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Human centric, fair and thriving data economy

Leading with the vision to the future of data empowered citizens, businesses and societies

The European data economy provides for the wellbeing of people, and fosters a culture of innovations and meaningful work based on the responsible use of data and a human-centric approach.

By unlocking the potential of data, industries are scaling their value-creation capabilities. Data is reused and shared across borders and between sectors in ways that respect the rights to data and that build trust-based relationships in data exchange and value networks.

Through forward-looking policymaking, conditions for data connectivity and interoperability are established to benefit all stakeholders. The use of data is based on reasonable and non-discriminatory terms that drive openness in innovations, fair competition and collaboration.

Data principles have practical impacts on the application of user-centric technologies, scalable service solutions and future-ready infrastructures to pave the way towards inclusive, equitable and sustainable growth.

Data principles guide us to find necessary measures towards a human-centric, thriving and balanced data economy. Share your views on the following principles – and make suggestions how to make these principles even more feasible?

A human-centric, thriving and balanced data economy is based on data use that builds on the rights of individuals, on a fair operating environment for organisations and on a well-functioning society. We need to focus on collaborative measures that effectively balance the different needs of stakeholders for data use. To do this, we need to ensure that all stakeholders are provided with the necessary abilities to use data.

Therefore, data principles are based on the abilities of people, organisations and societies to access, share, act, innovate, trust and learn with data.

Access
Share
Act
Innovate
Trust
Learn

Access

Access by default.  Access to data according to various access rights (e.g. business-to-business, business-to-government) should be facilitated by technical or legal solutions and support.

Access to the necessary data of each sector for various purposes should be provided on fair, reasonable and non-discriminatory terms while respecting rights of individuals and businesses.

Data must be digital in machine-readable format, and if possible available as real-time data. Access to data is provided and controlled through an open programming interface (API) within the entity that provides the data. 

Once-only principle. Data should be stored only once to enable easy access and timeliness of the data.

Publicly funded data sets should be open data and provided through open interfaces for individuals and businesses by default.

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  1. Commentor062

    API access is more useful when an industry/sector collaborates and provides a common standard/format. So when a common standard exists, entities in that sector should be forced to use it (or explain why it should not apply to them).

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  2. Commentor061

    -open programming interface (API) technologies has to be commonly used ones
    -roaddata and data from cars should be as open as possible

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  3. Commentor057

    Secure access and authentication mechanisms will be key to realise this vision, but also education of all citizens. This is what we should aim at: a secure and trusted infrastructure and well-informed citizends on the other.

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  4. Commentor054

    To answer Commentor039 no, no and NO. Absolutely and totally nothing for a multinational organization like EU.

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  5. Commentor048

    Distinction between aggregated and personal data. Access to the latter needs to be justified and governed by consent gateways

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  6. Commentor041

    Once-Only comes in two very different versions –
    1. Governement secondary abuse of citizen data through central profiling.
    2. Citizen-centric where citizens reuse data without transferring control.

    The first version is incompatible with democracy and free markets.

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  7. Commentor036

    The most important question is what rights are provided to businesses and individuals, on the basis of which they can restrict access to information and/or request fees exceeding FRAND terms.
    I do not fully agree with the once-only principle attached to storage. In fact, from a data security principle it is deeply troubling, as the risk of losing data is obvious. However, what I think is meant is that you should not be requested to PROVIDE the same data many times to different authorities etc.

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Share

Reusable by default. Data sets need to be interoperable and harmonised in a structured format to enable flow of data in automated processes.

All new initiatives for the production, collection and processing of data should be based on the principle of interoperability and in mutual reciprocity.

Reusability should be supported by interoperability measures such as

  • open standards and structured data sets
  • commonly used technologies and information systems
  • codes of conduct and model contractual agreements
  • governance structures for data exchange and value sharing in ecosystems.

Restrictions on data sharing should be based on well-defined reasoning at the corporate policy level and should not restrict third-party value creation. 

Conditions for data sharing that is justified by a clear and demonstrable public interests need to be established. Public bodies should ensure that their request for the reuse of private data are balanced (e.g. proportionality, functioning markets).

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  1. Commentor063

    One should take contain not to foster a monoculture. Multiple standards/technologies ensure robustness in case one system fails.

    Reusability should not hamper innovation of new standards/technologies.

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  2. Commentor058

    Of course we must ensure that policy makers, regulators and public authorieties undergo regular audits.

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  3. Commentor047

    The Sitra model is an explicit demonstration of what NOT to do.
    It drives central profiling and undermines both security, economics and trust in government structures.

    Instead – Empower Citizens distributed without “MyData” (man-in-the-middle models – untrustworthy by design).

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  4. Commentor042

    Having data in structured and semantically well-defined formats is essential for synergy.

    The essential question is to AVOID reuse of keys and identifiers, so control can remain citizen-side so citizens are not reduced to objects of control or someones product.

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  5. Commentor037

    Because of private property rights and self-determination of businesses (eg. copyright, protection of business secrets) it is not possible to force private businesses to share their data and/or make restrictions of data sharing subject to reasoning at the corporate policy level.

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  6. Commentor034

    Reusability requires common and open standards. The development is slow and we should point key areas where to start. Standardization bodies should address the data along the technoogies.

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Act

Human-centric by default. Individuals are guaranteed access to their personal data and means to manage the reuse of their data without lock-ins or impediments that inhibit access or portability (e.g. timeliness).

Users should be given full control and portability of their data, while safeguarding privacy.

Transparency and clear terms and conditions to understand how their personal data is used in services and automated decision-making (also by third-parties).

Empowering individuals to manage their data rights requires easy to use tools

  • to manage access to and the reuse of their data (e.g consents)
  • to increase findability and reusability of user-generated contents (e.g metadata)
  • to change service provider (e.g relocate data)

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  1. Commentor064

    “Transparency and clear terms and conditions to understand how their personal data is used […]”
    This should not imply automatic consent. Opt-in (with freely given consent) should be the default.

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  2. Commentor050

    Individuals need more than just tools they need use cases that demonstrate benefits to be had from using tools or manipulating their data. Without this demand will never reach a level that justifies commercial investment.

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  3. Commentor043

    This approach fail 100% as control will always transfer from the citizen to some system we cannot secure

    The essential question is to ensure citizens can remain in control, i.e. that citizens can collect, combine and share data in new context WITHOUT transferring control.

    With this, all the other issues comes natural. Without this, they are illusions.

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  4. Commentor031

    I wpuld say that a) understanding what will happen, then b) giving truly informed consent and c) being able to revoke consent (one a person learns that data is not usef according to stated policy or realizes something which was bot apparent before) are the most importand aspects of any datasharing. Plus an enforcement regime which will be effective in scenarios like “few persons against big multinational”.

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Innovate

Level-playing field by default. Data market access should be open to all on fair and non-discriminatory basis for the benefit of everyone. Undistorted competition in data markets should be guaranteed.

In order to enable innovations, the findability of data and data reusability should be supported by

  • data catalogues, extranets and other published channels
  • commonly accepted data models, standards, ontologies, libraries and schemas
  • functioning licensing
  • mechanisms for balanced value sharing

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  1. Commentor066

    Creating shared ontologies/standard etc. is hard and should be left to the sectors/industries.

    Big Data companies have enormous advantage over smaller companies to collect and use data. E.g. Google collecting speech information to improve speech recognition. By providing more open and publicly available datasets (or stimulation in the creation of those), this can create a level-playing field in numerous areas involving machine learning/big data for smaller companies that do not have easy access to these data.

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  2. Commentor060

    The dream of shared ontologies and commonly adpted standards is in my view difficult to achieve, but we must get there at some point.

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  3. Commentor051

    Given the state of legacy systems considerable investment may be needed to deliver this. A potential role for governments to secure a public good.

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  4. Commentor045

    The essence of enabling innovation is Citizen Centric Once-Only as the most critical element.
    Non-personal data are of course also interesting, but 90% of value emerge in interaction with citizens.

    Only citizens themselves can share data in new context and they need to be able to do so WITHOUT loosing control.

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  5. Commentor044

    Certianly – access to open data is great.

    Meaning no personal data
    Including data that are merely “anonymized” as that would reward surveillance and profiling.

    ONLY citizens themselves can make anonymous or non-personal data about themselves and it has be be seen through the entire value chain.

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  6. Commentor033

    IMHO most difficult part, seeing how GDPR is currently enforced (“slow”, “ineffective”, etc.), how complicated it is (EU citizens vs. US tech giants, etc.) and many other cgallenges.

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Trust

Ethically sustainable by default. Building trust in data use and data-driven technologies requires strong respect for human rights, and transparency, reliability and the inclusion of all stakeholders. Data security and privacy by design should be integral parts of business and service development practices.

Trust is created and maintained by

  • clear responsibilities for data management
  • easily understandable digital services and products
  • transparency (e.g. traceability, explainability, interpretability) of algorithms as well as autonomous and intelligent systems
  • traceability (e.g. logs) and security when processing data throughout data lifecycles
  • use of new technologies and mechanisms that build trust in decentralised data-sharing networks (e.g. blockchain)
  • establishment of accountability for intended and unintended consequences of gathering, processing and using data

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  1. Commentor065

    Trust is also created and maintained by providing free software. This means that the users have the freedom to run, copy, distribute, study, change and improve the software.

    Software created with publicly funded (tax payers) money should by default be released as free software.

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  2. Commentor046

    Anybody taking about trust are not designing trustworthy.

    “Data minimization” is not about consent, anonymization or legitimacy – it is about eliminating personal data altogether.

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  3. Commentor032

    But no need to drag blockchain into this (or else also some “not that cool but equally or even more important” techologies and solutions should be mentioned too. Typical example: EIDAS.

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Learn

Renewal by default. A thriving data economy requires societal change and constant re-evaluation and up-scaling of people’s skills and organisational capabilities.

Education systems should provide opportunities for individuals’ life-long learning in data-driven society. Individuals should actively learn new skills and gain know-how that will help them to adapt and contribute to the data economy.

Organisations should re-think strategic competence building for their needs in data-driven future. This requires also renewal of managerial and organisational culture and practises (e.g. experimentations).

The data economy will require societal changes such as new solutions in legislation, taxation, the social security system, funding and the development of education and training, and in work-based learning mechanisms and structures to support sustainable and holistic competence development.