# Mastering all technical data space challenges

> Albert Einstein: *"If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and 5 minutes thinking about solutions."*

**Target audience:** People making technology/architecture choices for data space initiatives or advising in such decisions.

**Session objective:** Foster a pragmatic and problem-based approach to the ongoing analysis and development of the data spaces technology landscape.

**Session output:** List of 30 well-defined most essential questions for the data space initiatives lead architects, CTOs etc., to answer. (DSSC may later publish this list)

In line with the quote from Einstein, we will collaboratively create a well-defined set of fundamental questions that the CTOs or architects in the data space initiatives can work to answer.

## What questions must any data space technology officer try to answer?

Add your name and your own questions in the list below:

**Sebastian Opriel (Sovity)**

- How to gain traction and onboard participants (overcome cold start problem)?
- Do you need a closed (i.e., data space rules apply; e.g. centralized identities with DAPS) or open (e.g., decentralized; e.g. SSI) Data Space?
- Do you need logging of participant activities e.g., for compliance?
- Do you need and which Usage Policies do you need?
- How sensitive are exchanged data (i.e. those, who have never been shared before or, now are shared via new DS technology, or have been openly shared before)?
- Which data space archetype do you follow (i.e. which use case types to you foresee)?
-- Data Marketplaces for selling/buying data (MDS)
-- Use Cases for optimization (C-X)
- In case of use cases: How does your data-sharing chain look like? And which requirements derive from that.
-- An Example: Supply chain in automotive industries: (m suppliers and n customers per participant = m+n connections) for each of the x participants in the supply chain = x*(m+n) connections per one supply chain wide use case. Thus, the technology must be extremely scalable and easily to be roll out.

**Antti 'Jogi' Poikola (Sitra / DSSC)**

- Who is who: What are the key data space standards, initiatives and architectures?
- What are the commonalities & differences between the approaches?
- What are compatible now or converging in the future?
- What are the diverging and competing approaches (need to choose between)?
- Level of traction & adoption of the different approaches (speed of development and sustainability over time)?
- How stable are the current specifications?
- What is the status of implementation (code)?

**Alex Tourski (Postplatforms)**
- what is Data Space? I noticed that most specialists fail to answer it. E.g. at Post-Platforms Initiative we see it this way: By Data Space we mean the “Google Doc effect” when actors work at the original data ot the source: e.g. when the city office changes the address of the house, the Cadastre document will reflect it immediately, as both city records and Cadastre records are kept at the house POD.
- how to get rid of monopoly of ALL platforms?
- how to get rid of data silos and keep data at the source?
- shouldn't we have one Data Space for all domains? as it is impossible to define where culture becomes tourism and where tourism becomes transport.
- how to return data to all people and organizations?
- how to return "relational data" to people? By "relational data" I mean all "likes" and "dislikes", all comments other people leave at all platforms we interacted with. If we get back all this data, we can calculate a kind of e-Karma, a cumulative rating.
- how to get rid of hundreds of logins/passwords and have one key to enter any platform, sign docs, get money from ATM, open a hotel room?
- how to protect the authors right and provide full-scale provenance to data owners?
- how to introduce e-money?
- how to answer the question "how much money have all people who voted for candidate XYZ?" without exposing these people?
- how to rollout Data Space?
- how to get rid of Fake news in Media?
- how to establish an open IoT infrastructure? E.g. When the company acquires an excavator, its insurance company, accounting department, the service company will get this excavator immediately into their systems.
- how to help corporations to overcome the issue of hundreds of platforms/systems they use? E.g. how to establish the situation when different accountants in the accounting department can choose their favorite platforms (e.g. SAP or Oracle Suit) and still work within the same accounting data space?
- how to make Internet a super storage for 500+ years, so that neither people nor companies do not have to backup data any more?

**Sebastian Steinbuss (IDSA)**

- Being a potential consumer/provider/prosumer of data and|or services, what kind of tooling do I need to join a dataspace
- Being a potential consumer/provider/prosumer of data and|or services, which are the base technologies that I must be able to master, What kind of capabilities do I need in my organization, which expertise do I need in my team and what are the Business Units that I would have to connect to?
- Being a potential consumer/provider/prosumer of data and|or services, what do I have to do with my data and services (techniacally) to "polish" them as a data asset in data space? How do I find data and services in a dataspace?
- Being a potential consumer/provider/prosumer of data and|or services, how can I make sure that potential partners/peers can understand my data and use my services? How do I overcome this from a consumer perspective?
- Being a potential consumer/provider/prosumer of data and|or services, how can I identify access and usage policies for the data I offer or understand and make sure that I stick to those rights and obligations?
- Being a potential consumer/provider/prosumer of data and|or services, which problems are solved by dataspaces and which are the new problems that I get from Dataspaces?
- Being a potential consumer/provider/prosumer of data and|or services, can I do brownfield integration of my legacy systems?
- Being a potential consumer/provider/prosumer of data and|or services, how can I ensure tracability and auditability of transactions in a dataspace, and if I would have this, how can I ensure that the content is kept confidentialy?
- Being a potential consumer/provider/prosumer of data and|or services, is it only about selling data to become rich and famous or do Dataspace also cover data exchange and data sharing to connect my organization to partners in the valuechain/supplychain?
- Being a potential consumer/provider/prosumer of data and|or services, can I provide value adding services in a dataspace and if how, i.e., can I provide a service offering or do I have set everything up in a federated model like federated learning?
- Being a potential consumer/provider/prosumer of data and|or services,is my membership in dataspace visible to others? Can I control who can see my memberhships, my data, my services?
- As an ecosystem/dataspace, how can I express the rules of this community and how can I manage the onboaring and offboarding to this group from a technical perspective (not the administrative process), what is the digitial membership card of the community members?
- As an ecosystem/dataspace, how can I manage members and keep track if they stick to our common rules?
- As an ecosystem/dataspace, who can provide support and technical asisstance to the members?
- As an ecosystem/dataspace, who can provide services that are required to build a data space? How can those be set up and operated? Are centralized services required? Is everything decentralized?
- As an ecosystem/dataspace, how can I federated/join/interact with other dataspaces?

# Synthesis of the questions

What kind of tooling the potential participants need to join our dataspace?

What base technologies the data space participants must be able to master?

- What capabilities and expertiese the data space participants need in their organization/team and what business units should know about the data spaces?

- What the data providers have to do with their data and services to "polish" them as data products in our data space?

- How the data receivers and users find relevant data and services from our dataspace?

- How the data- and service providers can ensure that other participants in our data space can understand and use their data services?

- How the data rights holders can identify access and usage policies for their data and how the data users can understand and follow those policies?

- What problems our data space solves for the participants and what new problems arise?

- How participants of our data space can integrate the data space to their legacy systems?

- How the participanst can ensure tracability and auditability of transactions in our dataspace and ensure that the content is kept confidentially?

- How our data space supports the participants to connect with relevant partners in the valuechain/supplychain?

- What kinds of value adding services the participants can offer in our data space and how?

- Is the membership in dataspace visible to others and can the participants control the visibility of their memberhships, data and services?

- How we technically express the data space rules and manage the onboaring/offboarding of members – what is the digitial membership card of the members?

- How we can manage members and keep track if they stick to our common rules?

- How / who provide support and technical asisstance to the members of our data space?

- Who can provide services for us to build and operate our data space?

- What is our approach to decentralisation, what parts of the data space servicers and goverance can be centralised and what has to be distributed?

- How can we become interoperable / federated or interact with other dataspaces?