Big Data lay at the core of the strong data economy that is emerging in Europe. Although both large enterprises and SMEs acknowledge the potential of Big Data in disrupting the market and business models, this is not reflected in the growth of the data economy. The lack of trusted, secure, ethical-driven personal data platforms and privacy-aware analytics, hinders the growth of the data economy and creates concerns. The main considerations are related to the secure sharing of personal and proprietary/industrial data, and the definition of a fair renumeration mechanism that will be able to capture, produce, release and cash out the value of data, always for the benefit of all the involved stakeholders.
DataVaults aims to address this kind of concerns that pertain privacy, ethics and intellectual property rights , by allowing individuals to take ownership and control of their data and share them at will, through flexible data sharing and fair compensation schemes with other entities (companies or not).
DataVaults aims to deliver a novel framework and architecture that leverages personal data, coming from diverse sources (sensors, IoT, wearables, data APIs, historical data, social network data, activity trackers, health records, demographic profiles, etc.) to help individuals construct their unified personal data hub, collect at a single point all of their personal data in a secure and trusted manner, and retain ownership and control on what to share and with whom, receiving also compensation for the artefacts they place at the disposal of other third parties. In turn, third party organisations (companies, public sector, NGOs, etc.) arrive at a position where they can request and get access to tons of personal data, which can complement the ones they already manage and that can be used for generating more efficient, effective and value added services, engaging with individuals into an entirely new way for data sharing, which generates trust and an increased feeling of collaboration, as the data owners (e.g. individuals) become the centre of attention and the most important partner and collaborator of those third parties.
At the core of DataVaults lies the DataVaults personal data value chain which could from now on be seen as a multi-sided and multi-tier ecosystem governed and regulated by smart contracts to safeguard personal data ownership, privacy and usage and attribute value to all entities that generate value within this chain and especially data owners. DataVaults will deliver a framework and platform that will set, sustain and mobilise this ever-growing ecosystem for personal data sharing and for enhanced collaboration between those who own data (data owners) and those who seek data (data seekers).
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.
- Data Seekers (Economic Operators: 1st-tier economic operators, that look for enjoying business intelligence based on Primary Personal Data. In this tier, data seekers (organisations of any type) 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). 2nd-tier economic operators that provide data and services based on analytics or data that is shared and generated by the 1st-tier economic operators.
DataVaults will provide the following services to enable users make the most out of their personal data while having maximum control over them:
- Holistic Personal Data Management: Personal data management services, including collection, mining processing, normalisation, formatting and availability at individuals’ personal devices level as well as on secure data vaults on the cloud
- Smart Data Interlinking: Personal data are linked to open, linked as well as proprietary data following Linked Data principles and openly (re-)publishing non-sensitive and business critical information to the LOD community
- Novel Data Security: Cryptography, data anonymisation and privacy preservation, remote attestation and trusted data exchange through the utilisation of TPM technologies between the Personal DataVaults and the DataVaults cloud-based engine
- Privacy Risk Assessment: Methods that offer a “situational awareness” picture to individuals with easy to understand privacy metrics, revealing the true risk exposure factor of individuals based on the shared data
- Privacy Preserving and Data Secure Retention Mechanisms: Accommodate the generation of anonymised “digital twins” of individuals, as well as specimen clusters (“persona groups”) to empower group analytics that contain valuable insights without violating privacy principles
- Twin-fold Data Brokerage Engine: A data brokerage engine to cater for IPR and data license safeguarding, documenting transactions in a privacy preserving, yet indisputable and unforgeable manner, facilitating compensations schemes with third parties (that support the shift to future monetisation streams) through the instantiation of multi-layer real-time micro-contracts specifically tailored to the needs of data sharing, redistribution and utilisation, constructing a bridge between personal data and industrial data platforms
- Edge and Centralised Analytics: Smart balancing of analytics methods to accommodate Edge Analytics as well as centralised operations depending on the degree of data volume, velocity and variety, always in conjunction with the security and privacy modalities allowed by the individual for each kind of analysis. Provision of intuitive analytics, reports, smart dashboards and visualisations tailored to the needs of each stakeholder of the domain, including the individual, as well as generic ones for wider use by any interested organisation and by the public