Strategies for Embedding Research Data Management Through Effective Communication

Abstract

Effective research data management (RDM) is essential for ensuring research integrity, reproducibility, and compliance with FAIR principles. Despite the development of comprehensive RDM frameworks, many institutions still struggle to ensure widespread engagement and compliance among researchers and staff. Adoption of RDM practices remains slow due to limited awareness, unclear benefits, and perceived administrative burdens. Using Mendelow’s Matrix, this study draws on survey data to map key stakeholders, such as researchers, RDM professionals, institutional leadership, funding bodies, and infrastructure providers, based on their power and interest to ensure developing tailored communication strategies. This paper presents a communication strategy to enhance RDM adoption by improving visibility, fostering engagement, and encouraging the integration of RDM into research workflows and curricula. It outlines key approaches, including awareness campaigns, targeted publishing, strategic partnerships, and knowledge-driven promotion to embed RDM into research workflows.

1. Introduction

Research data management (RDM) is increasingly recognized as a key component of good scientific practice within the research workflow due to its role in enhancing research integrity, accessibility, reproducibility, compliance, and FAIRness [1,2,3]. FAIR refers to research data being findable, accessible, interoperable, and reusable [4]. Funding agencies and academic journals are increasingly implementing policies that mandate data management plans and require data sharing [5,6]. Although RDM is increasingly recognized and encouraged as a cornerstone of sustainable research, its adoption faces several hurdles [7,8,9], which stem from the current state of implementation and stakeholder challenges. A similar pattern can be observed in the adoption of open educational resources (OER). Despite its potential advantages, the adoption of OER in Germany has been limited due to legal uncertainties, a lack of supportive policies, funding challenges, insufficient awareness and skills, and concerns about the quality of OER content [10].

To bridge the gap between RDM and stakeholders, particularly researchers, well-planned communication strategies are essential. The purpose of a communication strategy is to address the diverse needs of stakeholders to create awareness, build trust, address barriers, foster acceptance, encourage engagement and promote action to achieve successful implementation and adoption of RDM. Integrating RDM into institutional research practice represents not just a technical upgrade or advanced infrastructure, but a cultural and behavioral shift, one that may require structured change management. Change management frameworks offer valuable insights for navigating resistance, building stakeholder engagement, and sustaining long-term adoption. Foundational models such as Kotter’s eight-step process for Leading Change [11] and Lewin’s three-stage model [12] emphasize the importance of creating urgency, enabling participation, communicating the vision, and reinforcing new behaviors. There is a need to engage diverse stakeholders, realign institutional priorities, and build intrinsic motivation across disciplinary boundaries. Therefore, a communication strategy is just as essential for the success of RDM as other action areas, perhaps even more critical, yet it has not been adequately supported by specific strategic frameworks or approaches. Daily tasks of RDM professionals, such as data managers, data stewards, research data officers, and data librarians, are overwhelmingly broad, encompassing consulting, competence development and training, policy and standards development, infrastructure and technical services, subject-specific support, and networking and collaboration. Therefore, this paper aims to serve as a guide for RDM professionals and institutions seeking to enhance RDM adoption through strategic, stakeholder-focused communication efforts. It highlights the critical role of communication in RDM success, outlines current action areas and challenges in RDM implementation, and presents stakeholder mapping based on survey data collected from RDM professionals in Germany and other parts of Europe. The paper offers practical recommendations and actionable measures for developing effective communication strategies, and it encourages sustainable practices to foster a culture of shared responsibility for data management and achieve FAIR compliance.

1.1. Action Areas in RDM

This section briefly outlines the current action areas and efforts in RDM, including: Consulting and support: Integrating advisory services into institutional workflows is essential for developing long-term research data management competencies among researchers. Therefore, many institutions have established these services to support researchers in grant applications as funding bodies increasingly require data management plans. Scientific publishers also demand that research data be published alongside articles, increasing the need for guidance [13]. These advisory services help researchers efficiently and securely manage their data while ensuring compliance with legal and ethical standards such as data protection and good scientific practice. Support is offered through various formats, including self-service resources, written inquiries, consultations, and workshops.

Education and training: Since advisory services cannot be infinitely scaled, additional measures are needed to systematically provide researchers and staff with RDM knowledge and skills. Education and training form a key action area in RDM. While consultations offer practical guidance for specific inquiries, training raises awareness by reaching larger groups, especially early-career researchers, helping to make RDM an integral part of research. Training covers RDM fundamentals, FAIR principles, legal aspects, and institutional tools for cloud storage, data management plans, and archiving. Various formats, including workshops, webinars, and Train-the-Trainer programs, ensure broad accessibility. Efforts are currently being invested in integrating RDM into university curricula through mandatory courses and OER to support long-term competency development.

Developing policies, standards, and guidelines: Policies and standards form the foundation of a sustainable RDM strategy, facilitating adoption through best practices. They ensure data quality, support compliance with regulations such as GDPR (General Data Protection Regulation) and copyright laws, and align institutional and research needs. Universities develop tailored policies to embed RDM institutionally, while checklists aid service implementation. Key standards include technical data formats, data quality guidelines, security protocols, and metadata frameworks. FAIR principles, ontologies, and controlled vocabularies improve data standardization, interoperability, and reusability, ensuring sustainable research data.

Integrating infrastructure and technical services: Infrastructure includes physical and digital systems such as servers, networks, and storage, while services encompass repositories, cloud storage, data analysis tools, and authentication systems. These services align with the data lifecycle, from collection to archiving, and can be institution-based or decentralized. Modern IT infrastructures aligned with research needs are crucial to ensure seamless data management, analysis, publication, and archiving.

Discipline-specific support: Since different fields have unique requirements, a discipline-specific approach is essential in RDM. The demand for specialized RDM consultations and technical services has grown, with institutional IT centers facilitating collaboration and infrastructure development. Professional societies such as the National Research Data Infrastructure (NFDI, German: Nationale Forschungsdateninfrastruktur) consortia play a key role in establishing and promoting field-specific standards and best practices. Interdisciplinary efforts for standardized solutions also consider flexible tools and processes to ensure that RDM solutions meet the specific needs of each discipline.

Networking and collaboration: Interdisciplinary, national, and international collaboration, supported by institutional efforts and initiatives such as NFDI and EOSC (European Open Science Cloud), fosters knowledge transfer, resource sharing, and alignment with global standards. Collaboration among RDM professionals, academic, policy, and technology stakeholders is key to developing sustainable RDM solutions and maximizing resource utilization. Regular evaluation, strategic discussions, and institutional infrastructure development enhance long-term effectiveness.

Communication and outreach: Generally speaking, RDM efforts have so far lacked a comprehensive communication strategy to effectively disseminate information on its benefits and best practices. This may stem from the fact that many RDM professionals often view their role primarily as service providers rather than advocates or change agents (change management can be considered a critical action area for successfully embedding RDM into research practice.). Consequently, promoting RDM internally or aligning it with broader institutional narratives, such as research excellence, openness, or innovation, may fall outside their perceived responsibilities. Existing initiatives for communication and engagement are sporadic rather than systematic, lacking coordinated campaigns, clear messaging, and a strong social media presence. As a result, stakeholders remain inadequately informed about RDM fundamentals, best practices, tools, and benefits. Expanding outreach strategies is essential to raising awareness, driving adoption, and ensuring researchers fully leverage RDM resources. This paper highlights the critical role of an effective communication strategy in integrating RDM into research.

1.2. Current State and Challenges in RDM Implementation: Meta-Level Observations

Researchers, the primary drivers of RDM adoption, require simple tools, minimal workload, and assurance of data security. However, many are unaware of the need for data management, leading them to overlook or not participate in the training opportunities provided by their institutions. A perception issue persists, as researchers and students often have low awareness of RDM benefits and the available services and tools. For many, RDM is seen as an additional administrative burden rather than a necessity for research effectiveness, transparency, and sustainability. This is particularly true when researchers must standardize data types, formats, and metadata, which adds to their workload. Additionally, many lack the necessary skills and best practices for effective data management. A major challenge is the absence of incentives for maintaining high-quality data. Proper data management often goes unrewarded, leading to a lack of intrinsic motivation among researchers. As a result, they may prioritize immediate research outputs over long-term data stewardship and sustainability. Another factor that complicates data management and sharing is the issue of data rights and data protection, particularly in the life sciences, where anonymization can reduce the usefulness of data, and where in-house support for such complex matters is rarely available. Another barrier is the perceived complexity of RDM materials and tools, which may discourage researchers from engaging with them. The heterogeneity of data management cultures, processes, and infrastructure further complicates adoption. Finally, some researchers fear losing a competitive advantage or damaging their reputation by sharing low-quality or incomplete data, further limiting their willingness to embrace RDM practices.

On the other hand, RDM professionals require clear frameworks and adequate resources to ensure the smooth implementation of RDM practices and tools. A key challenge lies in the expanding demands placed on RDM professionals. In addition to technical responsibilities, they are increasingly expected to act as strategic partners and cultural change agents—supporting FAIR data, open science, and sustainable research practices. This requires a blend of technical, strategic, and interpersonal skills [14], yet their capacity to fulfill these roles is often constrained by limited time, resources, and institutional prioritization. Additionally, successful RDM adoption relies on support from infrastructure developments and governance units that can adapt policies to emerging technologies in a timely manner. A lack of dedicated resources from institutional leadership and research projects for outreach and communication efforts limits the ability of RDM professionals to effectively promote best practices. Furthermore, the absence of timely updates on policy changes from funding bodies often makes it difficult to keep RDM strategies aligned with evolving compliance requirements.

General barriers to RDM adoption include resource constraints—both in terms of personnel and technical budgets, which limit the capacity for effective implementation, especially when existing infrastructure fails to meet users’ needs. Additionally, the lack of strong stakeholder engagement and consistent communication strategies hinders widespread adoption and awareness. A major challenge is the resistance to change and the cultural shift required to integrate RDM into established research practices, making it difficult to achieve lasting sustainability. Integrating a well-designed communication strategy within the RDM framework ensures that stakeholders understand its value and adopt best practices.

2. Stakeholder Analysis and Mapping

2.1. Method

The first step in developing a communication strategy is to identify the need it aims to address, which in this case is enhancing awareness and encouraging the implementation of the best RDM practices in research. The next step is to identify and analyze target groups and key stakeholders. Several frameworks can help identify, assess, and strategically engage with individuals or organizations involved in or affected by RDM. This process enables prioritization of efforts and ensures that communication is tailored to specific needs. Mendelow’s Matrix, also known as the Power-Interest Grid, is a valuable tool for categorizing stakeholders based on their level of power and interest [15]. “Power” refers to a stakeholder’s authority, control over resources, or ability to impose decisions and shape project’s outcomes. “Interest” reflects their level of concern about the project’s success. This grid helps identifying key players, understanding their roles, needs, and challenges and designing messages and engagement strategies tailored to each group [16]. It also helps you prioritize allocating resources for those who can maximize the desired success or those who need specific support. The stakeholder grid consists of four areas:

• High power, high interest: Engage closely, as they play a crucial role in a top-down strategy (e.g., funding bodies, institutional leadership). On the other hand, research group leaders play an active role in encouraging the adoption and integration of RDM into the research cycle.
• High power, low interest: Keep them satisfied to prevent negative impact on your progress (e.g., infrastructure providers).
• Low power, high interest: Keep them informed and inspired, as they are key players in adoption. Keeping them motivated is essential, as they are key players in a bottom-up strategy. (e.g., early-career researchers).
• Low power, low interest: Monitor their engagement. These stakeholders are not actively engaged and have limited influence, but they should still be observed in case their relevance changes (e.g., students).

Different Stakeholder groups contribute to the resources, policies, infrastructure, expertise, and guidance necessary to implement and sustain RDM, including those who generate, manage, and share research data. These groups typically include research group leaders, spokespersons of clusters of excellence, collaborative research centers, and similar research consortia, early-eareer researchers (PhDs, post-docs), students, RDM professionals (data managers, data stewards, data librarians, data champions, data ambassadors), publishers (and reviewers), institutional leadership and top management, research data and open access initiatives (RDA (Research Data Alliance), NFDI, EOSC, Elixir, etc.), institutional infrastructure providers, IT managers, and IT support services, external infrastructure and service providers (research data repositories (e.g., Zenodo, Figshare, Dryad), DOI providers, and metadata services, etc.), policymakers and regulators (governance, data protection, ethics regulations, legal teams, good scientific practice, etc.), funding bodies, institutional communications and public relations teams, and the general public.

To estimate the power and interest of each stakeholder group, a survey was conducted among RDM professionals, including data stewards, data managers, and librarians. Respondents were asked to rate the power and interest of various stakeholder groups on a scale from 0 (low) to 10 (high). A total of 95 responses were collected, with 45 participants providing complete ratings for all 14 stakeholder groups (the dataset is available for reference [17]). The survey participants were primarily recruited through national RDM networks, mailing lists, and professional community meetings, with the majority being RDM professionals affiliated with German academic institutions. However, a small number of respondents from other European institutions also contributed, offering additional perspectives from the broader European research landscape. The sample draws from a broad and diverse cross-section of practitioners across institutional roles and contexts, providing valuable insights into RDM engagement. For compliance and data protection reasons, and to avoid any administrative delays, the survey focused solely on rating the power and interest of stakeholders; no personally identifying or demographic data—such as age, institutional affiliation, discipline, or organizational unit—were collected from participants. The mean values were calculated and missing responses were excluded from the calculations. The average scores were used to position stakeholders within a power-interest grid shown in Figure 1 and summarized in

Table 1. Stakeholder power and interest in RDM based on survey data and qualitative insights, see Figure 1.

Stakeholder Category	Power	Interest
Primary Users
Research group leaders	High	Moderate
Spokespersons of large research consortia	High	Moderate
Early-career researchers (PhDs, post-docs)	Low	High
Students	Low	Low
RDM Professionals
Data managers	Moderate	High
Data stewards	Moderate	High
Library teams	Moderate	High
Infrastructure Providers
Institutional IT and infrastructure services	Moderate to high	low to Moderate
External infrastructure and service providers	Moderate	High
Strategic Leaders
Institutional leadership and top management	High	Moderate
Communications/PR teams	Low	Low
Regulators
Policymakers and regulators	High	Moderate
Ethics and Legal departments	High	Moderate
Publishers (and Reviewers)	High	Moderate
External influencers
Funding bodies	High	moderate to High
Initiatives (Open Science, RD)	moderate	High
General public	Low	Low

. Figure 2 depicts the Standard deviations of power and interest scores per stakeholder and the number of respondents.

2.2. Results

Researchers are the primary users of RDM, responsible for generating, utilizing, and sharing data. While early-career researchers (PhDs and post-docs) play a key role in driving RDM adoption (average interest 6.17), their ability to influence strategic decisions is generally limited (average power 3.82).

In contrast, research group leaders hold significantly more power, average 7.95. Their interest in RDM is moderate (average 5.1), which tends to increase in response to external incentives such as funding requirements, publication opportunities, or collaboration prospects. Similarly, spokespersons of large research initiatives such as clusters of excellence or research data centers may have slightly less power (average 6.9) but are expected to show greater interest (average 5.6) in RDM implementation. Overall, early-career researchers consistently demonstrate higher levels of interest in RDM than their senior counterparts.

Students are potential users of RDM, engaging with data management during academic studies and research training. They have low power (average 1.8), and their interest is generally low (average 3.6) but may increase as they transition into research roles.

RDM professionals such as research data managers, data stewards, data librarians, besides the library knowledge management team provide consultation and education to ensure compliance with RDM guidelines, facilitate operational strategies, and ensure data accessibility, sustainability, and adherence to evolving standards. Their power ranges from low to moderate (average 5.2), but they have a high level of interest (average 9.4).

Institutional infrastructure providers, IT managers, and support services develop, maintain, and support the technical infrastructure required for RDM. They prioritize reliability, security, scalability, and user-friendliness of systems. Their power is moderate to high (average 5.9) as they control resource allocation, but their interest in RDM is generally low to moderate (4.6). In contrast, external infrastructure and service providers, such as commercial cloud platforms, domain-specific data repositories, or data management software vendors, often show higher interest in RDM (average 8.3) as it aligns directly with their core business and innovation goals. While their power within institutions is indirect, they exert moderate power (average 5.1) through technological standards, service availability, and contractual dependencies.

Institutional leadership and top management (such as presidents, provosts, vice-chancellors, deans, and department heads) play a strategic role by defining policies, setting priorities, and allocating resources for RDM. They prioritize strengthening institutional reputation, ensuring regulatory compliance, and sustaining infrastructure. However, they have limited direct engagement with implementation and researcher needs. They hold high power (average 9.1) and their interest in RDM may vary depending on institutional priorities (average 5.04).

Policymakers, legal teams, and regulators establish governance frameworks, set institutional policies, define compliance guidelines, and ensure adherence to legal requirements such as data protection, intellectual property, contracts, and ethical standards. They have high power (average 8.4) and low to moderate interest (average 6.6), which tends to grow when they are actively involved in RDM discussions and planning.

Academic publishers are increasingly involved in shaping RDM practices through data sharing mandates, submission guidelines, and by offering infrastructure such as data repositories. Their policies influence researcher behavior, institutional practices, and the broader scholarly communication ecosystem. They have Moderate to high power (average 8.1) and moderate interest (average 5.1). Their interest grows with commercial opportunities in data services and alignment with open science movements. Reviewers can also influence author behavior by encouraging or requiring the submission of FAIR datasets as part of the peer review process.

Funding bodies play a key role in shaping RDM practices by setting requirements for data management plans, data sharing, and open access. They promote good scientific practices such as FAIR principles to ensure data transparency and sharing. They hold high power (average 9.1) and moderate to high interest (average 6.6).

Research data, open science, and open access initiatives advocate for open access, FAIR principles, tool and framework development, and collaboration to enhance data transparency and reuse. Their priorities focus on promoting open access, driving cultural change, and facilitating collaboration. Their power is low to moderate (average 5.6) as they depend on funding bodies, but their interest is high in advocacy (average 8.9). It’s important to note that while they exert influence, their interest in directly implementing RDM at the institutional level is low.

Institutional communications and public relations teams can contribute to RDM by amplifying success stories, showcasing data-driven research, and supporting transparency and open science. They prioritize aligning messaging with funder, governmental, or institutional policy expectations, and they have competing communication priorities and limited understanding of RDM and its relevance. They have low power (average 3.4) and low interest (average 3) in RDM.

The general public benefits from publicly funded research outcomes and advocates for transparency, ethical data use, and societal impact. They prioritize access to understandable research, ethical data handling, and trust in responsible data management institutions. Their power is low (average 2.7) and their interest is also low (average 2.1).

When analyzing the standard deviations of Power and Interest scores across stakeholder groups in RDM, we find that the overall variability is moderate. The mean standard deviation is approximately 1.91 for Power and 2.05 for Interest. This indicates that while participants do not exhibit strong alignment in their assessments, there is also no extreme disagreement—views differ, but not dramatically.

Among the most consistently rated stakeholders in terms of power are the Funding Bodies. With a remarkably low standard deviation of approximately 0.88, there is strong agreement that this group holds significant influence. This likely reflects their clear and decisive role in shaping the RDM landscape through funding allocations, mandates, and policy influence. Similarly, students and institutional leadership show low standard deviation scores, suggesting a stable and shared perception of their influence, whether seen as low (in the case of students) or reliably high (for leadership).

In terms of interest, stakeholders such as RDM professionals, external infrastructure providers, and the general public exhibited the least variability in how their engagement was perceived. This level of agreement suggests that these groups are broadly understood and consistently recognized in their roles within the RDM landscape. The first two are seen as reliably interested in RDM, though likely for different reasons: RDM professionals are central to operational implementation, while infrastructure providers are valued for enabling transparency, ensuring accessibility, or delivering essential services.

On the other end of the spectrum are stakeholders with high standard deviations, which indicates significant disagreement among respondents. For power, this includes the spokespersons of clusters of excellence, the general public, and early-career researchers. These results suggest that some participants view these stakeholders as highly influential, while others see them as marginal or even irrelevant in the power dynamics of RDM. This kind of split likely reflects participants’ institutional context, familiarity with specific research programs, or assumptions about who drives change. Similarly, students, publishers, and cluster spokespersons show the highest standard deviations in interest scores, indicating mixed views on whether these groups are actively engaged in RDM. This variability may reflect real differences in engagement—students, for instance, may be deeply involved in some disciplines but largely absent in others. These discrepancies are not merely problems; they also present opportunities to investigate why some participants perceive these stakeholders as engaged while others do not.

2.3. Discussion on Stakeholder Mapping

Distinguishing between power and interest of different stakeholder groups when planning communication and engagement strategies for RDM is important to foster meaningful and sustainable progress across institutions. The stakeholder mapping illustrated in the stakeholder grid in Figure 1 reveals that the most critical group for advancing RDM practices includes those with both high power and high interest, positioned in the upper-right quadrant of the grid. Key stakeholders in this group at the institutional level include institutional leadership, research group leaders, spokespersons of large research consortia, policymakers, and regulators. Outside the institution, funding bodies and publishers also hold significant influence. With average power scores ranging from 6.9 to 9.1 and moderate to high interest, their active involvement is crucial. They have the ability to shape institutional policy and promote the adoption of RDM best practices. RDM professionals should prioritize sustained engagement with these groups to align research efforts with institutional strategies and funder expectations The figure also reveals that stakeholders directly involved in handling research data, such as data stewards, managers, and librarians, demonstrate significantly higher interest in RDM. This likely reflects their deep understanding of its value in practice, often surpassing even that of funding bodies and institutional leadership, who may not share the same level of day-to-day awareness or commitment and may have other institutional or strategic priorities. Data professionals play a frontline role in increasing awareness and fostering engagement around RDM. It is important to keep in mind that these insights reflect the perspectives of data professionals, who provided the assessments based on their own experience and institutional context.

Policymakers, legal departments, and ethics committees hold substantial power but often demonstrate lower interest in RDM implementation unless they are kept informed and actively engaged. Maintaining clear communication and involving them strategically helps avoid delays and roadblocks during the planning and implementation of RDM practices. When their interest remains low, these stakeholders typically fall into the “Keep Satisfied” quadrant of the power-interest grid, such as institutional infrastructure providers and IT managers. While their average power is moderate to high, their interest is often lower unless they are actively involved in RDM-specific planning. Their contribution is vital for delivering secure, scalable, and user-friendly data systems. RDM professionals must engage IT departments early to align infrastructure with evolving RDM needs. External service providers such as repository platforms and metadata services show relatively high interest and moderate power. Although their institutional power is indirect, they can influence standards and technical decisions, and should be engaged as partners, especially in tool selection and interoperability efforts.

To sustain momentum, RDM and open science initiatives, which show high interest and moderate power in promoting RDM adoption, should align with global trends, leverage collaboration, and foster shared learning to enhance their effectiveness. Partnerships between these initiatives and data professionals can significantly enhance awareness and promote the adoption of RDM practices. Early-career researchers demonstrate relatively high interest (6.2) but low power (3.8), placing them in the “Keep Informed” quadrant. As direct users of RDM tools and policies, they benefit from clear guidance, training, and incentives. Their active adoption of RDM practices can have a ripple effect across research groups and disciplines. The influence of research group leaders and consortium spokespersons can further strengthen their interest in RDM and support its implementation, enabling them to encourage wider adoption among their peers. Students reside in the lower-left quadrant, with both low power and low interest. The role of students in RDM is currently limited, but awareness and education efforts can gradually foster a culture of responsible data management among emerging researchers. The general public is also placed in the lower-left quadrant. In disciplines such as the life sciences, it is important to recognize that volunteer patients may have an influence on how data is used and shared. In addition, institutional communications teams are located in this quadrant. While they may prioritize other institutional topics, they can still play a valuable role in raising awareness of RDM through targeted campaigns and strategic messaging.

The findings offer a meaningful foundation for exploratory stakeholder mapping, yet they should be interpreted with awareness of contextual boundaries and potential sampling limitations. It is also important to note that the level of stakeholder interest in RDM can vary significantly depending on institutional priorities, national research cultures, and disciplinary norms. While the present study focuses on general patterns, future research could explore these disciplinary nuances more explicitly. In addition, the challenges and strategies explored in this paper are relevant to broader international contexts. Regional differences are acknowledged, and future comparative studies could further explore these dimensions.

3. Communication Strategies for RDM

3.1. Purpose and Importance

Communication plays a pivotal role in integrating RDM into daily research practice. It is the foundation that builds awareness, which in turn enables adoption and, ultimately, integration. To embed RDM meaningfully within research environments, a clear progression must be followed. The ultimate goal is to establish RDM as a core, sustainable element of the research process. This means embedding it across all stages of research, from initial planning and data collection to analysis, publication, and long-term preservation. To achieve this, the requirement is to increase the adoption of RDM practices among researchers, institutions, and stakeholders. This calls for strategic interventions, such as developing supportive policies, offering incentives, and fostering a culture that values responsible data practices. However, adoption cannot occur without a critical prerequisite: raising awareness. Researchers and staff need to understand what RDM is, why it matters, and how it benefits both individual projects and institutional credibility. Awareness must be built not only around abstract principles, but also around the practical value and applications of RDM in everyday work. To enable this awareness, institutions need a structured communication strategy. This includes well-crafted messages tailored to different stakeholder groups, the use of appropriate communication channels, and access to high-quality, user-friendly resources such as training materials, templates, and workshops. Finally, successful implementation depends on translating this strategy into action. This involves defining a clear concept and purpose, creating a guiding framework of steps and priorities, and executing a detailed plan with assigned responsibilities, realistic timelines, and ongoing evaluation.

Building on the stakeholder mapping presented in the previous section, this part of the paper focuses on translating those insights into actionable communication strategies. The adoption of RDM requires a gradual process of transformation, one that avoids overwhelming demands by advancing in calculated steps. Achieving lasting change depends on the active engagement of key stakeholders through tailored communication efforts aligned with their specific roles, interests, and influence. This section focuses in particular on researchers, identified as the primary stakeholders in driving the adoption of RDM best practices [7]. The communication strategy should focus on people and, at times, strike a balance between bottom-up and top-down approaches. A bottom-up approach emphasizes “pull factors” that inspire and build intrinsic motivation. In contrast, a top-down approach leverages “push factors”, using funder mandates and institutional policies to prompt action among target groups. Rather than relying solely on restrictions or sanctions, top-down strategies can also be designed around positive incentives, such as recognition, resources, or alignment with strategic goals. It suggests several actionable components: raising RDM awareness among stakeholders, promoting services and encouraging support, inviting collaboration, providing resources for education and training to build competency, facilitating engagement through two-way communication, and collecting feedback for continuous evaluation and improvement.

Marketing and sales professionals—and even motivational speakers—often say, “You can’t sell to an empty room”, underscoring the importance of visibility and engagement before attempting to promote a message. Since the launch of Research Data Alliance (RDA) initiative with the goal of building the social and technical infrastructure to enable open sharing and re-use of data [18], efforts to promote RDM in Germany have been ongoing, yet many of the same challenges persist. This may stem, in part, from an academic reluctance to use promotional tools such as paid outreach or public relations, which are often perceived as too commercial for scholarly environments. However, visibility is not optional—it is critical for ensuring that RDM practices are understood, accepted, and ultimately embedded in everyday research processes. If we aim to drive a meaningful cultural shift toward making RDM a standard element of the research framework, we must adopt more deliberate, effective communication strategies. Science communication plays a central role in this effort by making RDM accessible, promoting a culture of data stewardship, and ensuring that best practices reach the right audiences to support research integrity and long-term impact. Despite its importance, reaching the stakeholders who are essential to RDM implementation remains challenging. That is why stakeholder identification and mapping—such as the power-interest grid presented in the previous section—is a necessary foundation for targeted and effective communication.

The following tools can be used for knowledge dissemination, engagement, and transfer through short, dedicated campaigns:

Regular content: Share insights on best practices, policies, and the benefits of RDM through consistent, accessible communication, both online and offline. A strong content strategy can include social media posts, articles, blog entries, institutional newsletters, printed posters, and search-indexed materials. These formats help make RDM services and initiatives more visible and discoverable.

Promote awareness: Instead of relying solely on traditional advertising, invest in open-access resources, training programs, newsletters, and conference sponsorships to actively promote RDM awareness and education. Additionally, exhibiting at conferences, setting up booths, and hosting interactive sessions can provide hands-on engagement, fostering direct communication with researchers and students. Scientific conferences offer an ideal setting to introduce RDM to researchers and boost visibility. If data professionals are unable to attend, they can collaborate with researchers from their institute to present a single, compelling slide designed to spark curiosity and promote engagement and adoption.

Public Relations (PR): PR efforts play a key role in disseminating knowledge about RDM. Being featured in academic journals, institutional newsletters, podcasts, and media outlets helps normalize RDM and position it as a vital element of sustainable, high-quality research.

Partnerships: Collaborate with institutions, libraries, funding bodies, research organizations, initiatives and policymakers to raise awareness, establish RDM as a shared responsibility, and ensure its adoption and sustainable implementation.

RDM is not only about implementing tools and policies; it also requires fostering understanding, acceptance, and motivation among early-career and established researchers. A sustainable communication plan should focus on three core objectives: spreading awareness of RDM’s benefits, best practices, services, and tools; providing education on how to manage, preserve, and share data effectively; and inspiring action by focusing on the human side of data work and emphasizing the shared responsibility of advancing RDM practices.

An effective communication strategy begins with clearly defining institutional goals, such as raising awareness, fostering engagement, or advancing the adoption of RDM policies. The next step is to identify and analyze target stakeholder groups, understanding their specific needs, challenges, and motivations. With this foundation, institutions can create a strategic communication plan that includes customized messaging, key activities, and realistic timelines. Choosing the right communication channels, whether workshops, online platforms, or institutional media, is essential to reach diverse audiences. Successful implementation requires a clear assignment of responsibilities. Dedicated teams or ambassadors can lead initiatives and promote adoption within their communities. The plan should start small, then expand and diversify based on feedback and available resources.

A self-developed implementation plan is structured around three adaptable phases: short-term, medium-term, and long-term, each tailored to the personnel and resources available within a given institutional context,

Table 2. Implementation Phases for RDM communication Strategy.

Short-Term	Medium-Term	Long-Term
Repeated exposure to raise awareness Widespread of RDM online and offline, social media campaigns, success stories, training workshops, direct engagement with stakeholders, leverage newsletters, podcasts, conference sponsorships, collaborations, collect feedback and adapt.	Skill building and strategic collaboration Hands-on RDM training programs, assess and refine existing training materials, modernizing digital platforms, provide templates, tools, and best-practice guides, leverage dynamic formats such as case studies, short videos, and interactive content.	Sustainable integration and cultural shift Commit to embed RDM in research workflows and institutional curricula, strengthen collaborations, encourage continuous infrastructure improvements to align with evolving needs, maintain engagement by building systems to adapt, repurpose, and repost content.

. Continuous evaluation and adaptation, guided by stakeholder feedback and evolving needs, is crucial to ensure success.

3.2. Implementation Plan for RDM

• Short-term communication practices (0–1 Year): This phase focuses on implementing a persistent, multi-channel communication strategy that reinforces key messages through repeated exposure, ensuring widespread recognition of RDM and the adoption of its best practices. The choice of communication medium should be based on a careful analysis of institutional data on stakeholder engagement, supported by insights from peer recommendations. Social media platforms such as LinkedIn and YouTube effectively reach diverse audiences, while Instagram and TikTok are particularly useful for younger demographics. In addition, open-source platforms such as Bluesky and Mastodon are now receiving increased attention. Institutional official channels can be particularly valuable for reaching a broad audience.
  These channels should be leveraged to share key messages, success stories, and the benefits of RDM in an engaging and accessible manner. Showcasing real-life examples of researchers successfully implementing RDM can highlight its practical value and encourage adoption. Targeted campaigns should emphasize both the immediate and long-term benefits of RDM to encourage wider acceptance. Newsletters, podcasts, conference sponsorships, collaborations, and active participation in academic events can further enhance awareness and education. Exhibiting at conferences, setting up booths, and hosting interactive sessions provide direct engagement opportunities with researchers and students, strengthening outreach efforts. To maximize exposure, this phase should leverage all available resources and media within condensed timeframes.
  At the same time, existing resources, including guides, tools, templates, and self-education materials, should be prepared and actively distributed to ensure researchers can easily access the information they need. A strong and recognizable visual identity will reinforce awareness and improve engagement over time. Regular training workshops and webinars introduce the fundamentals of RDM, while informal events, such as “Lunch and Learn” sessions, coffee lectures, or open office hours, create opportunities for discussion and direct interaction. Engaging key multipliers, such as department heads, senior researchers, data champions, and research assessment managers, is essential to embedding RDM best practices within institutions. These individuals can serve as RDM ambassadors, helping to spread knowledge and encourage adoption among their peers. To measure the effectiveness of awareness efforts, it is important to gather stakeholder feedback and monitor engagement levels. Setting clear, measurable goals will help track progress, while maintaining a well-organized repository of communication materials ensures consistency and sustainability in messaging.
• Medium-term communication practices (1–3 Years): In this phase, skill-building, focusing on developing systems, strategic collaborations, and communication of RDM tools and best practices should be key priorities while maintaining continuous dissemination. Evaluating existing RDM training materials and resources is essential to ensure they meet diverse research needs and expectations, including those of newer generations (e.g., Gen Z). Where necessary, materials should be adapted to enhance relevance, efficiency, and effectiveness. Developing a centralized, user-friendly digital platform or modernizing the RDM website can significantly improve structure, clarity, readability, and accessibility. Providing well-organized resources, templates, and guides will further support researchers in integrating RDM into their workflows. Fostering a peer-support community enables researchers to exchange best practices and experiences, creating a network for shared learning. Short, engaging videos such as Instagram reels or LinkedIn videos can showcase case studies and best practices in an accessible format, catering to shorter attention spans and making RDM more relatable. To enhance visibility and impact, monitoring traffic and engagement metrics allows for data-driven adjustments, ensuring outreach efforts effectively reach the right audience. Interviews and collecting feedback during training sessions with key stakeholder groups can provide deeper insights into their concerns and help tailor communication strategies accordingly. Strategic collaborations and partnerships play a vital role in extending the reach of RDM initiatives, ensuring efficient resource use while amplifying impact. Continuous engagement with infrastructure providers is also necessary to align RDM systems with evolving research demands. Sustaining a long-term communication strategy requires effective content management, ensuring materials remain relevant and messaging improves over time. Storytelling-driven cultural shift initiatives can further highlight the personal and professional benefits of RDM adoption, reinforcing its role as a fundamental part of research culture.
• Long-term communication practices (>3 Years): This phase focuses on driving a cultural shift by embedding sustainable RDM practices into research workflows, self-learning materials, and institutional curricula. This can be supported by communicating the need and benefits of addressing RDM during the onboarding process of departments and organizations. Achieving this integration requires strengthening collaborations, continuously improving infrastructure to meet evolving stakeholder needs, and implementing automated systems that support content repurposing, updating, and redistribution to maintain visibility and impact. Sustainability also relies on fostering intrinsic motivation and prioritizing strategic stakeholder communication to enhance social interoperability. Key groups include infrastructure teams, education departments, research administration, management offices, libraries, and funding bodies. Communication efforts should emphasize the need for ongoing infrastructure development and advocate for accessible, regularly updated, and scalable platforms that remove barriers and enhance efficiency. Leveraging foundational services offered by initiatives such as NFDI, EOSC, and others can further support infrastructure optimization.
  Incentives and recognition programs such as awards and certifications can further motivate researchers to engage in and champion best RDM practices, reinforcing institutional adoption. To expand the reach and long-term impact of RDM efforts, global collaboration and partnerships with national and international institutions are vital. These relationships enable knowledge sharing, message alignment, and standardization of best practices across research communities. Sustained stakeholder engagement also depends on a strategic approach to content management. Existing materials should be routinely adapted, repurposed, and redistributed to ensure continued relevance, message consistency, and lasting communication effectiveness.

4. Conclusions and Recommendations

This article has explored key communication strategies essential for fostering research data management (RDM) as an integral part of good scientific practice. RDM plays a crucial role in ensuring research sustainability, accessibility, FAIR compliance, and reproducibility. However, despite institutional efforts, its adoption remains hindered by awareness gaps, stakeholder challenges, and resource constraints. Effective communication is not merely a supporting factor in RDM adoption, it is a fundamental pillar that drives engagement, builds trust, and encourages long-term integration into research workflows. The responsibilities of RDM professionals, including data managers, stewards, and librarians, are extensive, covering consultation, training, policy development, technical infrastructure, discipline-specific support, and stakeholder collaboration. To enhance their impact, this paper provides a strategic, stakeholder-focused communication framework aimed at highlighting the role of communication in successful RDM adoption, identifying key stakeholders and their specific needs and challenges, encouraging intrinsic motivation while providing actionable measures for effective implementation. Additionally, the article presents a stakeholder power–interest grid based on survey data, mapping key groups such as institutional leadership, regulators, RDM professionals, infrastructure providers, IT managers, researchers, students, funding bodies, and global RDM initiatives to better understand their influence and level of engagement. It also discusses four core approaches for effective knowledge dissemination, engagement, and advocacy: publishing content to share best practices and insights, investing in strategic promotion to enhance RDM awareness, leveraging PR and media to normalize RDM adoption, and building partnerships with institutions and funding bodies to ensure long-term sustainability. Finally, the article outlines a structured communication strategy designed for both immediate and sustained impact. In the short term, efforts should focus on raising awareness through omnipresent communication, leveraging social media, success stories, and structured training initiatives. In the medium term, strategies should emphasize skill-building and collaborative approaches by refining training materials, creating digital platforms, and fostering peer-support networks. In the long term, the goal should be to sustain intrinsic motivation and institutional integration by embedding RDM into research workflows and institutional curricula, establishing recognition programs, and strengthening global collaborations. By implementing these strategic communication efforts, institutions can bridge the gap between RDM policies and real-world adoption, fostering a culture of responsible, transparent, and collaborative research data management.