They will be specifically crafted for data spaces to ensure that data spaces and data space initiatives can make informed decisions, optimise processes, and achieve strategic goals. This approach provides metrics and key performance indicators that data spaces can use to monitor the data space’s performance, and allow for corrective action when targets are not met.
Workshops: Workshops are needed to allow the discovery of how to make decisions. The workshops will aid the data spaces and data space initiatives in compartmentalising the development of the data space. In case functionality needs to be added once the data space is operational, the workshops will decrease the amount of time required to design new functionality. Depending on the maturity or need of the data space, parts of the development processes can be skipped.
Cross-Data Space Questions: Currently, the Co-Creation Method explains how to set up and operationalise an individual data space. However, providing guidelines on collaboration with other data spaces in its development will be a valuable addition, especially in the context of common European data spaces. In future versions, cross-data space questions will be added to provide guidance on where to consider cross-data space collaboration and interoperability.
Change Management: Change management plays a crucial role in ensuring the data space is regularly reviewed. Reviews are necessary to assess whether the development of the data space is and will remain properly aligned with the business goals and organisational strategy of the data space in the context of the evolving needs of the data space.
A robust change management framework is essential in the dynamic landscape of data spaces, where technologies, regulations and business objectives are constantly changing. This framework facilitates the systematic examination of existing processes, identifying potential misalignments with development goals and determining whether adjustments are required. By fostering a culture of adaptability and responsiveness, change management ensures that data spaces can proactively address challenges, capitalise on emerging opportunities and optimise their processes to stay in sync with overarching development objectives. In future versions of the development processes, concrete methods of establishing and executing this change management framework within the data space will be added.
Expansion of Operational Processes: Currently, the focus of the operational processes is on the critical client flow. However, a data space should facilitate more processes to run properly. In future versions, additional operational processes will be added like (onboard and offboarding of participants, adding offerings, adding use cases, service provider onboarding, etc.). Furthermore, the current operational processes will be explained in more detail.
7. Further reading
Berkers, F., Gilsing, R., Lamerichs, G., (2022) Deliverable 2.3: Archetypes and methodology for designing Governance & Collaborative Business Models for 0FLW Data Space and Applications. ZeroW Project, Grant Agreement no. 101036388 – This project report describes archetypes of collaborative business models and governance models for data spaces and shows how they are connected.
Gilsing, R., Berkers, F., Lamerichs, G., Dalmolen, S., Cornelisse, E., Van den Berg, W., Van Houwelingen, G., Trifkovic, K., Bunderla, M. (2023) Deliverable D2.6 Methodology and learnings from the prototype kit. ZeroW Project, Grant Agreement no. 101036388 – This project report describes a practical approach for developing collaborative business models for data spaces in conjunction with governance.