Should I provide my health data for research? Citizens assessing the value of data provision

Abstract

In March 2024, the European Parliament and Council agreed to implement the European Health Data Space (EHDS), the first domain-specific common EU data space. Next to improving healthcare delivery in national and cross-border settings, the EHDS aims to advance the reuse of health data in research, innovation, policy-making, and personalized medicine. However, to fully harness the potential of a data-driven approach to health research and care, citizens must be willing to provide their data for research. To understand the conditions under which citizens are prepared to do so, this article investigates the situated ways in which they reflect on and assess their (non)provision of digitally available health data for research. Our empirical work is situated within a large-scale EU-funded project that sought to develop a health data infrastructure for transborder healthcare and research. Using a diverse set of engagement methods, we investigated how citizens value the provision of their health (care) data for secondary use in research and examined the valuation constellations that shape their assessments. Our analysis shows that citizens’ valuations of a digital health infrastructure are by no means binary—defining it as either worth supporting or not—and that visions, positions, and decisions cannot be considered stable over time. Their willingness to share health data is shaped by dynamic evaluations grounded in mediated reciprocity, assessments of future data-use-related uncertainties, and the need for relational transparency. Realizing and maintaining the value of health data infrastructures thus requires continuous efforts, which must be reflected in both their material design and governance.

Introduction

At the time of writing, we are witnessing a significant wave of policy initiatives aimed at enhancing the collection, accessibility, and mobility of health data across both national borders and institutional domains. In March 2024, the European Parliament and the Council reached a landmark agreement on establishing the European Health Data Space (EHDS)—the first sector-specific common data space within the EU, with additional domains expected to follow. The EHDS is designed to facilitate the seamless access to and exchange of health data for two primary purposes: firstly, to improve healthcare delivery within and across member states (primary use), and secondly, to support research, innovation, policy-making, regulatory oversight, and the advancement of personalized medicine (secondary use) (EC_COM, 2025). The EHDS represents a pivotal step toward realizing a vision of European health integration, one that has been gradually co-produced alongside a growing digital health and care infrastructure shaped by over two decades of policy development (Lievevrouw and Felt, 2025; Felt, 2025). The EHDS articulates a digital future oriented toward sustainability and efficiency: it promises considerable economic impact, with projected savings of €5.4 billion “over ten years from better use of health data for research, innovation and policy making,” and an additional €5.5 billion “from better access and exchange of health data in healthcare.” ¹

This is to a certain extent the culmination of efforts that could be witnessed already over recent decades. Indeed, analysts underline the increasing production of health data in various sites and through diverse practices, from medical treatment and clinical research to individual digital self-care (Van Dijck and Poell, 2016; Lupton, 2013), attributing great potential value to them in the biomedical and health care area, including through the secondary use of collected data (Krutzinna et al., 2019; Wilson et al., 2020). Data is described as relevant for the systematic monitoring of treatments, for the analysis of public health trends (Ganna et al., 2024) as well as for personalized medicine, which aims to consider patients’ individual characteristics in prevention, diagnosis, treatment, and monitoring (Prainsack, 2015). All this necessitates an intensification of data sourcing and the aggregation of larger volumes of higher-quality data from a broader pool of individuals (Hoeyer, 2019), a process that advancing health data infrastructures can support. The value of health data thus does not come from its gathering alone; data need to be made available and useable in settings different to those it was initially produced in, hence requiring mobility and interoperability (Leonelli, 2020). This, in turn, raises the issue of to whom and for what purpose data should be made available.

While we witness a mobilization of expectations and future visions of better health and care (Tarkkala et al., 2019), the central question remains how different actors assess them. As Ganna and colleagues point out, given the opt-out mechanism for data provision foreseen in the EHDS, the “research community has a lot at stake in terms of securing public support” (Ganna et al., 2024). Citizens thus play a central role in the sustainability and robustness of endeavors such as the EHDS, as their support is necessary to facilitate the connection between previously separate areas of health data production and use for health research. Indeed, benefit narratives are essential to ensure public support of the collective investments in establishing health data infrastructures that facilitate health data sharing for secondary data use. Yet, they address citizens and researchers in different ways, and also benefits and risks are unevenly distributed. While various actor groups—clinical researchers, policy makers, as well as large technology companies, who have expanded into the health sphere (Sharon, 2016)–have concrete interests in gathering and using these data, benefits for citizens oftentimes remain elusive, promising empowerment or better healthcare for all through data-based research (Marelli et al., 2023; Kruus, 2025). Furthermore, assembling large datasets and the secondary use of data always bear the risk of re-identification, all safeguards notwithstanding. Opting out seems to be the only mode of control citizens have at their disposal. However, even though this is presented as the solution to “balance the data subjects’ rights,” Kruus (2025) points to its complexities and expresses clear concerns whether this fully respects “the rights and interests of data subjects, researchers, and the public” (p. 2).

In general, research has shown that the provision of health data can be a contested issue from the perspective of citizens. While they might have a rather positive attitude regarding the provision of health data for research (Cascini et al., 2024; Skovgaard et al., 2019), this willingness is always conditional (Baines et al., 2024). Transnational data sharing, commercial involvement, and framing data as a national economic asset appeared, for example in the Danish context, as central concerns in a recent survey on attitudes toward health data reuse (Skovgaard et al., 2024). Public support for data sharing varies based on the recipient of the data and the perceived distance from the original purpose of data collection (Cascini et al., 2024; Skovgaard et al., 2024). Positive attitudes depend on factors like whether data serves the “common good” or is used by public researchers, while concerns arise about misuse by commercial entities, such as insurance companies (Skovgaard et al., 2019). Although the boundaries between public and commercial research are not always clearly drawn (Starkbaum and Felt, 2019), and there is awareness that publicly funded academic research can also result in commercial outputs, the literature shows a clear problematization of health data access for commercial actors given perceived diverging objectives or interests (Aitken et al., 2016, 2018; Benevento et al., 2023; Cascini et al., 2024; Skovgaard et al., 2019). This is particularly true for the pharmaceutical industry or insurance companies (Blasimme et al., 2019; Damschroder et al., 2007; Hill et al., 2013; Willison et al., 2003). We thus have by now quite a number of survey studies available on citizens’ attitudes and the concerns they have with regard to secondary data use.

What is missing is an in-depth exploration of how citizens develop their positions in situated ways and what we can learn from this for the development of health data infrastructures, particularly their governance. This article aims to make such a contribution by exploring in a fine-grained manner how citizens value the provision of their health (care) data for secondary use in research, examining the situated valuation constellations that shape their assessments. It thus delves into the values, concerns, and roles citizens consider in this process. Our data were produced in the context of a Horizon 2020 project prototyping what the EHDS aims for: to provide citizens with control over their health data, give healthcare professionals access to relevant data, and facilitate access to health data for researchers. Understanding the complexity and situatedness of citizens’ reasoning provides an important input to building sociotechnically robust data infrastructures while putting in place governance processes that facilitate the accessibility of such data in appropriate ways.

The article begins by establishing the analytical framework for examining citizens’ valuation practices, connecting debates from the field of valuation studies with studies on the relationality of data and data journeys. After describing our methodological approach and material, we discuss the processes of valuation that citizens engage in to assess data provision for research as appropriate for them or not. For this, we investigate three dimensions: citizens’ understanding of data, the anticipated contexts of data use, and the interplay of choice, governance, and responsibility. The article concludes with key learnings that need to be considered for the envisioned fundamental transformation of healthcare and research through digital health infrastructures to become a robust and widely supported solution.

Conceptual framework

How do citizens decide whether to make their health data available for research? To explore this question, we adopt a dual conceptual approach. First, we draw on studies underlining a relational perspective on data and on the sensitizing concept of data journeys (Bates et al., 2016; Leonelli, 2020) to follow citizens when they reflect how data move, evolve, and gain significance across various contexts while developing their positions. Second, our research builds on valuation studies, understanding valuation as situated practice and exploring so-called valuation constellations (Waibel et al., 2021). Together, these perspectives allow us to illuminate how citizens’ readiness to share their data is not simply a matter of individual stable preference. They help us to elaborate in detail the complex connections between citizens’ anticipations of how and where their data could potentially move, what new connections this creates, and how its meaning and value may shift along the way and thus impact their decision to provide data for research.

Following data and the connections they create

The promise of big (health) data is tied to the movement of data, as well as to their interoperability, i.e., their capacity to link with other data types from other sources (Leonelli, 2020). Data always need to be seen as relational in the sense that they do not “pre-exist their generation” (Kitchin, 2014, p. 19), but are connected to places, practices and material conditions of production (Gitelman and Jackson, 2013). Data never simply “represent and thus document specific aspects of the world,” but are “historical entities which (…) evolve and change as their life unfolds and merges with elements of their environment” (Leonelli, 2020, p. 6–7). In their evolving, data are what Klaus Hoeyer calls promiscuous, i.e., “relatively indiscriminate in their relation to users: what is seen as data on a thing for one purpose can always become seen as data on another aspect of that thing and be used for another purpose and by another user” (Hoeyer, 2020, p. 2). In a similar way, the value of health data is not absolute or intrinsic but is always related to the context (Fiske et al., 2023) and to the actors and purposes of use (Wilson et al., 2020).

The term data donation is often used to describe the act of making data available for research, highlighting the relational nature of this practice. It typically implies a non-commercial intent (Prainsack, 2019; see also Aitken et al., 2016) and aligns with the idea of a gift—something offered beyond immediate exchange. Yet, a gift establishes social bonds through cycles of reciprocity (Mauss, 1990), even if delayed or indirect. It thus can serve as a “systematic means for individuals and groups to articulate and reciprocate recognition, and thereby determine and shape identities” (Hummel et al., 2019, p. 29). In this sense, data donations can carry expectations, such as contributing to the welfare state with the hope of future benefits like appropriate medical care (Felt et al., 2009). While we draw on the sensitivities the donation metaphor brings, this article adopts the term data provision for research to better reflect citizens’ diverse valuations of making data mobile and reusable (Metzler et al., 2023), without assuming a fixed relational model.

With this in mind, we adapt the notion of data journeys (Bates et al., 2016; Leonelli, 2020) to trace citizens’ visions and imaginations of appropriate sites and practices for (their) health data. Data journeys designate the “movement of data from their production site to many other sites in which they are processed, mobilised and re-purposed.” (Leonelli, 2020, p. 9) The concept of data journeys is grounded in the observation that all data result from “contingent and contested social practices” (Dalton and Thatcher, 2014), which privilege specific understandings of the world. To focus on the movement of data between and through sites of data practices (Bates et al. 2016) and being attentive to the fact that “values of data are not pre-defined, but emerge and change over time and space as they flow through interconnected but different socio-cultural contexts each with their own conceptual frameworks and value systems” (Bates et al., 2015, p. 14), will sharpen our attention to how this matters to citizens. When the latter are asked to contribute to data's movement by providing data for research (or allowing the secondary use of health data), this implies that they need to make an assessment whether they accept data entering into relation with other actors, sites and practices and, possibly, obtain new meanings and realize different values. By being attentive to citizens’ anticipated data journeys, we draw on Bates and co-authors’ emphasis on the socio-material nature of data movements and Leonelli's notion of data mutability—the idea that data are continually shaped by the assemblages they become part of, which in turn influence how they are understood and valued.

Valuation constellations

When citizens consider making their health data available for secondary use via a data infrastructure, they engage in the social practice of valuation. This involves assessing the value of the data itself, the infrastructure and the relations it fosters, the actors managing it, potential future users, and the broader governance structures. These (e)valuations influence whether citizens perceive the process of data provision as reasonable and aligned with their values—such as equitable access to healthcare or minimizing power differentials. As noted earlier, the value of data is always context- and purpose-dependent. Data should be understood as continually journeying through different sites and actor constellations, rather than as a static entity. The specific value health data holds, thus, varies: it is different for tech corporations, for citizens contributing data, and for researchers using it—and even the same actor may value a dataset differently depending on the context or situation (Wilson et al., 2020, p. 2). Moreover, datasets can shift in value as they move into new relations. Accordingly, Wilson and colleagues advocate for speaking of values—in the plural—when discussing datasets, urging an investigation that is attentive to diverse, situated valuation practices. This is much in line with Tamar Sharon's (2018, p. 4) argument that a framework that simply contrasts “public benefit” with “private, corporate gain” is too narrow, overlooking other evaluative regimes at play. She reminds us of the plurality of visions of the common good that can be mobilized in the context of data provision for research.

In order to better understand how citizens develop a position on the question whether they should provide their digital health data for research and to account for the multiplicity and context-dependence of values, we decided to follow the suggestion of Waibel et al. (2021) to think in valuation constellations when studying citizens’ assessments. This means that we do not focus on singular moments of valuation, treating them as isolated events as this would “neglect the interconnectedness of moments across situations and social fields” (Waibel et al., 2021, p. 34). Instead, we see citizens’ valuations of the health data platform and the data provision process as “temporally and spatially situated” and pay close attention to how “valuation situations are linked in various ways” (p. 35) and what role interactions between different participants in our research play in valuation practices. Discussion groups—particularly due to their duration (Felt, 2016)—offer ample space for the development of complex interactions, allowing us to observe multiple valuation constellations and the shifts between them.

Valuation constellations have several components: the valuee (what exactly gets valued when thinking about a health data platform and providing data for secondary use), the valuator (in their diverse potential roles as citizens), and the audience toward whom the expression of value is (symbolically) directed (Waibel et al., 2021, p. 38f.). Furthermore, rules of valuation (p. 41f.), often defined by the setting in which a valuation takes place, and infrastructures of valuation (“the material contexts that facilitate or restrict valuations, p. 48), matter. Citizens’ assessment of the provision of health data for research is thus assumed as neither clear-cut nor stable across situations during a discussion. In taking the stance of the valuator and speaking to various projected audiences and about specific of parts of the platform infrastructure and its functionalities, citizens can assume diverse roles in making situated assessments. They might also change roles within one conversation, e.g., at one time speaking as a citizen concerned about data protection, in another moment drawing on previous experiences as patients or speaking in the name of others who are not at the table. Furthermore, actors might value different parts of the data infrastructure differently, embracing some elements while being concerned about others or even rejecting them. An analytic angle that is attentive to the “triad of valuator, valuee and audience” (p. 35) helps us grasp the complexities and multilayeredness of assessments and to observe how valuations are interconnected. To understand such multi-situational valuation constellations will then be essential for building a robust health data infrastructure as imagined in the framework of the EHDS.

Material and method

This article is based on material generated in the large-scale transdisciplinary Horizon 2020 project Smart4Health, in which we were involved as social science partners. The project assembled a consortium of partners to develop, test, and validate a health data platform prototype for the European Electronic Health Record exchange. This included a health data platform, a research data platform, and an app to trigger data provision for research, based on broad consent. The ‘object’ of development, thus, was a complex sociotechnical infrastructure (Star and Ruhleder, 1996) in the health domain and the relations it could or should enable (Felt et al., 2023). Our team was responsible for the establishment and implementation of a co-creation environment—ensuring the adequate involvement of future users in the development process—in which various methods (workshops, card-based group discussions, semi-structured qualitative interviews, scenario-based prototype testing, think-aloud techniques, questionnaires, digital living labs) were employed to develop user requirements, assess their implementation, as well as test and validate platform features with citizen and professional users from the healthcare field. ²

For the analysis presented in this article, we draw on four 4h-long card-based discussion workshops (DW), which involved altogether 23 citizens with diverse socioeconomic backgrounds and had them engage with the different features and processes of the entire health data infrastructure developed in the project. ³ Furthermore, nine qualitative semi-structured interviews (INT) with citizens gave detailed insights in their positioning on the informed consent process for data provision. In addition to this, on occasion, we employed further qualitative material from our additional citizen engagements, e.g., situations where some features of the platform were tested, (APP_test), in order to deepen or to validate specific dimensions of the analysis. The discussion workshops were conducted in a face-to-face setting in September 2019. In these workshops, we started with a brief introductory exercise for citizens to outline their position toward health data infrastructures more generally. The main part consisted of a structured exploration of the entire platform infrastructure via a simulation of their user journey through the platform, using cards that specified the different situations of platform engagement. This made it possible to discuss in some depth the situations they could encounter when interacting with the future health data platform and having to take some form of action (e.g., collecting health data, sharing data with a health care professional, or providing data for research). The discussion workshops concluded with a brief exploration of the key values citizens considered important for platform development and implementation. The qualitative semi-structured interviews were conducted in February 2021 (remotely, due to restrictions during the COVID-19 pandemic). In these interviews, participants assessed the informed consent form and process for the provision of data for research that had been developed by the consortium during 2020. The focus here was on the concrete dataset to be provided, possible data journeys (where data could or should not go) and governance questions.

In our analysis, we followed a thematic coding approach. In terms of the interviews, we openly coded the transcripts of the nine remote citizen interviews regarding valuations of data provision for research. We organized the codes and interview segments according to the following six themes: (1) situated understanding of data, (2) underlying assumptions of “just returns” for their contribution, (3) visions of good and trustworthy governance, (4) imaginations of potential data journeys to (in)acceptable locations/actors, (5) projections of potential health futures and (6) perceptions of risks and responsibilities. For each interview, we then mapped valuation constellations of valuee, valuator and audience, as well as the roles taken. The transcripts of the four discussion workshops were coded with attention to the interactional elements, specifically identifying particularly apparent and/or interesting valuation constellations and shifts that could be observed. The research team then met in several face-to-face analysis sessions, in which we discussed in-depth interpretations of specific interactions, mapped and aligned the codes and categories, and collaboratively organized our findings in the three central perspectives, which we present in the following section.

Findings

In what follows, we investigate the valuations of citizens when pondering over whether or not they should/would provide their health data for research. Grouping our observations in three main perspectives for how citizens approached this question, we will first explore how citizens’ attribute value to data. We will then engage with how they relate to actors using data and the anticipated use contexts. Finally, we will look into how citizens perceive those “controlling” the data, which highlights issues of governance and choice.

Multiplicity of data values

The statement that health data holds intrinsic value has become a prevailing trope in recent years (Fiske et al., 2023), a sentiment that was also well reflected in our empirical material. Among our participants, there was a broad and quasi-immediate consensus that data is, by nature, a valuable asset. This assessment echoed the market repertoire of justification that often frames data as key driver of wealth creation (Sharon, 2018). One such instance from our discussions illustrates this perspective, with three participants swiftly agreeing that, in contemporary society, data can be equated to money—highlighting its undeniable economic significance.

DW1_IP2: I have to say, data are the currency at the moment. There is nothing more valuable

DW1_IP1: than data, yeah.

DW1_IP2: than data today, yeah?

DW1_IP3: Yes, that's right.

Another participant drew a direct comparison between data and cash, framing it as an asset in a continuous cycle of value creation: once data enters circulation, it catalyzes the generation of wealth. In this view, digital data is the asset of the digital economy—a narrative readily embraced by our participants. While benefits are assumed to unfold for everyone through economic growth, a typical assumption in the market logic (Sharon, 2018), citizens voiced concerns that the benefits of data-driven economic expansion may not be equitably distributed and could, in fact, result in harm or disadvantage for them.

The combination of assumed high monetary value of data and concerns about its potential exploitation prompted citizens to expect stringent protective measures. When asked where they saw the appropriate, i.e., sufficiently protected, place for health data, one participant used the analogy of “the national bank, because these data are worth pure gold, and the national bank protects the gold reserve and money” (DW4_IP1). Citizens frequently used analogies to banking to emphasize the need for a high-security environment to protect their data. This comparison also emerged in their visions of data protection and control processes, pointing to banks as institutions that have already developed trusted and secure systems. By positioning themselves as clients who entrust their savings to a bank, participants were able to express both their expectations and concerns about the handling, security, and protection of their data.

The high general value of health data was rarely questioned by citizens—as long as their thinking remained within the general market logic. In this frame, data were seen as intrinsically valuable, and citizens adopted roles such as the informed participant or the client who trusts institutional safeguards, much like with other high-value assets. However, when asked to assess the specific value emerging in concrete, situated practices, citizens became more cautious—both in their perceived ability to assess such scenarios and in their willingness to take on an active role in them. The following participant opens such a reflection:

DW3_IP3: What would I donate? I cannot judge that, if I am not a physician, yeah? Then maybe it would also not make sense, no?

They point out that the concrete selection of data to be provided would be overwhelming for an ‘ordinary citizen’ who lacks the expertise to assess this choice. To take an active role for a citizen within a logic in which “healthcare and health science are often reduced to a logistics process of data flows between scientists, practitioners and patients” (Sharon, 2018, p. 6) would then mean to identify potential value and getting the right data, i.e., useful data, into circulation. This, however, requires expertise that cannot automatically—so the argumentation—be delegated to them. Speaking from the position of an active but overwhelmed citizen, what gets evaluated here is not so much the quality and quantity of data but citizens’ own capability of making a meaningful assessment of which data to provide.

Many participants shared the view that they would not be able to select specific datasets for secondary use in a meaningful way. Still, they wanted to be able to decide on the general path the data could take, and with this the relations the data could enter into. We can see this particularly well in the following exchange.

DW3_IP3: The selection is quite the challenge (…) for the patient: what do I share and what do I not share, no?

DW3_IP1: (…) I [do not] simply donate x-ray images [and say] do whatever you want with it.

DW3_IP2: So, concretely for a research project, for instance.

DW3_IP1: Yes (…) I would like to know what it [the research] is about. Yes (….)

DW3_IP3: For human research yes, but pharma companies (…) well, I think, for general research (…) there it would really be very important, no?

In this interaction, the participants shifted the focus from the concrete data to be selected towards deciding on its anticipated pathway, thereby reinstating their active role. Several potential dimensions can be identified here: the research purpose, which would allow them to assess whether the potential new contexts and relations of health data are appropriate or not; the concrete research project as information from which they could infer the appropriateness; and the actor groups who may use the data, thereby touching on the problematized configuration of data use by commercial actors, which has been well described in the literature (Aitken et al., 2016; Cascini et al., 2024).

Having the right and possibility to define the general pathway would prevent researchers from doing “whatever [they] want” with the health data provided for research, thus sustaining the data value as much as their active position. This formulation was also used in another group discussion. In both cases, the participants clearly did not want to provide data without knowing where it might end up and without being able to assess the purpose or context of use. They did not want to delegate the decision of what may be done with ‘their data’ to someone else and risk a value shift, given that the value of health data is always related to its context and purpose (Fiske et al., 2023). This was further elaborated by the following participant:

DW4_IP3: Not just generally, yes, here you have my data, do whatever you want with it. I would also like to know for what. (…) What came out, whereby have I maybe helped with my data, yes?

Here we see the role of the supportive/active citizen who wants to contribute data to research and potentially also get a positive return from knowing that they “maybe helped” through providing their data. A “do whatever you want” attitude would somewhat devalue both the data to be brought into circulation and the act of provision. The citizen participants thus did not conceptualize the data as entirely separate from them or as something they no longer care about once they agreed on its provision for research; the sense of attachment does not end with the act of provision. This is in line with Pinel and Svedsen's observation that “movement (…) comes with attachments to places and people. That is, even when data flow towards new fields, they are materially connected to specific places, groups and individuals who helped create them or previously used them” (2021, p. 2). The valuation of the data provision process hereby highlights the attachment to data and its value that has an affective dimension for citizens. For them to be able to ensure that actors cannot “do whatever they want with it” means to keep the value of the data intact that has been provided by them—in the here and now and in the future.

Assessing data relations: Transparency, symmetry, disentanglement

As indicated in the previous section, when citizens anticipated data pathways, they assessed the relations they wanted to articulate and strengthen through their data provision (Prainsack, 2019), and whether their concept of data value mapped with the value systems of the contexts they flow through (Bates et al., 2015). To be able to make such an assessment, citizens demanded transparency on the situation and modes of value generation, given that data value is related to context, purpose of use, and actors involved (Fiske et al., 2023; Wilson et al., 2020). In their explorations, our participants largely embraced the role of generous research supporters, seeing themselves as actively helping and contributing to research. For many, it was without question that health data collection is connected to value prospects and the expectation of future benefits. And in principle, they saw nothing wrong with this, as efforts and resources would need to be invested by others in collecting health data and making it available through developing an enabling infrastructure. However, in exchange for providing what they perceived to be their health data, they wanted to be taken seriously as equal partners. This included being addressed with unambiguous statements—“talk straight!” (INT_IP8)—and have transparency on data circulation, the aims and logics of value generation and the actors involved in it. All this would allow them to assess whether activities are in line with their own understanding of data value. Conversely, a disconnected sense of “shooting data up into the cloud” (APP_test_IP4) without understanding where it has gone, who is harnessing it and for what reason, can lead to feelings of anxiety and would not necessarily invite providing data for research.

A second crucial dimension in citizens’ assessments of the relations that the data provision forms or strengthens was whether or not the relations are symmetrical, which allows the integration of value systems that sometimes seemed incommensurable. Across the material, participants drew on the notion of the donation to make sense of data provision, which means to give it away for free with the expectation that it is used for the collective good (Skovgaard et al., 2019). However, many participants were wary about making health data available for free when they could theoretically be transformed into a commodity and taken out of circulation for the collective. The pharma industry, in particular, was perceived as engaging in such problematic transformations. In one discussion, participants were rather harsh in their assessment of the pharma industry:

DW2_IP1: Well, they are crooks, yes.

DW2_IP3: They are crooks, definitely.

While not all assessments of actors from the pharmaceutical industry and their profit-driven practices were as explicit as in the previous quote, a general sense of distrust toward them remained palpable. There were fears that they would take advantage of citizens’ voluntary contributions and exploit their generosity, for instance, by later overpricing medication or by patenting and thereby restricting access to treatments. Our participants sought reassurance that the nature of their donation—offered for “general humanistic purposes” (DW3_IP3)—would be respected, and that corporate interests would not ultimately constrain the benefits of their well-intentioned contributions to the collective good.

Value generation and value distribution, thus, must be symmetrical for citizens to consider providing their data in the first place. Symmetry in this context means data provision and data use do not change the tacitly assumed framework. If citizens provide data freely, it must be ensured that benefits can also be freely returned. Symmetry can be framed collectively, in the sense of a “social benefit [that] is to be achieved” (DW4_IP1). For some participants, it was important to emphasize that benefits must be public and fair and not just materialize for those who can afford expensive medication, reproducing preexisting inequities in healthcare. The outcomes of research based on data donation thus should “not just benefit the rich people, but really [be available to] everyone who needs it” (DW3_IP3). Expectations of symmetry can also relate to more direct beneficial effects, such as more personalized healthcare, receiving information on research that was conducted on the basis of one's data, or, as in one case, indirect benefits of preferential treatment, based on seeing themselves as part of the chain of value generation: “If I am taken to the hospital (…) then there should be a benefit for me” (INT_IP5). In other cases, participants identified the potential for individual benefits when discussing rare or life-threatening diseases or chronic conditions, through the faster circulation of data and, subsequently, research insights into the clinical/practitioners’ realm.

In contrast to this, asymmetrical value generation and distribution means that corporate interests stop the return of benefits to the collective realm or that corporations yield economic gains based on something that was given in a gift logic. There were some instances of citizens developing strategies for dealing with perceived asymmetries, for instance, by jokingly turning the provision relationship around—“pharmaceutical companies, they should donate something to us, no?” (DW3_IP3)—or demanding concrete savings—“I would also like to see a discount on my medicine” (DW2_IP1). In this way, the potential asymmetry in the generation and distribution of value was remedied by them changing the logic and demanding economic benefits: if the pharma industry makes economic benefits and the returns are also based in an economic logic, the exchange's character is again symmetrical and, thus, appropriate.

Finally, having the possibility of initiating the end of potential data journeys and disentangling established relations was another key element of citizens considering providing health data for research.

APP_test_IP4: If my data will be anonymized, if they could trace it back to me (…) but also if you wish to withdraw your consent - if it's possible (…) - what traces will be left of you?

A key notion here is “the trace,” i.e., data traces, that can come to haunt us (Thylstrup, 2019). Both instances of traces/tracing point to the assumption that even if data has been anonymized or deleted, there may still be an imprint that does not disappear. This is related to data mutability and data having been integrated into broader datasets, a concern that the following citizen expressed:

INT_IP1: What does withdraw actually mean when the data is already shared, when it's already part of (…) a larger bucket of other data. Is it really withdrawn from there or does it just mean, data generated anew will not be added anymore?

Extending the withdrawal of consent to the withdrawal of the data itself, they note that data mobility is crucial for it to be useful in research and, thus, valuable. This also means that if one withdraws data, it might well have become part of a new dataset and analyses, which calls into question the possibility of deleting data from established datasets that are the basis for scientific research (hence the possibility of removing traces). The skepticism about the end of data journeys and the virtual impossibility of controlling this brought to the fore the demand for transparent governance and accountability as well as expectations of institutional responsibility in dealing with the risks associated with data provision for research, to which we will turn next.

Choice by proxy: Governance and responsibility

In this section, we shift the attention to the relations citizens envisaged with those in control of their data. By looking at how they assessed the governance of data provision, we engage with another layer of valuation that mattered for citizens finding a position towards secondary use of health data. As Waibel and colleagues have highlighted, moments of valuation are interconnected across situations (Waibel et al., 2021). The user role foreseen for citizens in the health data platform had primed them as empowered: they were supposed to collect and manage their health data in their platform account and could in detail decide with whom to share what (or not). Many initially approached the data provision process from the active and empowered user position inscribed in the narrative of the health data platform and projected it also onto data provision, expecting fine-grained decision-making possibilities.

DW4_IP3: I would not simply generally provide my data so that any scientific research can be done with it, but I want to be informed: what kind of enterprise is this; is it (…) for the pharmaceutical industry or is it a syndrome that is being investigated (…). Every time, my data are being used, I want to know, for what.

This participant wanted to be kept in the loop to be informed who the recipient will be in each case and decide accordingly, thus implicitly arguing for a form of dynamic consent (Budin-Ljøsne et al., 2017). Such an approach would keep the attachment to data and its situated value intact, and would also stand against the envisaged “detachment of data in new health data spaces” (Åm et al., 2025, p. 10). However, others questioned what degree of choice would be appropriate and did not want to participate in extensive repeated engagement processes that would go beyond defining context and purpose, as the following quote illustrates.

INT_IP6: Well, I would then have to engage with all different kinds of institutions to tick off. No, I want my data to be only used for university research. So no, I think that would be going overboard.

A recurring theme in our material was that decisions on the pathway are made for a reason and should be respected, now and in the future. Also, concerns were voiced that too much choice could become a burden and not everyone can fulfill the demands that go along with the active user role, in particular, “the generation (…) 70+, who do not have the technical preconditions and also do not want to communicate [health data] via the Internet or apps” (INT_IP7). While constructing themselves as in principle capable of making choices, this was seen as challenging for those “others” who may lack digital infrastructure literacy (Gray et al., 2018) and an in-depth understanding of data, who may not have resources available to engage with their digital data, or in whose lifeworld digital data may currently have no relevance.

In contrast to the above-mentioned ideal vision of a more dynamic consent, our analysis in the project is based on the data provision process built on a broad consent approach (Steinsbekk et al., 2013), which pre-framed citizens’ choices. Citizens could only select which of their collected health data types they wanted to make available for research. However, they could neither select nor exclude those accessing the data (e.g., a specific research project or a group of actors, such as commercial companies) or define a specific research purpose. Instead, the choice on context and purpose was outsourced to a Data Access Committee (DAC). From the project side, the DAC was envisaged to determine the scope of data access, by whom, and for what purpose, according to specific and publicly available data access criteria. By citizens, the DAC was perceived as a powerful agent in the data provision process, as “they make the ultimate decisions. It just seems very authoritative” (INT_IP1). Such a configuration means that citizens need to trust an entity to act on their behalf, deciding who can access the data they collected and provided.

Understanding the DAC as proxy for citizens’ choice and decision-making, citizens thus began to assess the DAC in lieu of those actors, places, and purposes the data would ultimately be entangled with. To come to such an assessment, they requested detailed information about the DAC's composition, the criteria for accessing data, and how rigorously these would be applied. The trustworthiness of the DAC and the reliability with which it would apply the specified data access criteria were seen as depending on its composition, as “the promised procedures are only as good and reliable as the people responsible for them” (INT_IP5). Moreover, for citizens, positioning themselves as active and critical, it was not only about the composition of the DAC as an institution but also about the affiliations and background of its members, how the committee came into being in the first place and who was involved in this decision.

If citizens accepted that the DAC as proxy makes decisions about who may use data for research and for what purposes, they also expected a robust distribution of responsibility regarding the risks inherent in data provision. In a dedicated section of the informed consent for data provision, citizens can read about (1) the central risk of disclosure of private information and the potential but concrete consequences, e.g., feeling stress, anxiety, or embarrassment due to disclosed information, and (2) about being informed of a data breach within the timeframe given by the GDPR. In principle—and in line with the direct form of communication mentioned in the previous section—such transparency was appreciated.

INT_IP1: I like that it's just very clearly stated, these are the risks (…); but also, we’ve taken these measures (…), we’re following the law and obviously there's always remaining risks. But I just felt (.) I just liked reading it; it felt very honest.

However, the concrete examples also created feelings of unease. Particularly, those who had initially favored opting into data provision were taken aback by the realization that data might be misused and that the security procedures were no guarantee. Even if initial narratives included statements like “everyone can know everything about me” (INT_IP5), the concrete risks outlined raised awareness of what this could mean in practice and made citizens reconsider the provision. The reasoning for this, however, was not merely grounded in concerns about the risk itself, that the transparent information had brought to their attention, but also regarding the responsibility for its potential consequences, which these citizens perceived as being shifted to them. In other words, those in charge of the platform were seen as absolving themselves of responsibility if something went wrong, through a preventive logic of transparency: citizens had been informed of risks beforehand, had thus taken an informed decision, and would be informed should problems occur.

INT_IP5: For me that again is only a (…) safeguard. Yes, we promise it to him, but we do not guarantee for anything.

Thus, being informed and providing consent on this basis cannot absolve the platform provider of responsibility by shifting it onto citizens, especially while control over the data's journey remains with the DAC. Because if things go wrong, currently only citizens seem affected, which led to questions such as “What do I get in return other than a depression?” (INT_IP6), or would one “become eligible for some kind of reimbursement” (INT_IP5). For many citizens, the question of responsibility thus needs to be addressed fairly and more symmetrically, if the platform provider wants to ensure a stable trust relation.

Discussion and concluding remarks

A thorough analysis of the valuation constellations emerging from our interviews and discussion groups has shed light on how prospective users conceptualize their willingness to make health data available for research purposes. Synthesizing these insights, we identify three overarching themes that are critical to the governance, implementation, and ongoing maintenance of digital infrastructures. These themes, we argue, are essential if the envisioned transformation of healthcare and research through digital means is to be both sustainable and effective.

First, citizens engage in nuanced and dynamic (e)valuations when considering whether to make their digital health data available for research. Rather than holding fixed positions, they continuously shift perspectives depending on the specific aspects they are confronted with. This fluidity in thinking highlights the importance of understanding not just what is being valued, but also which roles individuals adopt in making these assessments, the implicit norms they follow, and the forms of reasoning they regard as legitimate. A case in point is the principle of reciprocity. Our analysis shows that simply invoking the public good or promising general benefits to healthcare is insufficient. What matters more to citizens is not whether a party stands to gain from their data, nor whether they receive a direct personal benefit, but whether such interests align with their own value frameworks and can be seen as legitimate by them. Rather than expecting immediate or directly perceptible returns, participants anticipate what we term “mediated reciprocity”: a reasonable and credible assurance that their contribution will indirectly support tangible, long-term improvements in the healthcare system. It is legitimacy, rather than immediate benefit, that proves decisive in their willingness to share data.

Second, trust or skepticism toward data provision for research is neither fixed nor absolute; rather, it reflects a situated (e)valuation of the broader digital landscape. This landscape extends well beyond health data and the necessary technical infrastructures to include the actors involved and the envisioned mechanisms through which value is generated. Citizens assess not only the data itself but also the new contexts it enters and the relationships it establishes. Researchers, policymakers, and infrastructure designers often emphasize the collective benefits of health data use to encourage public participation. However, this strategy also creates normative expectations among citizens. These expectations are not limited to improved health outcomes; they extend to how actors manage their roles and responsibilities. Participants in our study expect those overseeing data collection and use to make ethically well-balanced decisions, particularly in determining how data journeys are governed and how the resulting value is distributed. Importantly, this expectation is not rooted in a simplistic rejection of commercial interest. Rather, citizens call for a proportional and just return for society—what they seek is not the absence of profit, but the presence of fairness in how benefits are generated and shared.

Third, temporality—though central to the dynamics of health data infrastructures—remains largely implicit in public discourse. While citizens are asked to provide their data in the present, the actual use of that data for research and the realization of its benefits are deferred to an uncertain future. This future is often described as open-ended, making it difficult to predict when, how, under what socially and technically altered conditions, or even whether meaningful outcomes will eventually materialize. As a result, citizens draw on their past and present experiences to inform decisions about data sharing, using what is known now to navigate what remains unknown. This temporal gap becomes even more significant in light of the fast-paced, constantly evolving nature of digital health environments. People are being asked to make decisions today within a context characterized by both high expectations and deep uncertainty. Their valuations—and ultimately their willingness to contribute data—occur within this tension between promised futures, current realities, and past experiences. In this context, we emphasize the strong sense of attachment many citizens feel toward their personal data. These affective entanglements shape how they imagine the future uses of their data, including potential benefits and harms. This emotional dimension includes both trust and apprehension, anticipating how data traces might be interpreted, reused, or even misused in ways that could matter profoundly in a future quite different from today. Such perceptions highlight that data provision is not a one-time transaction but a deeply temporal and relational act.

In conclusion, we underscore “relational transparency” as a fundamental precondition for the robustness of sociotechnical endeavors such as the EHDS. For citizens to make informed decisions about whether to contribute their health data for research, they must be able to assess not only the infrastructure itself, but also the network of actors and relationships it sustains. Transparency must extend beyond technical functionality to illuminate where data may travel, who may access it, and how value will be generated from it. Such relational transparency is not simply a matter of openness; it is essential for building and maintaining trust. It enables citizens to evaluate the legitimacy of data use based on the roles, intentions, and practices of the actors involved. Given the inherent mobility and mutability of digital health data, transparency becomes even more complex—yet all the more vital. Crucially, as we could show through our analysis, the valuation of digital health infrastructures is not a one-time, binary judgment. It is a dynamic and ongoing process, shaped by evolving experiences, shifting contexts, and emerging futures. As digital health systems develop at a rapid pace, both design and governance must be sufficiently adaptive to be able to remain attuned to the changing ways in which users understand and value their participation. Sustaining the legitimacy and value of health data infrastructures demands continuous effort, both in how these systems are materially built and in how they are governed, and thus a response-able and inclusive way of continuing the development of these cross-border health data infrastructures.