The Project

The strong growth of the data economy is hampered by the lack of trusted, secure and ethical-driven personal data platforms and privacy-aware analytics methods, capable of both securing the sharing of personal data and defining how value can be captured, produced, released and cashed out for the benefit of all the stakeholders involved.

The data value chain that is tackled by DataVaults can be seen as a structure of a trusted cycle, which includes:

  • Primary Personal Data Providers (Individuals). This tier includes all the individuals which are generating and collecting their personal data from various services, devices and applications. It is these data which is considered “personal” and constitutes the core data of that is of interest of the DataVaults project.
  • Economic Operators. These are data seekers (also titled as 1st-tier economic operators), that look for enjoying business intelligence based on Primary Personal Data. In this tier, data seekers (organisations of any type, including public administration) are able to work on the data of the first tier (primary data) and combine them with other types of data they have to create new datasets or relevant derivatives (insights, reports, etc).

Beside these two main actors, DataVaults aims also to attract a third category, which can be seen as 2nd-tier economic operators that provide data and services based on analytics or data that is shared and generated by the economic operators which belong in the core data sharing cycle (1st-tier). Such stakeholders are interested to provide services that are based on reused/resold data. In a typical scenario, the value generated by organisation of this tier does not flow back to the data owners, as business deals are restricted between the Tier 2 (demand) and Tier 1 (supply) entities. By exploring the value that can be generated through these tiers, DataVaults aims to capitalise on such existing modern technological breakthroughs in the areas of the data-driven economy, and roll out a completely new, trusted and secure value chain of interrelated data streams coming from individuals (personal data) in order to revolutionise the way personal data can be managed and shared with interested stakeholders, demonstrating a huge, but realistic economic and societal impact that can being achieved by introducing a fair and well balanced economy build around personal data, that will be linked to various sectors whose services rely on, or are interested in sourcing and analysing such data.

The project will last three years and is co-ordinated by the Fraunhofer Institute (Germany), it includes 17 partners from 9 different EU countries and 5 demonstrators: Italy (Municipality of Prato), Greece (Municipality of Piraeus and Olympiakos), Belgium (Andaman7) and Spain (MIWEnergia).

The Objectives

The project aims at meeting 7 SMART objectives, as summarised in the following tables.

ObjectiveAimKey Output
Business Objective I
To deliver a pan-European Personal Data Platform, compliant with EU regulations, national laws and adopting high security and privacy primitives, which can be used by any individual for storing collecting and sharing, after consent, personal data (or derivatives), validated and populated through a set of representative, long lasting (24 months) demonstrators.DataVaults Infrastructure, DataVaults cloud-based platform, DataVaults Personal App, DataVaults Demonstration Scenarios.
Business Objective II
To instantiate a novel business model for personal data and insights sharing where data is valued based on different modalities and is attributed to the rightful owners though trusted smart contracts that dictate usage and access rights, placing data owners as the starting point of the value chain and offering to them benefits and full control of their data and the way the latter is used.DataVaults Trusted Data Management and Sharing Principles, DataVaults Personal Data Sharing Business Model, DataVaults Value Distribution Method, Smart Contract Patterns and Templates for Stakeholder Collaboration and SLAs.
Business Objective III
To cultivate a trusted sustainable and ever-growing ecosystem where individuals can constantly enjoy benefits and organisations from diverse domains can take advantage of accessing (after consent) a multitude of personal data (or derivatives), renovating the way they operate by expanding their offered services.DataVaults Public Showcase and Web Presence, Marketing Kit, Exploitation and Marketing Plan, Dissemination and Stakeholders’ Engagement Plan, Events and Workshops, Publications and Press material.
Technical Objective I
To deliver an technical solution comprising of secure and trusted Data Management and Analytics cloud based platform as a Service, coupled by Personal Data Apps, for storing, manging, sharing and monetizing over personal data (derivatives) which can be used by any individual with the aim to capitalise on the real value of his personal data, without dropping control of ownership or loosing track of the usage methods, providing also constant awareness of the privacy, security and risks he may be exposed at by sharing such data.DataVaults cloud-based platform, DataVaults Personal App, DataVaults Personal App libraries, Data Model, DataVaults Open API, Data brokerage engine, Documentation and Usage manuals.
Technical Objective II
To integrate existing approaches, tools, libraries and components that allow handling of personal data in the way they should be preserved, accessed, valued, and controllably shared, guaranteeing high quality results which can support rapid prototyping, traction generation, fast market entry and sustainability.Modularised Services and Tools for data management and sharing as part of the platform, a unified data management service to interconnect all other components, improvement and integration of technical data infrastructure solutions supporting both secure and trusted data exchange and retention, a novel paradigm for the documentation and IPR handling of conducted exchanges.
Scientific and Innovations Objective ITo deliver an innovative, secure, privacy preserving, IPR respecting, and fair compensation data exchange methodology, propelling the creation of a joint venture of personal data owners and data seeking organisations.Value Chain definition, Personal Datasets and Data sources, semantic representation of Personal Data, update on existing semantic vocabularies and contributions to LOD, data analysis algorithms.
Scientific and Innovations Objective IITo successfully link novel trusted and security-by-design data mining, management, analysis and sharing techniques, with legislation- and ethics-driven functions, facilitating both privacy and trust preservation, risk situational awareness, easy access to, and usage of valuable information and fair compensation models for all the actors of the value chain.A security and privacy by design Personal Data lifecycle Management framework, an Assets Brokerage methodology, Methods to isolate data and make them searchable even when encrypted, Methods to share data at different levels and modalities, Methods to calculate risk exposure.