– Press Release –

Hannover/ Freiburg, DE – 7 December 2022. A successful data service ecosystem is created when enough participants can expect and contractually secure economic benefits from the exchange of data assets.

Only through data intersection do business models become profitable

“Data is the new gold” – this statement is often used to emphasise the importance of data exchange in data platforms. In the TRUSTS project, data exchange platforms were investigated across Europe and examined regarding their economic and organisational sustainability. It was found that those platforms that were able to offer a business model for data exchange were able to survive in the market – especially those data markets that were able to develop a monetisable business model for the exchange of data. exchange of data. The most successful data platforms are those that add value through data intersection or data refinement. The motto should therefore be changed to “insights from data analytics are the new gold”. At the core of successful data platforms is the value-added service for participants.

Business before technology – it has to pay off!

Which technical basis is used for the data exchange is not decisive. Once a business model has been found and established, data can be exchanged (and subsequently monetised) using existing technology or technology that is currently developing in the context of Gaia-X. More important than the technical systems used, however, is the measurable added value created for the participants.

“It is a misconception that the technology is the decisive factor for the success of a data exchange. It is the simple and clear business model that determines the lasting success of a data exchange” (Andreas Huber, Managing Director of G1 and consortium partner in TRUSTS).

Monetisable data exchange: benefits, scalability and a secure framework

To design and build a new digital business model, four things are needed in essence: a) a new customer benefit (new uses) b) an automatable and scalable data model (new user), c) a legal-economic framework (contracts) and d) if this benefit is quantifiable in monetary terms (added value). Thus, if the intersection of previously unrelated data leads to better predictions for future events – for example, the intersection of weather and energy data and the number of residents present in a neighbourhood – costs can be reduced by a quantifiable amount (in this case, through earlier planning of energy needs).

“Establishing a viable business model for a data exchange is at the beginning of our work with our clients. The set-up takes a good one to two years. The technical implementation takes place afterwards or even in parallel and is the result of a viable economic model and not the other way around.” (Managing director of an established platform for data exchange)

Operators needed for data platforms in Europe

The technological and business aspects of data platforms can only find their transition into reality through a trusted operator (data entrepreneur). In this sense, data-driven business models are like all business models: without an initial investment, the desired return cannot be achieved. So at the beginning of a successful data exchange is a validated business plan that illuminates the long-term economic aspects.

The TRUSTS project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871481.

• Download the Press Release here
• Austria Press Agency (APA): Press Realease in German

For further inquiries:

Nina Popanton
Data Intelligence Initiative
nina.popanton@dataintelligence.at
www.dataintelligence.at

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The paper, written by Hosea Ofe, Harm Minnema and Mark de Reuver in Safe-DEED and TRUSTS, aims to propose a framework for how privacy-preserving technologies (PETs) create business value for organizations. The framework was developed by examining the literature on privacy and information technology’s impact (symbolic and function). The authors evaluate the framework’s applicability using multiparty computation (MPC) as an instance of PETs, with expert interviews in the telecommunication industry.

The post New Research Paper: What’s the business value of privacy-preserving technologies? appeared first on TRUSTS.

Data and algorithm sharing is an imperative part of data and AI-driven economies. The efficient sharing of data and algorithms relies on the active interplay between users, data providers, and algorithm providers. Although recommender systems are known to effectively interconnect users and items in e-commerce settings, there is a lack of research on the applicability of recommender systems for data and algorithm sharing.

To fill this gap, we identify six recommendation scenarios for supporting data and algorithm sharing, where four of these scenarios substantially differ from the traditional recommendation scenarios in e-commerce applications. Specifically, we identify two traditional scenarios of recommending datasets to users (SC1) and algorithms to users (SC2), and four novel scenarios that are unique to data and algorithm sharing platforms, i.e., the recommendation of datasets to algorithms (SC3), algorithms to datasets (SC4), datasets to datasets (SC5), and algorithms to algorithms (SC6).

We evaluate these recommendation scenarios using a novel dataset based on interaction data of the OpenML data and algorithm sharing platform, which we also provide for the scientific community to foster future research on this important topic. Specifically, we investigate three types of recommendation approaches, namely popularity-, collaboration-, and content-based recommendations.

We find that collaboration-based recommendations provide the most accurate recommendations in all scenarios. Plus, the recommendation accuracy strongly depends on the specific scenario, e.g., algorithm recommendations for users are a more difficult problem than algorithm recommendations for datasets. This indicates that each recommendation scenario that can occur in a data and algorithm sharing platform, can be viewed as a separate recommendation problem. Finally, the content-based approach generates the least popularity-biased recommendations that cover the most datasets and algorithms. Overall, our work showcases how recommender systems can be helpful tools in data and algorithm sharing platforms.

Find the full paper here

About the Data Economy Workshop

The Data Economy Workshop will be co-located with the 2022 International Conference on emerging Networking EXperiments and Technologies (CoNEXT 2022). The workshop and the conference will be held in the splendid setting of Rome, at the Sapienza University of Rome. For the workshop 9 papers where accepted – find them here.

The post Towards Employing Recommender Systems for Supporting Data and Algorithm Sharing appeared first on TRUSTS.

Technical Approach

The challenges TRUSTS is trying to tackle as well as the technical approach were presented by Victor Mireles-Chavez from Semantic Web Company. He gave a quick overview of the elements that make up the TRUSTS platform from a technical standpoint. Some of the design choices behind the implemented architecture were motivated, and the concrete implementations were mentioned. In particular, the different components deployed in a corporate node were explained, as well as their interactions with the pre-existing components that a TRUSTS participant might have already deployed.

The core features of TRUSTS

The core features of TRUSTS

• (Meta-)Data Governance
• Datasets and services onboarding functionality and processes
• Intelligent data/service exploration and correlation functionality and processes
• Data protection
• Advanced data analysis based on Machine Learning
• Trusted and legitimate data flows

were explained by Ahmad Hemid (Fraunhofer Institute for Applied Information Technology FIT) who also showed a demo on how to log in and to create a service within the TRUSTS platform.

The Legal Framework

“The TRUSTS project comes to life in a complex tapestry of existing and envisaged regulatory efforts by the EU to boost the potential of digital markets”, explained Lorenzo Gugliotta (KU Leuven). This creates compliance challenges – related to data protection, platform regulation, intermediation service obligations, ethical AI – but also opportunities to use the approach of TRUSTS to such regulation in order to enhance trust. Via state-of-the-art Privacy-Enhancing Technologies (PETs) TRUSTS, combined with federated learning, TRUSTS can enhance trust in data subjects and data holders; via blockchain-based smart contracts TRUSTS can then enhance trust between businesses cooperating through the platform. The legal and ethical assessment of the platform and the three use cases demonstrated, on the one hand, the potential of TRUSTS in increasing compliance with the law; and on the other hand, the need for the legal framework to tackle existing challenges that can still stifle the full untapping of the value of data.

Use Cases & Leassons Learnt

Last but not least, Gianna Avgousti (eBos Technologies), Manos Paschalakis (Relational Technology) and Emmanouil Adamakis (Foundation for Research and Technology) gave insights into the three TRUSTS use cases and the – so far (the trials will end at the end of November) – lessons learnt:

• The TRUSTS Platform is an opportunity to securely share and trade data for Anti-Money-Laundering purposes, to maximize operational effectiveness whilst maintaining or reducing costs.
• Sharing anonymized up-to-date data in target marketing actions to specific local areas or individuals in a sustainable and GDPR compliant manner was possible with the TRUSTS Platform. 
• Big data analytics techniques applied on data shared in a secure, sustainable and effective manner can provide timely and meaningful information towards targeting profitable customers
• Innovations like smart contracts and recommendation mechanism are important for data exchange and therefore were integrated into TRUSTS platform
• TRUSTS platform’s interoperability with open-data libraries and external federated marketplaces were tested with success
• New services, like recommender and admin view services give additional value to the platform, facilitating both the platform user and the platform administrator

• Identification of a lack of a consolidated, widely viable, secure and GDPR compliant data marketplaces, adequate to benefit various business collaborations
• Platform’s security and GDPR compliance needs further assessment
• simple-user-friendlieness needs improvement

Thank you to all speakers of the session, to all of the visitors of EBDVF and to the organizers – it was a great pleasure to join the European Big Data Value Forum 2022! 

Impressions from EBDVF 2022

Watch the Session on YouTube:

The post Technical Approach, Core Features and Use Cases – a brief look into TRUSTS at EBDVF22 appeared first on TRUSTS.

This year, the event took place in Prague, Czech Republic on November 21-23, with a central theme of “At the Heart of the Ecosystem for Data and AI”.

TRUSTS held its final session on 23 November and gave insights into the project development and showcased the TRUSTS Platform. It was also project sponsor and had a booth in the EBDVF exhibition hall.

Besides, TRUSTS co-organised the workshop “Towards Data Spaces Interoperability Workshop on standardization” together with BD4NRG and IDSA. In this workshop, several initiatives and projects, which are working to address the challenges of interoperability, helping to standardize data spaces and make them interoperable, were presented by Achille Zappa (i3-Market), Juanjo Hierro (FIWARE Foundation), Robert David (Semantic Web Company, TRUSTS), Matthijs Punter (TNO) and Antonio Kung (TRIALOG).

Robert David presented the results of the TRUSTS workshop on data spaces and semantic interoperability, held in June in Vienna. The identified gaps were:

• Interoperability is seen often on metadata level ONLY (what about the data?)
• No industry specific controlled vocabularies & Knowledge Graphs are in place
• If such resources are available these resources not available in other languages than English
• Insufficient data usage control mechanisms (right-, value-, purpose modeling)
• Connection of the physical and digital world still missing

Read more about the workshop on data spaces and semantic interoperability here.

The post TRUSTS at EBDVF 2022 appeared first on TRUSTS.

TRUSTS at the EBDVF 2022

TRUSTS will be at #EBDVF22! We are looking forward to this years EBDVF by the Big Data Value Association (BDVA). Mark your calendar – the TRUSTS session will be on the 23 November, 10am. You can also visit us at our booth – we are looking forward to see you there!

Will we see you in Prague?

TRUSTS Whitepaper – out now!

In this whitepaper, the TRUSTS Consortium provides hands-on insights on their experiences on data governance mechanisms in one of the three use case domains: Anti-Money-Laundering.

Read it now!

Must-Read: Book Chapter on Privacy-Preserving Techniques

Read the TRUSTS-chapter “Privacy-Preserving Techniques for Trustworthy Data Sharing: Opportunities and Challenges for Future Research” in the newly published open access book on Dataspaces Design, Deployments and Future Directions.

Read it now!

Press Release: TRUSTS in the Community

“What TRUSTS has fostered is an understanding of interoperability for individual companies, but especially collaborative data spaces. We did a great job here in advancing that necessity for functional data ecosystems”

more

Second Cycle of TRUSTS Trials finished

The EU funded project ‘TRUSTS’ is coming to an end, while it runs for almost three years. August 2022 marked the conclusion of the three Use Cases second demonstration cycle.

more

Listen to our latest podcast episode!

Get insights into the process of the project: Silvia Castellvi (IDSA) talks about standardization activities, the latest workshop on data spaces and semantic interoperability and trustworthy collaboration.

more

Save the Date! 14 November – online

Be part of the virtual workshop which showcases the results and lessons learned of the 3 business oriented Use Case actual field trials. The trial investigators will share challenges encountered, solutions developed, and thoughts for the future.

The post 9th TRUSTS Newsletter appeared first on TRUSTS.

This book

• Educates data space designers to understand what is required to create a successful data space
• Explores the cutting-edge theory, technologies, methodologies, and best practices for data spaces
• Captures lessons and experiences in creating data spaces based on real-world projects in various industry sectors

One of the foundations of data sharing in the European Union (EU) is trust, especially in view of the advancing digitalization and recent developments with respect to European Data Spaces. In this chapter, we argue that privacypreserving techniques, such as multi-party computation and fully homomorphic encryption, can play a positive role in enhancing trust in data sharing transactions. We therefore focus on an interdisciplinary perspective on how privacy-preserving techniques can facilitate trustworthy data sharing. We start with introducing the legal landscape of data sharing in the EU. Then, we discuss the different functions of third-party intermediaries, namely, data marketplaces. Before giving a legal perspective on privacy-preserving techniques for enhancing trust in data sharing, we briefly touch upon the Data Governance Act (DGA) proposal with relation to trust and its intersection with the General Data Protection Regulation (GDPR). We continue with an overview on the technical aspects of privacy-preserving methods in the later part, where we focus on methods based on cryptography (such as homomorphic encryption, multi-party computation, private set intersection) and link them to smart contracts. We discuss the main principles behind these methods and highlight the open challenges with respect to privacy, performance bottlenecks, and a more widespread application of privacy-preserving analytics. Finally, we suggest directions for future research by highlighting that the mutual understanding of legal frameworks and technical capabilities will form an essential building block of sustainable and secure data sharing in the future.

The post 𝗠𝘂𝘀𝘁-𝗥𝗲𝗮𝗱: 𝗕𝗼𝗼𝗸 𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝗼𝗻 𝗣𝗿𝗶𝘃𝗮𝗰𝘆-𝗣𝗿𝗲𝘀𝗲𝗿𝘃𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 appeared first on TRUSTS.

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High-level stakeholders from the energy sector and beyond such as Roberta Metsola, Vasco Alves Cordeiro, Mariya Gabriel, Eva Kaili, Maria Leptin, Pascal Lamy and many more will be speakers during this year’s European Research & Innovation Days.

This year’s event gives all participants the opportunity to discuss how EU research and innovation will help build the world we want to live in. Join us to define and shape new solutions here.

Make sure to discover the programme as well as the speakers in order to not miss out any info!

The post TRUSTS at the European Research & Innovation Days 2022 appeared first on TRUSTS.

The TRUSTS Use Cases were defined to ensure the technology innovations developed and thoroughly test the TRUSTS solutions and business aspects, involving actors that represent all targeted sectors. Subsequently conducting advanced field trials within the sectors of Financial Institutions, Telecom Operators, Corporate data providers, etc., while demonstrating and validating the TRUSTS Platform.

The three TRUSTS Use cases executed more than 80 trial sessions throughout the duration of the TRUSTS trials performed under the two defined demonstration cycles. Trials Cycle 1 was executed between May – November 2021 with a total of 22 trial sessions collectively by all three Use Cases while, Cycle 2 trials was executed between February – August 2022 with a total of 62 trial sessions.

The two cycles of the TRUSTS trials intended to evaluate the TRUSTS marketplace in the various versions developed throughout the project and provide feedback and lessons learned to support the accomplishment of the final version. The outcome of the second demonstration cycle will give feedback mainly back to work package 3 focusing on the developments, for further and final iterations.

Evaluation and Lessons Learnt

The final 360^o TRUSTS evaluation and lessons learnt will be documented in the public deliverable D5.11 entitled “Performance evaluation and lessons learnt report II” which will be submitted by November 2022.

The operational plan followed is documented in the public deliverable D5.2 where the methodology used is laid out, although a final updated version will be submitted by November 2022.

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