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Data, AI and Robotics (DAIRO) AISBL

BDVA

The Association promotes Data, Big Data and Data-Driven AI Research and Innovation.

Lobbying Activity

Response to European Innovation Act

3 Oct 2025

BDVA welcomes the European Commissions efforts to improve the European innovation ecosystem through the European Innovation Act. Addressing the innovation in Europe to boost the competitiveness and foster growth is a key challenge from BDVAs perspective. Many limitations related to bringing the innovation to the market have already been identified and have been addressed, but achieving the necessary speed for this process remains a challenge in todays reality. As an association with a focus on data and AI, BDVAs members are directly involved in that process. Of its more than 250 members, almost 80% of them fall into the categories of SMEs, start-ups, and academia and research organisations the backbone of the European Innovation ecosystem. With this background, BDVA wanted to share the observations and recommendations which can contribute to the goals of the European Innovation Act, which through well-balanced measures can help boost Europes innovation and create an environment where European companies have a fair chance to compete with multinational corporations on merit.
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Response to European Data Union Strategy

18 Jul 2025

BDVA welcomes a renewed data strategy for Europe that builds on the foundations of the European Data Strategy 2020. Data must remain at the core of Europes Digital Strategy and the focus must be on accelerating the speed of generating value out of data for European businesses and society. Despite AI and other advancements in digitalisation being the main drivers to update the European Data Strategy, data remains the cornerstone of innovation, competitiveness, and public value creation. For this reason, updated policies and investments in data (data spaces, data sharing ecosystems, data technology and services, data research and innovation, data companies and data skills) are essential not only to support AI and digital strategies in the current context of strategic autonomy, but also as engines of economical and societal value in Europe. The European Data Union Strategy should also focus on ensuring that the value created with European data remains in Europe. In addition to the above listed high level recommendations the BDVA community suggests a set of actionable recommendations linked to these 3 objectives identified by EC can be summarized as follows: Data availability, access and use. Data for AI: o Invest in AI-ready data tools, frameworks, benchmarks, and standards. o Use Data Labs as a framework to accelerate convergence of AI and data ecosystems. o Boost new industrial collaboration models for the creation of vertical foundation models. o Continue and consolidate public and private investments to achieve sustainable, scalable and interoperable data spaces and data sharing ecosystems. o Establish a European coordination body to achieve convergence on current fragmented efforts in setting up data spaces. o Introduce incentives for data producers and data intermediaries. o Grow the ecosystem of new data companies in Europe. o Establish data innovation hubs in all regions of Europe. o Invest in synthetic data. Simplification: o Apply a holistic approach to data and digital legislation. o Develop automated compliance solutions (RegTech) and new paradigms in regulation for automation. o Address legal barriers for research and innovation transfer to market. Development of an international Data Strategy: o Develop and support international standards and protocols. o Contribute to the definition of global data governance principles. o Invest in collaborative research and innovation, launch pilot projects and support referential lighthouse projects (e.g., International Manufacturing-X). BDVA is a European non-profit association with over 250 members from industry (including SMEs, startups, and large companies), research, academia, and the public sector, all united by a mission to create value for society and industry through data and AI innovation. The AI Continent Action Plan and the European Data Strategy are central to BDVAs mission and objectives. As the private private member of the EuroHPC JU, a founding member and strong contributor of the AI, Data and Robotics Partnership in HE, and a strong player in the data spaces ecosystem of projects and activities, BDVA actively contributes to achieving all foreseen objectives of the European Data Union Strategy BDVA stands ready to support the EC, Joint Undertakings, Member States, and other collaboration partners and associations in turning the European Data Union Strategy into tangible outcomes. Strong, structured collaboration with community-driven initiatives like BDVA will be essential to ensuring impact on the ground. The BDVA position paper attached to this feedback elaborates in our community input. Also to be found at https://bdva.eu/
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Response to A European Strategy for AI in science – paving the way for a European AI research council

5 Jun 2025

The use of AI in the sciences is transforming the way we perform science. The awarded Nobel prizes this year in physics and chemistry are illustrative for the scientific breakthrough enabled by AI. Further advances in core AI technology is expected to further accelerate this trend that has the potential to significantly accelerate scientific research for all scientific disciplines. These are likely to lead to (disruptive) scientific breakthroughs discovery beyond the reach of conventional methods. At the same time, there are serious concerns with using AI in the sciences including evaluation, and reproducibility that touch upon the core of the scientific method for knowledge acquisition. Likewise, the raise of AI creates an increased dependency on data, compute, algorithms and expertise limiting the ability to perform research at the frontiers of science to those that have access to these resources. To ensure that Europe remains at the forefront of research and innovation and to safeguard future social-economic prosperity and the European way of living, it is of paramount importance to take measure of the eminent metamorphosis of the scientific process and the consequences it entails in terms of Europes capacity to perform cutting-edge scientific research. BDVA acknowledges the impact of the ongoing transformation and very much welcomes the European focus on AI for Science as part of the AI Continent Action Plan in the larger framework of Eurpean competitiveness and value creation for industry and society. From this perspective we would like to offer the following considerations leveraging the key priorities and strengths of the association. The innovation gap and sustainable value creation: AI for science can help us to accelerate scientific discovery and address difficult challenges, but it is equally important to move this knowledge into sustainable value for companies, public sector and society. The innovation gap that already exists in Europe needs to be urgently addressed or it has the risk of becoming ever bigger. Research industry collaboration remains relevant in the AI for Science and we need to invest in new ways for collaboration that bring together scientists, the cutting edge Start-ups and the more traditional companies and public sector: how the enquiry can be already connected to solving issues that the industrial players in any sector (new material materials, manufacturing processes, healthcare, agriculture, mobility, media, space etc). Industrial data and AI for Science: Advancing AI for Science may require more than data access when talking about industrial or business private data; it demands collaboration between data-holding organisations and scientists. Focus should be on data that is relevant and valuable for specific AI uses and scientific needs, not just high quality. Starting with use cases defined by data holders, in secure environments, is key. Scientists must actively engage with data spaces and data ecosystems as part of broader AIdata value ecosystems. For AI-enabled Science it is essential to develop robust frameworks to critically evaluate the performance of LLMs and AI models for ensuring human centricy in AI systems. The core argument is that AI and LLMs inherently carry biases, as these are embedded in the data used during training. We can only approve their functionality if we have robust frameworks to critically evaluate their performance. Evaluation itself is a complex task involving design considerations and human-in-the-loop processes. We need to support the scientific and cross-disciplinary networks collaboration to develop this AI-driven methodology and giving then the opportunity to share at build the new methods at European level. The BDVA's position paper to the AI Continent Action Plan is attached and also avaialble here: https://bdva.eu/news/towards-a-european-ai-data-value-ecosystem/
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Response to Apply AI Strategy

4 Jun 2025

The AI Continent Action Plan presents a forward-looking and comprehensive framework aimed at accelerating Europes leadership in trustworthy AI. As a key stakeholder in the European data and AI landscape, BDVA has released a position paper attached to this call for evidence and public on our website. Some highlights for Apply AI Strategy: Stronger integration of AI and data strategies: Despite referencing each other, the AI Continent Action Plan and the European Data Union Strategy remain insufficiently connected. Europe needs a unified, ecosystem-based AI and data strategy that combines data spaces, computing infrastructure, AI deployment, skills, and regulatory alignment within AIData Value Ecosystems. E.g European Digital Innovation Hubs (EDIHs) should evolve not only into AI experience centers but into AIdata innovation hubs, supporting not only AI adoption but also active participation in data sharing initiatives. BDVA i-Spaces, many of which are already part of the EDIH network, serve as effective models. Emphasising societal and economic Impact: AI has transformative potential beyond technical excellence. The Action Plan would benefit from articulating a clearer vision for how AI will improve citizens livesreshaping areas such as healthcare, education, and public serviceswhile driving economic resilience and competitiveness. Integrating these dimensions into the strategic narrative and investment priorities is essential to ensure broad and inclusive value. Strategic sector support: The Apply AI strategy rightly emphasises uptake in strategic sectors for Europe such as advanced manufacturing, aerospace, agri-food, and health. However, it omits key sectors for Europe like Tourism. Clearer rules on allocation and long-term sustainability are needed, especially in relation to coordination across funding programmes and HEP clusters Amount, timing and type of Incentives: The scale and speed of funding are not proportionate to Europes ambitions. Current funding volumes, spread over multiple countries and sectors, are modest. More flexible and rapid instruments are needed to ensure uptake, especially by SMEs. BDVA recommends streamlined models similar to COVID-era Digital Innovation Vouchers and accessible proof-of-concept schemes (e.g., 510K vouchers) Time is of the essence: delays risk compromising Europes competitiveness. Governance of Instruments: While the proposal to coordinate initiatives such as TEFs, EDIHs, AI Factories, and Apply AI pilots is positive, the plan lacks operational clarity on governance, sustainable funding, and coordination mechanisms. A clear governance model, with shared objectives and structured alignment across regions and sectors, is needed. The role of data as a core enabler must also be better reflected and integrated. Sustainability and purposeful AI development: The Plan gives insufficient attention to long-term sustainability, scale-up strategies, and societal relevance. Beyond pilot projects, the EU should anchor AI development in mission-driven goals that address Europes major challenges. This would give more direction and impact to innovative investments and help ensure scalability and export readiness of EU-developed AI systems. BDVA is a European non-profit association with over 250 members from industry (including SMEs, startups, and large companies), research, academia, and the public sector, all united by a mission to create value for society and industry through data and AI innovation. The AI Continent Action Plan and the European Data Strategy are central to BDVAs mission and objectives.BDVA stands ready to support the EC, JUs, Member States, and our collaborations partners and associations in turning this ambitious plan into tangible outcomes. Strong, structured collaboration with community-driven initiatives like BDVA will be essential to ensuring impact on the ground.
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Response to Data Act (including the review of the Directive 96/9/EC on the legal protection of databases)

12 May 2022

The Big Data Value Association (BDVA) is a European industry-driven research and innovation community on Big Data, Data Value, and Industrial AI. BDVA is also a unique platform for pre-competitive collaboration between industry and research, combining a research-oriented and experimental approach to data-driven innovation and a focus on competitiveness and adoption. BDVA welcomes the Data Act and believes it will play a fundamental role in the development of European data spaces and in the creation of data spaces governance frameworks and infrastructures. BDVA also welcomes the introduction of interoperability and standards as a key measure to achieve the goal of fairness in the distribution of value along data value chain, We believe Industry and researchers should play a strategic role in the life cycle of production, monitoring and evaluation of interoperability requirements and standards for data spaces. For this purpose we would recommend the Commission and ESOs to closely collaborate with communities such as BDVA, the Data Spaces Business Alliance (BDVA, FIWARE, Gaia-X and IDSA), the upcoming Data Spaces Support Centre (DSSC) and the existing Federation of Big Data Innovation Hubs (EUHubs4Data). The community underlines the importance of experimentation in data spaces with regards to data governance models and mechanisms. BDVA stresses the importance to clarify the relation and interaction that the Data Act proposal will have with the existing EU digital policy and regulatory frameworks (incl. GDPR, Regulation Free Flow of Non-Personal Data, Open Data/PSI Directive, Trade Secrets Directive, security and competition law) and the ongoing negotiations (incl. AI Act, ePrivacy Regulation, Digital Services Act). It is also advisable to work towards a taxonomy of data categories and clarity on how to deal with different data categories. Further clarification is also needed on the types of data concerned by the different parts of the proposed text, and a clear understanding of what type of data is targeted in the various chapters of the Act. Additionally definitions of some of the roles and actors and related concepts may be necessary in chapter I. This is particular important of the “Operators of Data Spaces”. The Data Act is expected to incentivize data sharing and build trust to promote value in the data economy. However, this will only be achieved if regulation acts as an enabler, rather than as a set of restraining obligations. If businesses see additional costs for them to provide data or risks of penalties for non-compliance, they will make less data available leading to a reduction of the possibility for value creation and for common good. The proposed provisions aim for facilitating access to and use of IoT data by consumers and businesses, while preserving incentives to invest in ways of generating value through data. BDVA stresses the importance of clear definitions and a coherent identification of scope of these provisions and suggests improvements in the scope and definitions of data, products, and roles, and in the data holders´ rights protection. Concerning the switching in between cloud services, we acknowledge the intention of the Data Act to foster and safeguard a maximum level of switching including data, applications, and any other data asset for customers of a data processing service provider). However we suggest important improvements in the definitions of key terms, in the deadlines proposed, in the term and usage of the “functional equivalence” and we propose the extension of norms held in data sharing to applications that are transferred to data as well. As for the link with the development of trustworthy AI, BDVA underlines the connection between data and AI and stresses the importance of further investigating the impact of the proposal on the life-cycle of data-driven AI (e.g MLOps). Full position paper attached.
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Response to Legislative framework for the governance of common European data spaces

5 Feb 2021

BDVA/DAIRO welcomes the possibility to provide feedback to the public consultation on Data Sharing in the EU – common European data spaces and more particularly on the Data Governance Act and its inception Impact Assessment. BDVA/DAIRO position paper of November 2020 “Towards a European-governed data sharing space” includes a number of points and recommendations which are of relevance for this European Commission’s initiative. BDVA/DAIRO response to the public consultation covers in particular four aspects of the Data Governance Act and notably: • The requirements applicable to data sharing services; • The provisions on Data Altruism; • Reuse of certain categories of protected data held by public sector bodies (PBSs); and • The establishment of a European Data Innovation Board. BDVA/DAIRO input is provided in the document attached.
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Response to Requirements for Artificial Intelligence

9 Sept 2020

BDVA welcomes the possibility to provide feedback on the Inception Impact Assessment concerning a Proposal for a legal act of the European Parliament and the Council laying down requirements for Artificial Intelligence. As already highlighted in BDVA response to the AI Whitepaper, BDVA strongly supports the development of a solid AI European approach based on European values. BDVA response to the AI Whitepaper already focused on one of the key themes of the present Inception Impact Assessment and notably the fact that PRCS (Policy, Regulation, Certification, and Standards) issues are pivotal for building an AI ecosystem based on trust and they are likely to become a primary area of activity for the new AI, Data and Robotics Partnership. Building on these considerations and on the response to the AI Whitepaper, BDVA wishes to underline a few important elements concerning both the challenges identified in the Inception Impact Assessment and the possible policy options. Comments on the issues identified • European businesses see Industrial AI as more of an opportunity than a threat. However, the business, economic and societal context to which AI is applied needs to be considered as decisions are not made in a vacuum but within the socio-economic context of a society of humans which, in the European case, requires the AI application to be trustworthy. • Businesses are aware that AI systems may be used in value chains, and see the possibility that liabilities emerge; for example, when an AI system bases its outputs on data that is created by another AI system from a value chain partner. • Requirements on AI algorithms may have to be scoped carefully; usually, an algorithm is trained before it can be used operationally (it is called a model, then) and in such case, the training data is also part of the behaviour of the AI system. Thus, requirements for AI systems may have to be extended to training data as well. It may even be considered that the specific business process in which the AI system operates can be seen as part of the algorithm, or that the design criteria (including team composition and stated business goals) could be in scope. This will become complex, so careful scoping is needed. Comments on the policy options • Many stakeholders see certification in relation to AI systems as a critical trust-building mechanism for adoption of AI solutions. A methodological approach to certification could include best practice from other sectors being mapped to AI in tandem with the Standardization Landscape approach. Standards provide the foundational documentation for certification, regulation, legislation, compliance and ultimately enforcement. • Awareness of potential issues needs to be addressed. Voluntary certification and labelling schemes can have several benefits, both for purchasers of the certified AI system as well as for its producer. Such certification increases the confidence of users in AI systems as it indicates the producer’s commitment towards higher safety and quality standards. At the same time, however, voluntary certification should be carefully addressed as it can result in a meaningless label and evens increase non-compliant behaviour when there are no proper verification mechanisms. Voluntary labelling may make end-users more aware, just like Nutriscore intends to make consumers more aware of the features of the food that they are buying. When a voluntary labelling scheme is adopted, producers of AI will also become aware that end users may assess their products or services in a specific way; which will mean opportunities for producers who want to be transparent about their products and services. • It is already acknowledged in the AI Whitepaper that regulatory intervention should be targeted and proportionate. Such an approach will reduce the risk of overregulation and hence slow down technological innovation. In the Whitepaper the European Commission seemed not to want to regulate all AI systems but
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Response to Legislative framework for the governance of common European data spaces

30 Jul 2020

BDVA welcomes the objectives described in the Inception Impact Assessment, focusing on the development of a framework for the governance of common European data spaces. BDVA supports further research and experimentation on the utilisation of data, AI technologies and data-driven innovation for the good of business and society via a smart mix of technical, legal, ethical and business methods. An experimental research approach is needed to identify the factors for success or failure, e.g. the technology, the nature of data and of stakeholders, the objectives assigned to the governance mechanism, and the legal framework.. It is only against this background that room for further legislative initiatives (e.g. in the Data Act) can be identified. The nine BDV PPP research and innovation projects funded under ICT13a (Industrial and Personal Data Platforms) are already providing valuable insights across a diverse set of domains on how to address many of the issues mentioned in this initiative that are holding the EU back from realising its data potential: availability of data, data interoperability and quality, data governance, data infrastructures and technologies, empowering individuals, data literacy and cybersecurity. Additionally, the federation of Data-Driven Innovation Hubs and the new generation of European Data incubators (funded under DT-ICT-05 ) have as their overarching objective the mobilisation, use and sharing of data between sectors and borders, providing different governance frameworks to align needs coming from different sides (offer / demand) and moving towards a Common European Data Space. Overall BDVA suggests two practical policies that could translate into high impact data sharing activities: i) Policies that create the conditions for the development of a trusted European data sharing framework, in order to enrol a critical mass of stakeholders to engage in pan-European data sharing, including all Member States to encourage showcasing evidence-based benefits for business, government, science and individuals alike; ii) Policies that provide supportive measures for European businesses to safely embrace new technologies and practices, supported with data sharing facilities and environments where new business and innovation models can be safely tested. Therefore the EU should focus on a digital sovereign infrastructure in which a level playing field for both non-European and European (data sharing) platforms is created. Existing mechanisms such as the network of European Digital Innovation Hubs (DIH) (in particular the Big Data Innovation Hubs network to be implemented by the EUHubs4Data project) and the BDVA i-Spaces should be leveraged by industry for safe experimentation and validation under recognised labels. In addition, new mechanisms and instruments like European-wide Regulatory Sandboxes need to be made available as flexible experimental facilities to incentivise and de-risk the exploration and testing of new business and innovation models enabled by disruptive data sharing technology. Considering the four main areas of intervention/four main objectives laid down in the Commission document BDVA has significant feedback to two of them: i) Lower the costs of the use of data through interoperability at the technical level and availability of generic enabling standards; ii) Lower the costs of data sharing by supporting an emerging offer of data intermediaries. The attached document provides details and additional information in these two areas of intervention.
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Meeting with Roberto Viola (Director-General Communications Networks, Content and Technology)

16 Sept 2019 · SRIDA, AI, PPPs

Meeting with Roberto Viola (Director-General Communications Networks, Content and Technology)

1 Jun 2017 · Progress, positioning and strategy of the Big Data Value Public Private Partnership (BDV PPP) - Big Data Value cPPP (status, cPPP contribution to the European Innovation and Industrial policies, DG Connect’s vision for this cPPP, BDV cPPP in H2020 LEIT WP2018-2020)- Future Challenges to develop the European Data Economy