We are happy to introduce you to the newest research on data markets, technology innovation, and the implementation of data sovereignty. In this edition of the newsletter we will take a look at certain key topics such as use cases in finance and telecommunication, data privacy, data markets, legal framework, and functional requirements. To engage you in some interaction, we added some exciting events at the end. Get involved and let´s innovate the European data market together.
With the TRUSTS project, the European Commission initiates a pan-European solution for data-related issues of the future. Aim: innovating European data markets through trust, security, and federation.
Data sharing shapes the economic and societal future of Europe and bears huge potentials, but also comes with risks and apprehensions. The EU project TRUSTS was established to identify and overcome legal, ethical, and technical challenges of cross-border data markets while upholding European values such as privacy and data protection.
17 international partners combine their knowledge and experience in research and business. They are located in Austria, Belgium, Cyprus, Germany, Greece, Israel, the Netherlands, Romania, and Spain.
To demonstrate and realise the added value of the TRUSTS platform, three business-oriented use cases (UCs) showcase the sharing, trading, (re)use of data and services, and added value generated through innovative applications built on multiple open and proprietary data sources.
The use cases target corporate business data in the financial and telecommunications operator industries.
Use Case 1: The Anti-Money Laundering (AML) compliance use case
The ambition of EBOS, FNET and InBestMe is to classify the business and the technological opportunities that derive from the TRUSTS data marketplace.
Financial institutions, corporate audit depart-ments, tax advisors and many more need to do AML checks. UC1 aims at establishing and validating how data shared via the Platform can feed into an existing AML solution enhanced with big data analytics, for providing faster and more accurate detection of financial crime and money laundering, and how these enriched data can be securely traded via the platform. Artificial Intelligence (AI) and Machine Learning (ML) techniques will be applied and are expected to make a significant and valuable difference in AML.
Use Case 2: The agile marketing through data correlation use case
In this scenario, we establish and validate how big data analytics techniques applied on data shared via the TRUSTS platform can provide timely and meaningful information towards targeting profitable customers at a local level.
The use case will be collecting financial/personal data and telecommunications customers’ data from respective banking and telecommunication enter-prises participating in TRUSTS (Piraeus Bank, FNET). Data will be anonymised by FORTH according to the principles established in the GDPR and company compliance policies ensuring the extrapolation of any private and sensitive information.
Use Case 3: The data acquisition to improve customer support services use case
The TRUSTS Data Marketplace vision is to create an out-of-the-box analytics solution for the anonymisation and visualisation of Big Financial Data, specifically to advance new ways of human-computer interaction currently in their infancy.
The purpose of this demonstrator is the development of an innovative input in the field of debt collections. The idea is that through enhanced analytics, artificial intelligence and the integration of bots, a bank will be able to run a full operation around debt collection without needing to employ agents to follow-up with customers.
Relational Romania in collaboration with the data warehouse of Alpha Bank group, will generate anonymised benchmark datasets using data management procedures that will be set up to transmit all the data.
Author: Gianna Avgousti, eBOS Technologies Ltd, Cyprus
Privacy Preserving Smart Contracts:
Synopsis of a Dell Solution
A blockchain, in its standard configuration, is a structure in which data is available to all participants, in unencrypted form, which presents a problem for applications which require data privacy.
This is because blockchains were not originally intended to be fully private structures, rather they were for integrity checking purposes; logging a verifiable chain of transactions.
Privacy preserving technologies, specifically their application to smart contracts, are an interest of the TRUSTS project smart contracts task.
A more practical solution to privacy issues on a blockchain explored by Dell EMC is the use of hashing algorithms. Each participant stores their private data off-chain using their own infrastructure and places the hash values of said private data on-chain.
Once stored on the blockchain, a given hash value can be used to verify that the generated Hash of a private data artifact matches that which is stored on the blockchain, providing the ability to verify the integrity of data artifacts in a privacy preserving manner.
Any processing of said private data in this solution occurs off-chain, with processing tools, or smart contract programs, being selected via participant-consensus, for example using on-chain voting.
This selected data processing utility will then be greenlighted to push the outcomes of its processing to the blockchain. This allows for non-sensitive inferences about data to be stored on-chain, while protecting the privacy of the underlying source data which was processed.
The addition of Trusted Execution Environments and Secure Enclaves to this solution, within which the selected data processing utilities would run, provides additional robustness; addressing the concern that a dishonest participant may interfere with their instance of the data processing software.
Smart contract software would be run in such a Trusted Execution Environment and then propagate results to the blockchain.
Author: Alan Barnett, Dell EMC, Ireland
Legal regime for data sharing within the TRUSTS project
Data sharing is essential for the functioning of the data marketplace. Whether it takes place between platform partners or with data customers, it generates security, ethics, and privacy issues. Which legal regime applies to data sharing within the TRUSTS project, is not a black-and-white scenario.
As a general rule, the principle of contractual freedom governs contractual arrangements. This freedom, however, may be limited by mandatory legislative provisions. These include the GDPR (when personal data is involved), sector-specific obligations, contract law provisions, intellectual property rights legislation, financial regulations, competition law restrictions as well as national legislation.
In the context of non-personal data being shared on the TRUSTS platform, the Free Flow of Non-Personal Data Regulation does not impose any obligations on businesses, nor does it limit their contractual freedom to decide how their data is to be shared.
Due to the lack of a specific legal regime governing data sharing in business-to-business (B2B) settings it takes place mainly on the basis of contractual agreements (i.e. data sharing agreements).
However, as each dataset is different there is no one size fits all solution for data sharing. Depending on the specific needs of the parties, data sharing may take different forms, such as reciprocal exchange of data, one-off disclosures of data, several partners pooling data and making it available to each other and/or third parties, etc.
(i) transparency; (ii) shared value creation; (iii) respect for each other’s commercial interests; (iv) ensure undistorted competition; (v) minimized data lock-in.
Stay tuned to know more about legal and ethical challenges that lie ahead of the TRUSTS partners.
Photocredit NASA on Unsplash
A Case for Data Markets?
(2) implications arising from a still nascent understanding and misconceptions of data as tradeable economic good, and (3) technological and regulatory constraints and hurdles in emerging data ecosystems.
Business model research within the TRUSTS project will need to identify how these principal technological capabilities, supplemented with additional responsibilities within the ecosystem, can be translated into commercial sustainability and contribute to untying the Gordian Knot of data markets.
Author: Bert Utermark, G1 Governance One, Germany
TRUSTS – requirements
Figure 1: Methodology for the requirements elicitation, analysis, and usage
- Requirements gathering – Understanding and specifying the context of use
- Requirements specification – Specifying the user requirements
- Design – Producing design solutions
- Evaluation – Carrying out user-based assessment of the TRUSTS platform
- key stakeholder interviews
- the use of dedicated electronic surveys
- the analysis of selective related data marketplace activities
- the analysis of related legal framework
- the analysis of the use cases
- All requirements sources are analysed for individual requirements and their justification.
- The requirements mentioned above drive the definition of the FRs, which will be used for the implementation of the TRUSTS platform as well as the operational processes design.
- To assist implementation, each FR is mapped to the respective project task.
- Furthermore, the FRs will be used by the methodology defined in task T2.3 Testing framework and benchmarking to evaluate and provide coherent feedback through the UC trials (Work package 5 – WP5).
The requirements collection process resulted in 44 FRs, which are part of the following categories:
- Datasets and services onboarding functionality and processes
- Intelligent data/service exploration and correlation functionality and processes
- Purchasing and billing
- (Meta-)Data Governance
- Data as a Service and Subscribers management
- Data protection
- Advanced data analysis based on Machine Learning
- Trusted and legitimate data flows
Deliverable D2.2 is a public document and will follow.
In this deliverable we analysed key sources to gain requirements with respect to the development and operation of an industrial data marketplace targeting the telecommunication and financial sector and beyond, following a comprehensive methodology.
In today’s interconnected world business silos seem to fade enabling business expansion to other domains and collaboration between various industries. A forward looking data marketplace endeavour such as TRUSTS aims at clearing the obstacles in the data exchange process by establishing a comprehensive platform which includes all respective best practices, standards, and regulations to address a wide variety of telecommunication companies, financial institutions, and their collaborators.
- all WP1 tasks to evaluate additional information with respect to the TRUSTS architecture and data marketplace initiatives and trends
- WP7, which will produce adequate business models and receive market feedback from any related exploitation action
- WP6, which will define the legal aspects and processes
- WP3 and WP4, which will undertake the platform development
- WP5, which will execute the UC trials providing valuable feedback and
- WP8 to provide information and evaluate feedback from respective events
This work will be thoroughly analysed in the deliverable D2.3 Industry specific requirements analysis, definition of the vertical E2E data marketplace functionality and use cases definition II, which is due in M24.With regard to advancing T2.2 activities and the implementation of the D2.3 deliverable, the project will assess the initial developments, identify additional stakeholders, and refine questionnaires to constitute the final set of the TRUSTS environment requirements.
Author: Ioannis Markopoulos, FORTHNET, Greece
If you would like to learn more about the EU-funded TRUSTS project, just follow the link below to access the recording of a journalists’ call on 7 September 2020.
It gives an introduction of the project and contextualises it with European policies.
Speakers: Ioannis Markopoulos (Forthnet, Greece) and Andreas Huber (Governance One, Germany).
Host: Nina Popanton (Data Intelligence Offensive, Austria)
TRUSTS in the financial industry – enabling data sovereignty beyond existing solutions
In collaboration with the International Data Spaces Association, Alexandra Garatzogianni, the coordinator of the project along with Gianna Avgousti (eBOS), Christos Roupas (REL) and Benjamin Heitmann (FHG) will introduce the goals of TRUSTS.
Privacy Preserving Technologies for Trusted Data Space
October 1 @ 11:00 – 12:00 | Webinar, Free
Our consortium member IDSA is on a mission to bring sovereignty and trust to data ecosystems while the Reference Architecture Model (IDS-RAM) is offering a framework to leverage more data in a trusted way.
But how could it be executed in highly constrained environments? What can the technology could offer when data cannot be moved or disclosed at all?
Women in Data Science Vienna
October 3 @ 10:00 – 16:30 | Free
Anyone interested in data science, no matter what professional background or gender, is invited.
European Big Data Value Forum 2020