By Juan-Luis Rodrigues-Quintero, RTDS Group
In the fast-moving world of research and innovation, data isn’t just a byproduct – it’s a currency. With over a decade of experience in IP and innovation management across 35 collaborative EU R&D projects, one question has consistently haunted my work when it comes to research data used in such projects: Who owns the data?
It’s a query that echoes across project consortiums, regardless of the research area, technology, or diverse backgrounds of those involved. In this editorial piece, I will explore not only how this question influences the successful implementation of these projects, but also how it shapes the future of exploitation strategies after the research ends.
As a lawyer, I often jokingly respond, “It depends,” whenever this question is asked. Data ownership isn’t just a legal technicality – it’s a battleground that can determine the success or failure of innovation and commercialization of EU projects. The ownership of data depends on various factors that require careful consideration. However, at the heart of the issue lies a simple yet critical question:
Does the research data meet the legal criteria to be considered ‘owned’?
Before we dive into the complexities of legal jargon, it’s important to first grasp what ‘ownership’ really means in the context of research and innovation.
Ownership refers to a property right – a legal entitlement to possess, use, control, and transfer an asset, whether tangible or intangible. Ownership of data often comes under the umbrella of intellectual property rights (IPRs). In the context of research projects, these rights grant their owners the capacity to exclude others from using their research outcome, such as data, without their prior authorisation, protecting the legitimate interests of creators and innovators.
But the application of these rights to research data is far from straightforward. The intangible nature and sometimes the origins of such data might complicate matters. Ownership is not always so clear-cut. Furthermore, the question of who truly “owns” research data doesn’t just hinge on intellectual property law. It may even raise other legal issues – ones that we won’t explore here, but which certainly merit another editorial piece. These include other concerns such as, data privacy, access to public funding information, and ethical implications.
To understand the concept of data ownership, let’s start by defining what data really is. The Oxford Dictionary defines “data” as “facts and statistics collected together for reference or analysis,” with the term originating from the Latin ‘datum’, meaning “a piece of information” or “an observation”. Here, the real complexity arises from the fact that mere facts, observations, or statistics – such as just numbers in an unformatted spreadsheet – typically don’t qualify for any legal protection. While copyright laws demand originality as their core principle, raw research data doesn’t exactly possess that creative spark.
This principle is consistent across various legal frameworks. Take the Berne Convention, for example – the cornerstone of international copyright law. It clearly excludes “news of the day” and “miscellaneous facts” from copyright protection.
But here’s the catch: Much of the research data isn’t simply raw numbers and mere observations. These numbers and observations are often the product of years of painstaking research, carefully curated and systematically structured. The resulting databases are valuable intangible (intellectual) assets that reflect substantial investment of time, funding and expertise, which should be compensated through a property right.
Therefore, in the EU, database developers benefit from a distinct legal protection known as the “sui generis” database right, which safeguards the substantial investment of time, effort, and resources required to compile and organise data. Understanding database as “a collection of independent works, data or other materials arranged in a systematic or methodical way and individually accessible by electronic or other means”. This right exists independently of traditional copyright protection, which may or may not apply to the individual data entries within the database. Unlike copyright, which typically protects creative expression, the sui generis right ensures that the database creator has exclusive control over the extraction and reutilisation of significant portions of the dataset, even if the underlying data itself lacks originality.
The sui generis database right is granted automatically upon the creation of a database if it meets the protection criteria established in Directive 96/9/EC. However, this right has been subject to ongoing debate and criticism, particularly in the context of machine-generated data and digital innovation. Furthermore, the enforcement and interpretation of the sui generis right vary across jurisdictions, leading to fragmentation in legal protection and creating difficulties for organisations seeking to exploit it across borders. Therefore, the sui generis database right remains a complex and evolving issue, which we will surely explore further in upcoming editorial pieces.
Data Ownership in R&D: A Collision Course Between Openness and Control?
When research meets industry, data becomes both an asset and a battleground. Who gets to use it? Who controls its fate? And what happens when the disclosure of scientific discoveries clashes with commercial interests?
In collaborative R&D projects, data isn’t always meant for public eyes. When it holds industrial or commercial value, its owners might have the power to dictate its fate. Thats why data ownership is a critical factor in collaborative research and development (R&D) projects, where researchers, SMEs and industry representatives join forces to generate, collect, and analyse vast amounts of information. Without clear ownership structures, things can get messy – fast. Defining access rights, privileges, usage policies and control over generated data from the outset isn’t just best practice – it’s essential for avoiding disputes down the line. Let’s discuss just some of the complexities around the allocation of ownership of data generated in collaborative R&D frameworks.
- Navigating joint ownership issues
One of the key challenges in collaborative R&D projects is navigating joint ownership issues. Take the Horizon Europe (HEU) Programme, the EU’s flagship R&D funding framework. Here, ownership is generally determined by the active contribution of project partners to the development of each project result. This criterion can lead to joint ownership, typically governed by a preliminary “default” agreement outlined in the project’s Consortium Agreement – established before the project even begins. This agreement requires joint owners to define additional terms and conditions for the allocation of exploitation rights, along with other considerations for the jointly developed result, in a separate agreement, usually under fair and reasonable conditions.Why does this matter? Simply put, joint ownership can complicate the management of exploitation and dissemination plans for project results. Unresolved ownership claims can stall research progress, block commercial opportunities, and even undermine the overall impact of the research if disputes arise between co-owners. Imagine, for instance, that your co-owner shared your data with a competitor without informing you, as they were allowed to do because no agreement on the allocation of exploitation rights was made between you. After both of you spent years on a groundbreaking discovery, you might now find yourself tangled in a legal dispute over conflicting legitimate interests regarding the use of the same data. Therefore, proactively addressing ownership agreements ensures that valuable research can translate into real-world innovation, free from unnecessary legal obstacles.
- Data Dissemination vs. ConfidentialityAccording to the HEU Grant Agreement, beneficiaries are required to publicly disseminate the research data they generated in the project. This ensures adherence to open science practices, such as the open-access publication of research data. However, an exception to this rule exists: data may be kept confidential if public access would conflict with the legitimate interests of another project partner (including commercialisation plans), the EU’s competitive interests, or any other factor that could jeopardise the project’s impact.
While researchers are typically eager to share their findings openly with the broader scientific community, industrial and commercially valuable research data present additional complexities. Industry and commercial entities involved in the project may seek to secure potential financial gains through commercialisation plans. As a result, these entities might attempt to block or control data dissemination – regardless of who is the owner of the data – by invoking the exception outlined in the Grant Agreement. This could, for instance, involve integrating the data into proprietary analytical tools for commercialisation, preventing data publication to secure a patent, licensing it to third parties, or imposing usage restrictions – provided that such commercialisation plans were prioritised in the project call and subsequently reflected in the Grant Agreement.
For example, data obtained from testing a product developed by an industry partner within a consortium may automatically belong to the researchers conducting the experiment, including data collection and analysis. However, the industry partner that owns the tested product may seek to control the further use and dissemination of the data to protect its commercial or industrial value. This creates a conflict of interest between researchers, who are recognised as the data “owners,” and the industry partner, who aims to safeguard its commercial interests by controlling the dissemination attempts.
This presents a significant challenge when the goals of data owners and potential data controllers come into conflict due to inadequate planning and management of exploitation and dissemination activities during project implementation. Data and knowledge dissemination are fundamental to fostering further research and innovation worldwide. At the same time, commercialisation plans resulting from HEU projects contribute to economic growth, enhancing innovation capacity and competitiveness of Europe. Proper project management should aim to integrate all perspectives and objectives under a shared vision, ensuring that no party feels excluded or restricted.
- The Lack of Legal Interoperability and the risk of (IPR) infringement
The lack of legal interoperability and the risk of intellectual property rights (IPR) infringement pose significant challenges in collaborative projects when data ownership and terms for using it are not recognised or unclear to all the consortium members. In collaborative project, the research data might have a different owner than project partner (beneficiary). In fact, Research data is often sourced from various existing databases or proprietary software, each governed by different legal frameworks. For instance, the use of data from public entities—such as, non-governmental and intergovernmental agencies (e.g., EFSA, ESA, etc.), and research organisations like universities – is governed by the terms and conditions or licences (such as Creative Commons) published alongside the data.
However, sometime people share datasets with other project partners from some of the existing sources without consulting such terms and conditions and brief the rest of the consortium members on the potential restrictions imposed by the owner, as normally required in the Consortium Agreement. Hence, if the terms and conditions established by the data owner(s) aren’t understood by all consortium members during the project implementation, researchers may use protected datasets and other materials without proper authorisation, exposing the project to legal challenges.
For instance, a research team might unknowingly integrate a dataset into their study without realising that it is subject to specific licensing conditions, such as restrictions on commercial use or obligations to provide attribution. If the dataset owner enforces these restrictions, some consortium members could face legal consequences, including demands to cease data usage, revoke publications, or even pay licensing fees or damages. Such issues can disrupt the research timeline, limit dissemination opportunities, and, in extreme cases, jeopardise the entire project’s outcomes.
To prevent these risks, it is essential that all consortium members conduct thorough due diligence before incorporating external data into their work. This includes carefully reviewing licensing agreements, obtaining explicit permissions where necessary, and ensuring that all partners understand their rights and obligations regarding data use. Establishing clear data governance policies within the project can help mitigate potential legal conflicts, ensuring that research outputs remain compliant with intellectual property laws and accessible for intended use without unnecessary legal barriers.
Avoiding the Ownership Trap: Proactive Strategies for R&D Teams
The best way to clarify ownership issues is to define them upfront – in particular during the development of a project proposal. All project partners should try to avoid future conflicts, by openly discussing the foreseen use of the research data. Particularly, anticipating some of the situations discussed in this article. This also includes the negotiation of legal agreements by informing all project partners of the potential restrictions on project resources and expected results in the consortium agreement of the project. Furthermore, a well-thought-out data management plan (DMP), adherent to the FAIR data guiding principles, is also a crucial tool to proactively clarify data ownership in R&D projects. The DMP acts as a blueprint for managing research data —outlining who owns what, how data will be shared, and the rules governing access and use. Establishing clear guidelines from the onset of an R&D project can save a lot of headaches down the road.
Four Takeaways for Data Ownership in R&D:
- Define ownership and access rights upfront – Open discussions with project partners can prevent conflicts before they arise.
- Read the terms and conditions – Always check the licensing terms governing the use of data and the repositories you will use in your R&D collaborations.
- Remember that ownership and access are distinct – Data collection doesn’t necessarily equate to ownership or unlimited access.
- Keep an eye on your data policies – Regularly review and refine your data policies to ensure remain effective and relevant and aligned to all databases consulted in the project.
Data as a Strategic Asset: Protect It, Use It, Leverage It
Data is more than just a research byproduct. It’s a powerful asset. Navigating data ownership in collaborative R&D projects can be complex, but by establishing clear agreements and frameworks early on, teams can set themselves up for success. A well-organised data management plan streamlines collaboration, maximises the impact of the research, and ensures legal compliance.
At the end of the day, data is more than just a research byproduct. It is one of the most valuable asset. By proactively addressing ownership issues, teams can unlock new discoveries, protect their rights, and safeguard their interests. The future of innovation depends on it.
Want to learn more about effectively managing data ownership and intellectual property (IP) in your R&D collaborations? Don’t hesitate to reach out to me at rodrigues@rtds-group.com, and don’t forget to subscribe to our newsletter to stay updated on upcoming editions of RTDS IP Insights for expert updates.
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