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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.

How important is this?

65 votes, average: 4.29 out of 565 votes, average: 4.29 out of 565 votes, average: 4.29 out of 565 votes, average: 4.29 out of 565 votes, average: 4.29 out of 5 65
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Total votes:

Is this feasible?

  • Yes 73%
  • No 27%
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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).

How important is this?

53 votes, average: 3.98 out of 553 votes, average: 3.98 out of 553 votes, average: 3.98 out of 553 votes, average: 3.98 out of 553 votes, average: 3.98 out of 5 53
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Total votes:

Is this feasible?

  • Yes 70%
  • No 30%
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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)

How important is this?

55 votes, average: 4.24 out of 555 votes, average: 4.24 out of 555 votes, average: 4.24 out of 555 votes, average: 4.24 out of 555 votes, average: 4.24 out of 5 55
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Total votes:

Is this feasible?

  • Yes 77%
  • No 23%
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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

How important is this?

50 votes, average: 3.92 out of 550 votes, average: 3.92 out of 550 votes, average: 3.92 out of 550 votes, average: 3.92 out of 550 votes, average: 3.92 out of 5 50
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Total votes:

Is this feasible?

  • Yes 78%
  • No 22%
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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

How important is this?

51 votes, average: 4.37 out of 551 votes, average: 4.37 out of 551 votes, average: 4.37 out of 551 votes, average: 4.37 out of 551 votes, average: 4.37 out of 5 51
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Total votes:

Is this feasible?

  • Yes 83%
  • No 17%
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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.

How important is this?

47 votes, average: 3.94 out of 547 votes, average: 3.94 out of 547 votes, average: 3.94 out of 547 votes, average: 3.94 out of 547 votes, average: 3.94 out of 5 47
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Total votes:

Is this feasible?

  • Yes 82%
  • No 18%
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