Adopting EOSC on the ground – Integrating (European) Research infrastructure into national institutions

Stefan Reichmann; Dimitri Prandner; Barbara Sánchez Solís; Katharina Flicker; Ilire Hasani-Mavriqi

doi:10.1515/abitech-2025-0059

Article Open Access

Adopting EOSC on the ground – Integrating (European) Research infrastructure into national institutions

Stefan Reichmann
Stefan Reichmann
, Dimitri Prandner
Dimitri Prandner
, Barbara Sánchez Solís
Barbara Sánchez Solís
, Katharina Flicker
Katharina Flicker
and Ilire Hasani-Mavriqi
Ilire Hasani-Mavriqi

Published/Copyright: August 7, 2025

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From the journal ABI Technik

Abstract

The contribution traces the adoption of the European Open Science Cloud (EOSC) by Austrian research-performing institutions. Starting from its trajectories, the article sketches how Open Science has been imbued with competing meanings, resulting in conflicting interpretations of the goals of EOSC. In this, official EOSC narratives have moved away from the current Open Science discourse, which accounts for the hesitancy of researchers and institutions towards EOSC. This is made plausible by contextualizing Open Science within the broader context of science studies to argue that competing narratives result in persistent tensions which surface in moments of practical implementation. As a result, EOSC operates in a highly contested environment, existing within a broader matrix of European policy frameworks, and in this sense, EOSC is susceptible to contradictory interpretations. Its foundational philosophy, the FAIR Guiding Principles, tacitly universalizes one set of practices, norms, and values as the sole reference point. Through anecdotal evidence from research support staff active in the implementation of EOSC, the article describes how the tensions embodied in the development of EOSC are perpetuated “on the ground” of research practices.

Zusammenfassung

Der Beitrag zeichnet die Akzeptanz der European Open Science Cloud (EOSC) an österreichischen Forschungseinrichtungen nach. Ausgehend von der Entwicklung von Open Science skizziert der Artikel, wie der Begriff mit widersprüchlichen Bedeutungen aufgeladen wurde, was zu unvereinbaren Interpretationen der Ziele der EOSC geführt hat. Dabei haben sich die offiziellen EOSC-Narrative vom aktuellen Open-Science-Diskurs entfernt. Dies erklärt ein Stück weit das Zögern von Forschenden und Institutionen gegenüber der EOSC. Der vorliegende Text diskutiert die mit Open Science verbundenen Spannungen im breiteren Kontext der Wissenschaftsforschung. Diese Spannungen treten vor allem dort zu Tage, wo konkurrierende Open-Science-Erzählungen konkrete Umsetzung erfahren. Infolgedessen agiert die EOSC in einem höchst umkämpften Umfeld, das sich in eine breitere Matrix politischer Rahmenbedingungen der EU einfügt und in diesem Sinne für widersprüchliche Interpretationen anfällig ist. Die grundlegende Philosophie, die FAIR Guiding Principles, verallgemeinert stillschweigend eine Reihe von Praktiken, Normen und Werten als einzigen Bezugspunkt. Anhand von Erfahrungsberichten von Mitarbeitenden der Forschungsförderung, die an der Umsetzung der EOSC beteiligt sind, wird in diesem Artikel beschrieben, wie die Spannungen, die in der Entwicklung der EOSC zum Ausdruck kommen, in der Forschungspraxis “vor Ort” fortbestehen.

Keywords: EOSC; Open Science; social construction of technology

Schlüsselwörter: EOSC; Open Science; Social Construction of Technology

1 Introduction

A kick-off workshop in Brussels at the end of March 2025 started the so-called build-up phase of the EOSC Federation.^[1] The event marked an important milestone in a process begun in 2024, after the EOSC Federation promised to render the European Open Science Cloud (EOSC) operational by the end of 2025. The present article takes this process as a “strategic research site”^[2] to reflect on two key questions:

What does Open Science mean in the context of the EOSC?
How does the Open Science concept of the EOSC relate to the actual activities and understandings present at national and institutional levels?

Inspired by the Social Construction of Technology (SCOT) approach, we suggest that the development, adoption, and stabilization of innovations is a deeply social process, with competing actors struggling to enforce their specific vision. With the establishment of the EOSC Federation Build-up Group in March 2025,^[3] the development of the EOSC has now entered a crucial phase, which provides ample opportunity to study the tensions and conflicting visions of Open Science it embodies. In the following pages, we touch upon several aspects fundamental to studying the science-policy interface, as they concern the nature of Open Science, the role of evidence in policy-making, and the role of knowledge infrastructures. Commentators have become increasingly skeptical, not with respect to the potential of Open Science but with respect to its current trajectories.^[4] There is already a “mismatch” between norms, (research) practices, and research-performing institutions, rooted in conflicting ideas that shape the understanding of academic work.

We begin by laying out the trajectories of Open Science (section 2), to then explore those trajectories by looking at the inherent structural tensions in the context of the EOSC, and how these tensions can be conceptualized (section 3), before locating the origins of the conflicts in the very idea of the EOSC (section 4), and introducing case studies of early adoption of the EOSC in Austria (section 5). The article concludes with a brief discussion of the findings (section 6).

2 Trajectories of Open Science

2.1 From research practice …

Since the early 2000s, Open Science has been a rallying call for researchers hoping to make research more transparent, accessible, and sustainable. This – largely idealistic – claim has been justified, more recently, by an appeal to the so-called reproducibility crisis,^[5] and accompanying calls for more transparency and accountability in science. Open Science entails a wholesale reform of scientific practice that proposes a (technical) “fix” to various problems of academia. In this, the Open Science movement presents a response to various large-scale transformations of academia brought about by digitization, commodification,^[6] and globalization, in which new technologies and an increasingly mobile workforce^[7] massively increase the speed and volume of discoveries,^[8] which has spawned various crises: the reproducibility crisis;^[9] the crisis of peer review;^[10] the crisis of the academic labour market,^[11] and the crisis of open access publishing^[12] Universities struggle to adapt to these transformations, key to which is a renewed attention on the diversity of research outputs and a profound rethinking of scholarly communication, with the aim of making the most of all kinds of research outputs (data, models, algorithms, software, instruments, to name but a few). Open Science calls for a re-examination of what research outputs should be shared, with whom, and when,^[13] continuing a long tradition of increasing academic and political accountability^[14] reaching back, at least, to the work of Karl Popper, on open societies,^[15] which defends the view that democracies are distinct from dictatorships to the extent that their decision-making processes are subject to scrutiny and critique, and Robert K. Merton, on the normative structure of science,^[16] which develops the view that in order for science to function properly as the purveyor of certified knowledge, researchers adhere to a set of (now dubbed Mertonian) norms – universalism, disinterestedness, communalism, and organized skepticism.^[17] Open Science in its various forms has been positioned simultaneously as a panacea to the various crises of academia^[18] as well as a sought-after policy response to increasing pressures from the data economy, a welcome opportunity^[19] to remodel research practices, evaluation, and governance.

2.2 … to research policy …

In response to these developments, research-performing organizations are increasingly implementing Open Science policies as well as introducing research-support services.^[20] Open Science has been picked up by (European) policymakers in the early days of the new millennium, linking openness (and, to a somewhat lesser extent, accountability) in research explicitly to challenges to the European Single Market brought about by digital transformation. In this, Open Science has been put into the context of other European Policy Initiatives, such as the European Data Act^[21] and the creation of Common European Data Spaces.^[22] The European Open Science Cloud was launched in Vienna in 2018^[23] as a process integrating extant European Research Infrastructures, to make digital research objects accessible to researchers in Europe under the same terms and conditions.^[24] The idea of openness has been connected to the idea of a digital single market almost from the start:^[25] “European science must master the results of its publicly funded research itself […] not only open innovation was important, but also O[pen] S[cience] and O[pen] D[ata].”^[26] The accompanying interpretation of Open Science, along the lines of increasing the efficiency and velocity^[27] with which scientific products are shared, has been the subject of critique from the get-go, as it aligns with the ideas of reforming academia along the lines of platform capitalism.^[28]

Open Science has likewise been challenged for promoting a conventional idea of (data-driven) research,^[29] to the detriment of those further removed from reaping the supposed benefits of increasing datafication.^[30] This critique states that Open Science “promotes a very specific way of knowing’, encouraging a ‘digital positivism or the specific belief that the data, suitably circumscribed by quantity, correlation, and algorithm, will, in fact, speak to us’”.^[31] These discussions link Open Science to broader trends of remodelling academia according to principles of neoliberalism,^[32] which call for academia to broaden its original mission to emphasize competition, train the workforce, and foster new products and services.^[33] Further, there is considerable contrast between the institutional realities of data practices^[34] and the normative aims of Open Science.^[35] Open Science policies create unintended consequences for research institutions and researchers alike.^[36] Data sharing creates friction^[37]—problems of fit between (everyday) (meta)data practices, including “standardization frictions, temporal frictions, data sharing frictions, and frictions related to the availability of human support”^[38] – as the movement of research objects through and across infrastructures is constrained by socio-material conditions and power dynamics.^[39]

As Mirowski observes,^[40] research objects do not travel in and of themselves.^[41] In the early days of Open Science, data sharing had been readily interpreted in terms of a truism – that data provides evidence for knowledge claims and, therefore, should be shared as widely as possible.^[42] As digital research objects tend to proliferate across sites as they are shared and reused, they are transformed through processes of data cleaning.^[43] However, appeals to data mobility cannot adequately capture the multiple (epistemic, social, economic, political) dimensions of research data,^[44] as evident in the more recent discourse linking Open Science to improved research data management (RDM); there, interpretations of RDM oscillate between epistemic and administrative interpretations.^[45]

2.3 … and back: A vision for openness

The recent interest in Open Science has been informed by an emphasis on research fields that are already prone to open research practices. While understandable from a methodological standpoint, this tacitly universalizes the idiosyncrasies of these fields whenever these results are translated into research policy. This is exemplified in the work of, e. g., Sabina Leonelli on model organism research, which is “one of the most prominent and best developed arenas for the implementation of technologies and institutional regimes for the storage and mobilization of scientific data within the life sciences and thus constitutes a close approximation of what may be viewed as ‘ideal conditions’ for data travel.”^[46] There, the necessities of developing bio-ontologies explain the need for data professionals. Political science databases in the 1960s are another case in point. These originate in quantitative election research, where data dissemination was a precondition for research.^[47]

Fig. 1:

Open Science as a contested concept: Juxtaposed between ideological and institutional positions, and between science as competitive versus science as a public good

At present, the adoption of open science practices by research institutions, research infrastructures, and other stakeholders is strongly disciplinary driven,^[48] however, Open Science policies come with implicit one-size-fits all conceptions of open research practices,^[49] which are frequently at odds with the situated and contextual nature of research practices.^[50] Accordingly, this has led to modelling open research practices on the affordances of those fields where they are already common.^[51] The FAIR Guiding Principles for Scientific Data Management and Stewardship^[52] are a case in point, having been adopted as general guidelines for RDM by research institutions^[53] and research funders alike. They ostensibly provide “a set of minimal guiding principles and practices for research data stewardship in the life sciences,”^[54] and have had an astounding career as guidelines for research data management,^[55] expressing the idea – not new in itself – that scientific data should be both human- and machine-readable.^[56] Jointly conceived by stakeholders from academia, industry, research funders, and publishers,^[57] the FAIR guiding principles describe an aspirational philosophy for managing all kinds of digital research objects that, if achieved, “should enable machines to make optimal use of data resources.”^[58] In this, the FAIR principles constitute a signpost on the road to “an Internet of FAIR Data and Services [for which] a global convergence towards accessible, robust, widespread and consistent FAIR implementations is required.”^[59] They have been widely endorsed by a broad range of stakeholders,^[60] most notably by the European Commission within its Horizon2020 and HorizonEurope funding schemes,^[61] as “a minimal set of community-agreed guiding principles and practices”^[62] to enable all stakeholders to “more easily discover, access, appropriately integrate and re-use, and adequately cite, the vast quantities of information being generated by contemporary data-intensive science.”^[63] Insofar as research outputs are increasingly digitized, the FAIR principles purport to apply to all research data (management) practices.^[64] The FAIR Guiding Principles have been adopted as the official philosophy of EOSC, e. g. in the recently published EOSC Federation Handbook,^[65] but also in the EOSC Interoperability Framework.^[66]

However, as documented by a growing number of case studies,^[67] (open) research practices are extremely diverse, which seems difficult to square with the idea of a single federated research infrastructure that spans all of research under one set of guiding principles. There exists, then, a gap between the grand vision of Open Science as cast into research policy and actual research practices. These tensions coalesce in the figure of the data steward, who simultaneously caters to mutually exclusive values, norms, and practices (research versus administration, technical versus scientific contributions), a situation resembling the way middle management is expected to balance the demands of upper management with other constraints.^[68] Likewise, knowledge infrastructures, those “robust networks of people, artefacts, and institutions that generate, share, and maintain specific knowledge about the human and natural worlds,”^[69] tend to embody these tensions but have limited (self)knowledge about the contingencies of their (current) order.

3 Open Science Adoption: Research practices, institutions, and policy

Science studies offer a multiplicity of conceptual tools for describing scientific change. For instance, paradigms^[70] constitute the incommensurable (due to their multiplicity) contextual backdrops for scientific understanding, systems of ontological, epistemic, and methodological convictions that determine plausible questions, methods, and answers.^[71] Drawing both on Kuhn and others,^[72] laboratory studies^[73] proposed an ethnographically informed analysis of processes of knowledge production,^[74] to move away from studying “fixed” products of science^[75] and stress the artificiality of the scientific process.^[76] Epistemic cultures^[77] serve as a catch-all for the strategies, practices, instruments, and convictions researchers deploy in the production of knowledge. Epistemic cultures offer ontologies (what exists), epistemologies (how can these entities be known), actors, and strategies,^[78] along with distinct processes of socialization, differences that tend to disappear^[79] when focusing, merely, on research outputs. By observing how the adoption of EOSC is (not) achieved against the local, contingent, and contextual character of research,^[80] it can be shown where the logic of large technological research infrastructure projects might be (un)fit to accommodate the diversity of research (data) practices.

Indeed, while it had been a truism in descriptions of the Open Science transformation^[81] that research outputs should be shared as widely as possible to maximize their evidential potential, the data journeys research programme instead interrogates “the conditions for data movement, and the ways in which data mobility and interoperability can be achieved, from the viewpoint of the history, philosophy and social studies of science,”^[82] mindful that “transforming data into knowledge requires more than some generalist algorithms, clustering methods, robust infrastructure and/or clever apps.”^[83]

Scholarship in the Social Construction of Technology (SCOT) suggests that – similar to the way researchers “fixate” evidence^[84] in the form of published results^[85] – the development, adoption, and stabilization of innovations (as well as the products of science^[86]) result from social struggles for dominance. Innovations emerge, are adopted, and are stabilized^[87] in a process that affords considerable interpretive flexibility.

With respect to organizational innovation, neo-institutionalist perspectives in the sociology of science^[88] suggest that while this typically starts as a response to problems, adoption follows perceived legitimacy, based on “definitions, principles and purposes that are cognitively constructed in similar ways throughout the world.”^[89] For EOSC, the relevant principles have been condensed into the FAIR Guiding Principles,^[90] as has been made explicit in the EOSC Federation Handbook.^[91] In this, Open Science can be interpreted as the (tacit) universalization of values and norms^[92] by establishing one set of practices (data-driven research), norms, and values as the sole reference point. Indeed, it had been assumed that all would benefit equally from increased openness,^[93] a claim that has become increasingly untenable in light of recent studies of the conditions for the reuse of (digital) research outputs in non-western contexts, which find that (seemingly minor) social contingencies can severely hamper the production and reuse of open data.^[94]

4 A brief history of EOSC: The idea of a European Open Science Cloud

The rest of the contribution argues that EOSC, a large-scale policy process that envisions interlinking existing European research infrastructures,^[95] embodies rather than resolves these tensions. In particular, the notion of EOSC entails that all (relevant) research outputs can be digitized.^[96] EOSC consolidates competing interpretations of Open Science that are borne by different social groups, each with its own stake in Open Science and a European Open Science Cloud. The resulting tensions tend to surface when trying to consolidate disparate research infrastructures. In this, the present moment in EOSC constitutes a “strategic research site”^[97] for studying the adoption of Open Science. In what follows, we reconstruct the events that led up to this moment.

The past two decades have seen sustained professionalization of research in Europe as well as ongoing expansion of research infrastructure.^[98] This development has been supported by the European Commission (EC) since 2002 through the establishment of a broad landscape of research infrastructures,^[99] with the aim of enabling a wide range of research support infrastructures for high-quality data collection (data generating research infrastructures), archiving, provision (repository research infrastructures), and continuous training opportunities.^[100]

Following the Europe 2020 strategy^[101] that describes research infrastructures as central to scientific excellence,^[102] the EC granted the European Research Infrastructure Consortia (ERICs) a specific legal form at the European level.^[103] The idea behind these initiatives is that collaboration in data sharing and exchange offers enormous potential for scientific progress.^[104] Through a federated model, research projects would benefit from reduced platform and cloud services costs. As such, EOSC was expected to optimize the return on public investment in research, at a time when approximately 80 % of data was collected and stored in the United States, making it a strong case against US technological dominance.

The Open Science movement in Europe has gained momentum since the official EOSC launch. EOSC is recognized by the Council of the European Union as the pilot action to deepen the new European Research Area (ERA).^[105] It is also recognized as the science, research, and innovation data space which will be fully articulated with the other sectoral data spaces defined in the European data strategy.^[106] Since 2020, the EOSC ecosystem has been co-created through a series of funded projects initiated by the European Commission, as well as initiatives from Member States and Associated Countries. The EOSC Association (EOSC-A)^[107] plays a vital role in coordinating and steering these investments, maintaining a high level of engagement with the community involved in this effort, including 251 members, mandated organizations, and observers.

Implementation of the EOSC is expected to take place from 2021 to 2030, with a joint investment of €1 billion anticipated by 2027. The current implementation phase is carried out within the framework of the “European Co-programmed Partnership for EOSC”^[108] launched in 2021 and formalized through a Memorandum of Understanding (MoU)^[109] between EOSC-A and the European Commission. Member States and Associated Countries are represented in an EC Expert Group, the EOSC Steering Board. The partnership is supported by European funding of almost €500 million, matched by in-kind and financial contributions from the partner organizations. The strategic direction of EOSC is defined by the Strategic Research and Innovation Agenda (SRIA)^[110] which is jointly developed by the entire EOSC community. SRIA defines the framework for future research, development and innovation activities, providing the necessary foundation for EOSC-A to align and mobilize various components of EOSC in a synchronized manner. The SRIA also serves as the basis for the Multi-Annual Roadmap (MAR), which is regularly updated and contributes to the development of the Horizon Europe work programs. The Partnership is complemented by the Monitoring Framework (MF).^[111]

EOSC-A works towards the creation of a “Web of FAIR Data and Services” for research in Europe, where EOSC is to provide a multidisciplinary environment for researchers to publish, find, and reuse data, tools, and services. This approach is accompanied, at the discursive level, by reference to challenges such as providing support to scientific discovery, stimulating innovation by facilitating collaboration and sharing of scientific resources, increasing transparency and reproducibility, reducing data silos and duplication of effort, and facilitating interdisciplinary research and cross-sector collaboration. Of late, EOSC has been described as a mechanism for strengthening European competitiveness^[112] by creating a network of data repositories, computing resources, and services. Taken together, this makes for a very specific vision for Open Science, providing ample ground for interpretation. This brief exposition of the development of EOSC documents the hopes associated with Open Science by European policy actors. In what follows, we describe case studies of the implementation of EOSC in Austrian research-performing institutions.

5 EOSC on the ground: How European integration of Research Infrastructures is affecting research practice

The Austrian Declaration on Open Science and the European Open Science Cloud, section 4 of the Austrian Open Science Policy,^[113] commits Austria to “contribute to defining and regulating the building blocks of the open science ecosystem.” Further, the National Action Plan of the Austrian ministries^[114] defines steps for implementing EOSC activities in Austria. The EOSC Support Office Austria (EOSC SOA) was established in 2021, to support Austrian institutions in realizing the EOSC vision of creating a federated system of multidisciplinary research infrastructures. In this, EOSC SOA is the operational unit of the Austrian EOSC Mandated Organisation, a function legally performed by ACONET Verein. Founding partners include the Natural History Museum Vienna, Graz University of Technology (TU Graz), TU Wien, the University of Vienna, the Climate Change Center Austria (CCCA), Johannes Kepler University Linz, and the Academy of Fine Arts Vienna. The number of participating institutions doubled by 2025,^[115] whose commitment to collaborate has been formalized in a Memorandum of Understanding (MoU) delineating the roles and responsibilities of key governance structures (General Assembly, Management Board and Secretariat, Steering Committee, various Working Groups, and the Synergy Team, EOSC Café).

The General Assembly, EOSC SOA’s decision-making body, convenes (at least) annually to welcome new partners, elect individuals to specific positions, and exchange information. The Management Board and Secretariat coordinate the activities of the EOSC SOA and its partners, and oversee operational functions (e. g. communication, stakeholder engagement, and community building). The Secretariat is funded by the Federal Ministry of Education, Science, and Research (BMBWF). The Steering Committee provides strategic direction for the initiative, composed of one representative per partner institution, and convened by the GA. The Synergy Team, comprising the coordinators of the Working Groups (WGs), oversees the coordination of WG activities, while the EOSC Café serves as an open forum for external input and collaboration. Despite this elaborate framework, adoption of EOSC varies considerably across institutions.

On the one hand, university rectors are quite happy with the support structures and targets provided by the EOSC framework and services. It is worth mentioning that EOSC has been included in the triannual performance agreements, which form the basis for financial negotiations between universities and ministries. On the other hand, without tangible goals for EOSC, they tend to take an observing role, even while the initial set of “national nodes” are being established. There is awareness that the EOSC offers opportunities but that there are many organizational, security, and financial details still to be clarified. At the same time, other major initiatives are underway, such as the transformation of the Vienna Scientific Cluster into the Austrian Scientific Cluster, and the establishment of an AI Factory. It is not yet clear how a national EOSC node will be integrated into this network. Institutions participating in European EOSC-related projects or acting as partners in ESFRIS and Research Infrastructures have a certain head start in adopting the EOSC concept and preparing for a possible participation in the EOSC Federation. These were also the first to join EOSCA. Here, SOA is building bridges through the exchange of information and the provision of platforms. Indeed, EOSC and EOSC SOA provide a forum for research support staff to discuss organizational level policies and to provide guidance to researchers in their institution and create awareness for these issues at the local level.

EOSC and EOSC SOA are seen as a multiplier of ideas for useful tools, services, and ways in which these can be formally incorporated into established university level workflows. On the other hand, responsibility for the development, use, and promotion of Open Science tools and EOSC as a whole is put squarely on researchers, and much less on university management and central services. University management regards Open Science as a bottom-up process where researchers are responsible for using and developing ideas within institutional, national, and supranational regulatory frameworks, which aligns well with the central tenet of EOSC, to federate existing and emerging cyber (horizontal) and thematic (vertical) data infrastructures. This approach has also been adopted by the Austrian Federal Ministry of Education, Science and Research (BMBWF), which has been promoting synergies in the development of infrastructures and services in so-called “digitalization calls” since 2020.^[116]

At the local level, resources are split between existing EOSC initiatives and partners as well as central services providing a more hands-on approach to current problems related to Open Science. Here, SOA is regarded as a facilitator and source of inspiration for keeping researchers informed. These developments beg the question of what is possible within an Open Science framework. The normative ideas and regulatory imperatives are well-received, but the institutional creativity of how to implement them within existing frameworks is lacking, illustrating the tensions between Open Science discourse and Open Science implementation.

6 Discussion and conclusions: Dialectics of EOSC

We have seen how within EOSC, competing interpretations of Open Science coalesce and frequently collide. These interpretations are borne by diverse stakeholder groups, each with their own priorities and investments in both Open Science and EOSC, which results in persistent tensions, not only about what constitutes openness but also about how to align infrastructural and policy goals. These tensions surface in moments of practical implementation. The open science discourse has taken to push for making research practices and outputs more equitable.^[117] Others^[118] have been even more vocal in stating that technological fixes will not bring about the desired openness unless accompanied by measures to tackle the more fundamental inequalities in academia. Consequently, while engagement within the EOSC ecosystem has placed Open Science in all kinds of agendas, researchers and institutions have been hesitant, in part due to lack of implementation of the proposed technical solutions and in part due to the EOSC narrative moving away from the current Open Science discourse.

In this, EOSC operates in a contested environment, existing within a broader matrix of European policy frameworks, such as the EOSC Co-programmed Partnership’s Strategic Research and Innovation Agenda (SRIA), Horizon Europe, and the Digital Agenda of the European Commission. In a sense, due to the “implementation” gap between the vision and the launch of the EOSC EU Node, EOSC remains a “floating signifier”^[119] susceptible to multiple contradictory interpretations. Its meaning remains open, shifting between visions of a “web of FAIR data and services” for researchers, a “European Knowledge Commons,” and, more recently, a platform for AI-readiness. While EOSC is a large-scale technological project, it is accessible, merely, by way of metaphor.^[120] This discursive flexibility accounts for fragmented understandings and uneven levels of buy-in across the research landscape. Even while EOSC has been remarkably successful as a socio-technical process for unifying existing research infrastructures, tangible benefits for researchers remain difficult to articulate.

EOSC discourse is largely disconnected from Science and Technology Studies (STS) perspectives on Open Science, as it tends to align more closely with administrative workflows, research management practices, and policy compliance processes, rather than epistemological debates about openness. While institutions use EOSC-aligned tools and standards, these are often embedded in Research Data Management (RDM) support structures which rarely mention EOSC. The emphasis is on compliance, preservation, and efficiency, rather than, say, transparency and reproducibility. This creates a disconnect: research support staff often operate outside Open Science debates, focusing instead on technical implementation, and as such are ill-positioned to serve as multipliers for EOSC engagement. Accordingly, EOSC is conspicuously absent from day-to-day conversations, having scant appeal with researchers/institutions, respectively, at times, with the broader Open Science discourse. On the one hand, there is high-level policy advocacy for Open Science as part of a reformed, sustainable, and transparent academic system – framed in terms of concerns about reproducibility, publishing regimes, and institutional transformation. On the other hand, research management tends to reduce “openness” to a set of compliance-driven technical standards, with (as yet) little bearing on actual research practices. In this, EOSC displays many hallmarks of (research) infrastructures:^[121] EOSC will be embedded, transparent (ready-to-hand), linked to (open research) practices, invisible, and built in modular increments. While end-users (researchers) need not be aware of the EOSC ecosystem to use the solutions on offer, the latter need to align with open (research) practices.

This means that while the EOSC has (albeit indirectly) promoted open research practices over the past years and continues to harbour significant potential for further engagement,^[122] researchers participate in these initiatives and engage with EOSC selectively. This is understandable considering that researchers are motivated by opportunities for data sharing, discoverability, and collaboration, and tend to be open to adopting enabling technologies and infrastructures. At present, EOSC employs various metaphors to reflect these competing perspectives, aiming to appeal to both researchers and technology providers who tend to acknowledge the necessity of discussing bureaucratic and financial structures in long-term, complex frameworks. Yet, the way EOSC communicates its value has profound implications for its adoption. Simply “providing data” is too vague and fails to address a scientific challenge; at best, it touches upon an organizational issue. To bridge these gaps, EOSC requires personnel within Research Infrastructures (RIs) who can serve as structural mediators and systematically address communication mismatches and the blending of conceptual levels – not necessarily in technical terms but in ways that clarify the roles and expectations across communities. Currently, RI staff often reinforce these structural ambiguities, existing in a space that is neither purely scientific nor purely administrative.^[123]