The Dimensions of Research Visibility: A Multidimensional Framework for Scholarly Discoverability and Reach

The growth of digital scholarly communication has created an increasingly complex environment in which research outputs circulate through multiple interconnected systems. A single research article may simultaneously exist within a journal website, Google Scholar, Crossref, OpenAlex, Scopus, Web of Science, an institutional repository, an author's ORCID record, a university research profile, social media platforms, research networking systems, citation networks, and policy or professional knowledge environments.

The existence of a publication in one of these locations does not guarantee that it is equally visible across the others. This asymmetry creates an important research problem, which can be stated directly:

What exactly does it mean for research to be visible?

ResearchTrics Research Bulletin No. 001 proposed that research visibility is the degree to which a research output, researcher, research group or institution can be discovered, accessed, recognised, connected, engaged with and represented within relevant scholarly and knowledge ecosystems (Oladunmoye, 2026a). Bulletin No. 002 subsequently distinguished research visibility from research impact, arguing that visibility creates opportunities for engagement and influence but should not itself be interpreted as evidence of consequential impact (Oladunmoye, 2026b).

The present Bulletin develops these propositions further by asking a more precise question: what are the fundamental dimensions through which research becomes visible? In answering this question, the Bulletin also situates the ResearchTrics framework more firmly within the established literature on bibliometrics, altmetrics, open science and responsible research assessment, and adds worked illustrations, comparative tables and visualisations that were absent from the original conceptual note.

The claim that visibility is multidimensional is not new in isolation; it draws together several distinct literatures that have developed largely in parallel. Bibliometric scholarship has long cautioned against treating any single citation-based indicator as a complete measure of scholarly value. The Leiden Manifesto sets out ten principles for responsible research metrics, including the principle that quantitative evaluation should support, rather than replace, qualitative expert assessment, and that comparisons should account for variation across fields and publication types (Hicks, Wouters, Waltman, de Rijcke, & Rafols, 2015). The San Francisco Declaration on Research Assessment similarly calls on funders, institutions and publishers to stop using journal-based metrics, such as the journal impact factor, as a proxy for the quality of individual articles or researchers (San Francisco Declaration on Research Assessment, 2013).

A second relevant literature concerns altmetrics, which emerged from the recognition that traditional citation counts are slow to accumulate and capture only one channel through which research circulates. Priem, Taraborelli, Groth and Neylon (2010) argued that new, web-based filters, including social bookmarking, discussion and sharing, could reveal broader and faster signals of scholarly attention than citation alone. This literature underpins the engagement dimension developed later in this Bulletin.

A third relevant literature concerns open science and data stewardship. The FAIR Guiding Principles state that research objects should be Findable, Accessible, Interoperable and Reusable by both humans and machines (Wilkinson et al., 2016), a formulation that maps closely onto the discoverability, accessibility and openness dimensions proposed here. UNESCO's Recommendation on Open Science extends this reasoning to policy level, framing open scientific knowledge and open infrastructures as central components of a fair and inclusive knowledge ecosystem (UNESCO, 2021).

A fourth literature concerns researcher identity and attribution. Persistent identifiers such as ORCID were introduced specifically to resolve author name ambiguity and to link researchers reliably to their outputs across publishers, institutions and countries (Haak, Fenner, Paglione, Pentz, & Ratner, 2012). This literature underpins the scholarly recognition dimension.

Finally, the sociology of science has long observed that visibility and recognition are not distributed evenly. Merton's account of the Matthew effect describes how already prominent scientists tend to receive disproportionate credit relative to less established colleagues, even for comparable contributions (Merton, 1968). This literature is a reminder that visibility measures are not neutral: they can reflect and reinforce existing patterns of advantage, a concern that is returned to in the discussion of context and equity below.

Table 1 summarises how each strand of literature maps onto the eight dimensions developed in this Bulletin.

Table 1. Mapping of established literature onto the eight proposed dimensions of research visibility.

Research visibility is often approximated through individual indicators, such as citation counts, journal indexing, article views, downloads, social media mentions, search engine rankings, researcher followers, publication counts and database coverage.

The problem is that each indicator captures only part of the underlying phenomenon. Citation counts, for example, provide information about subsequent scholarly referencing but do not directly measure whether an article is accessible to potential users. An article may be indexed in a major database yet receive little engagement. A publication may attract thousands of downloads while generating few citations. A researcher may have substantial local influence without extensive representation in international bibliometric databases.

No single observable indicator can adequately represent the full construct of research visibility. This is the central premise supporting a multidimensional conceptualisation, and it is consistent with the broader responsible metrics literature summarised above (Hicks et al., 2015).

The ResearchTrics framework treats visibility as a property that emerges from interactions among several components of the scholarly communication system. At the most basic level, research must exist before it can become visible. Once produced, however, several conditions influence whether the research becomes visible in practice:

• Can it be found?
• Can it be accessed?
• Can it be correctly attributed?
• Does anyone engage with it?
• Is it connected to other research?
• Does it enter citation networks?
• Is it openly reusable?
• Does it reach audiences beyond the original scholarly context?

These eight questions generate the eight dimensions proposed in this Bulletin, and each is developed in turn below.

5.1 Dimension: Discoverability

Definition. Discoverability is the extent to which a research output or researcher can be located through relevant scholarly and information retrieval systems. It represents the entry point into the visibility process.

Potential indicators include:

• Indexing status
• Search engine retrieval
• Database inclusion
• Metadata completeness
• Title searchability
• Abstract availability
• Keyword relevance
• Persistent identifiers
• Structured metadata
• Searchable full text

Google Scholar's technical guidance illustrates the practical importance of crawlable scholarly content, individual URLs, searchable abstracts or full text, and appropriate bibliographic metadata for inclusion in its index (Google Scholar, n.d.). Discoverability should be distinguished from visibility as a whole: an article that cannot be found is unlikely to be engaged with, but being discoverable does not guarantee subsequent engagement.

Research question. To what extent does discoverability predict subsequent scholarly engagement?

5.2 Dimension: Accessibility

Definition. Accessibility concerns the degree to which discovered research can actually be obtained, read, interpreted and used by relevant audiences.

Potential indicators include:

• Open access status
• Repository availability
• Readable file formats
• Accessible abstracts
• Accessible supplementary materials
• Data availability
• Methodological transparency
• Language accessibility
• Machine readability
• Technological accessibility

Open science frameworks increasingly emphasise the accessibility and reuse of scientific knowledge and associated research resources. UNESCO's Recommendation on Open Science identifies open scientific knowledge and open infrastructures as central elements of an inclusive open science ecosystem (UNESCO, 2021), and the FAIR Guiding Principles explicitly require that data be Accessible as well as Findable (Wilkinson et al., 2016). Accessibility is therefore more than the existence of a URL: a publication may be discoverable but effectively invisible to a potential reader if access barriers prevent meaningful use.

Research question. Does improved accessibility increase subsequent research engagement and reuse?

5.3 Dimension: Scholarly Recognition

Definition. Scholarly recognition refers to the extent to which a research contribution can be accurately identified and attributed within scholarly information systems.

Potential indicators include:

• ORCID and other persistent researcher identifiers
• Author disambiguation
• Institutional affiliation records
• Publication attribution
• Researcher profiles
• Journal identity
• Institutional research records
• Relationships between researchers and their outputs

Recognition is particularly important in an environment characterised by fragmented researcher identities. The ORCID registry was introduced specifically to resolve the problem of author name ambiguity, linking researchers to their outputs across disciplines, organisations and countries (Haak, Fenner, Paglione, Pentz, & Ratner, 2012). A publication may be visible as an isolated document but remain poorly connected to its author if identity metadata are incomplete, creating a meaningful distinction between document visibility and researcher visibility.

Research question. To what extent does persistent scholarly identity improve the visibility and attribution of research outputs?

5.4 Dimension: Scholarly Engagement

Definition. Engagement represents observable interaction between research and its potential or actual audiences.

Potential indicators include:

• Article views
• Downloads
• Saves and bookmarks
• Online discussion
• Academic presentations
• Requests for materials
• Social dissemination
• References in teaching
• Research reuse
• Practitioner engagement

Engagement should not automatically be interpreted as a positive evaluation; a paper may attract attention because it is controversial rather than because it is well regarded. This distinction follows the conceptual separation established in Bulletin No. 002 (Oladunmoye, 2026b) and is consistent with cautions in the altmetrics literature that attention based indicators reflect interaction rather than quality (Priem, Taraborelli, Groth, & Neylon, 2010). Engagement is evidence of interaction, not necessarily evidence of research quality or impact.

Research question. Which forms of engagement are most strongly associated with subsequent scholarly use?

5.5 Dimension: Connectivity

Definition. Connectivity refers to the degree to which a research entity is linked to other entities within the knowledge ecosystem, including researchers, publications, institutions, journals, datasets, instruments, projects, methods, research groups and funding sources.

Potential indicators include:

• Co-authorship
• Citation relationships
• Institutional collaboration
• Dataset to publication links
• Project relationships
• Researcher networks
• Interdisciplinary relationships
• Institutional partnerships

Connectivity introduces a network perspective into research visibility. A publication connected to numerous relevant research entities may have greater structural visibility than an isolated publication, even where both have identical citation counts.

Research question. Does network connectivity predict the growth and persistence of research visibility?

5.6 Dimension: Citation Visibility

Definition. Citation visibility refers to the extent to which a research output becomes represented within subsequent scholarly citation relationships.

Potential indicators include:

• Citation count
• Citation velocity
• Citing author diversity
• Citing institution diversity
• Geographic citation reach
• Disciplinary citation reach
• Citation network centrality
• Citation trajectory

Citations provide important evidence of scholarly communication. However, as established in Bulletin No. 002, citation visibility should not be treated as equivalent to research impact: citations may represent methodological use, theoretical engagement, criticism, background discussion or other forms of scholarly interaction. Responsible research assessment frameworks caution against interpreting citation metrics without appropriate context, and the Leiden Manifesto in particular emphasises disciplinary differences, contextual interpretation and the complementary role of qualitative assessment (Hicks et al., 2015).

Research question. Under what conditions does citation visibility predict substantive scholarly influence?

5.7 Dimension: Openness

Definition. Openness concerns the degree to which research outputs and associated research resources are available for inspection, access, verification, reuse and connection.

Potential indicators include:

• Open access publication
• Open data
• Open methods
• Open protocols
• Open software
• Reusable metadata
• Transparent reporting
• Preprints
• Research repositories
• Open peer review practices

UNESCO's Recommendation on Open Science provides an international policy framework emphasising open access to scientific knowledge and broader openness of research processes and infrastructure (UNESCO, 2021), while the FAIR Guiding Principles set out concrete criteria for Interoperability and Reusability (Wilkinson et al., 2016). Openness can therefore facilitate visibility by increasing the number of pathways through which research can be accessed and reused. However, openness remains conceptually distinct from accessibility: an open dataset may technically be available but difficult to interpret if documentation is inadequate.

Research question. How does openness influence the discoverability, accessibility and reuse of research?

5.8 Dimension: Knowledge Reach

Definition. Knowledge reach represents the extent to which research extends beyond its immediate publication venue and disciplinary environment, across disciplines, institutions, countries, professional communities, policymakers, educators, industry, practitioners, civil society and communities.

Potential indicators include:

• High national reach
• Moderate to strong international reach
• Strong disciplinary reach
• Limited or extensive interdisciplinary reach
• Substantial practitioner reach

Knowledge reach recognises that research can circulate through multiple knowledge ecosystems simultaneously, and that these forms of reach need not move together. A multidimensional visibility framework should be capable of representing these different forms of reach independently rather than collapsing them into a single score.

Research question. Which characteristics of research predict broader disciplinary, geographical and professional reach?

The eight dimensions, together with their core guiding question and representative evidence, are summarised in Table 2.

Table 2. The ResearchTrics Research Visibility Dimensions Framework.

These dimensions should initially be treated as conceptually distinct but potentially correlated; empirical research is required to determine their statistical structure. Figure 1 offers a worked, hypothetical illustration of how a single researcher's visibility profile might be represented across the eight dimensions, using a simple three point qualitative scale (low, moderate, high) purely for illustration.

6.1 A Higher-Order Conceptual Model

One possibility is to conceptualise research visibility as a higher order construct, in which discoverability, accessibility and recognition function as more immediate first order factors, engagement, connectivity and citation visibility as intermediate factors, and openness and knowledge reach as outcomes that depend on the factors beneath them. Figure 2 illustrates one such arrangement.

This arrangement should not be interpreted as a confirmed factor structure. Three competing possibilities should be examined empirically, and are compared in Table 3.

Table 3. Three competing structural models for the eight dimensions of research visibility.

Determining which model best represents the phenomenon is an empirical question, and it is particularly important to resolve before developing any composite Research Visibility Metric.

Research visibility should not necessarily be treated as static. Consider a hypothetical article published in 2026. At the point of publication, discoverability might be moderate, accessibility high, and citation visibility zero by definition. Several years later, discoverability may be high, engagement and connectivity high, citation visibility substantial, and knowledge reach international. Figure 3 illustrates this kind of trajectory for four of the eight dimensions over a five year period, using hypothetical values for illustration.

This dynamic view suggests that future ResearchTrics research should investigate visibility trajectories, growth rates, visibility persistence, visibility decay, time to discovery, time to first citation, network expansion, and longitudinal visibility profiles more generally. A dynamic framework may eventually prove more informative than a single cross-sectional score, particularly for early career researchers whose visibility profile is still developing.

A major methodological concern is that research visibility is not independent of context. Citation and publication behaviour differs considerably across disciplines: citation practices differ between, for example, psychology and mathematics; publication structures differ between the humanities and the biomedical sciences; collaboration patterns differ between laboratory sciences and individual scholarship; language influences international discoverability; and research infrastructure differs considerably across countries.

The Leiden Manifesto explicitly warns that research assessment should account for differences between fields and avoid inappropriate comparisons based on universalised metrics (Hicks et al., 2015). Merton's account of the Matthew effect adds a further caution: visibility indicators can reflect and reinforce existing patterns of accumulated advantage rather than underlying quality alone, which is a particular concern for early career researchers and for researchers based in less well resourced institutions or countries (Merton, 1968).

Future ResearchTrics measurement should therefore consider, at minimum, the joint influence of discipline, geography, career stage, institution, research type and time before making any comparative judgement.

The multidimensional framework changes the question asked by research evaluators. Instead of asking only how many citations a researcher has, a richer evaluation system could ask a structured set of questions, summarised in Table 4.

Table 4. Reframing research evaluation questions around the eight dimensions of visibility.

This structured profile is broadly consistent with the spirit of the San Francisco Declaration on Research Assessment, which calls for evaluation based on the substantive content and reach of research rather than on a narrow set of journal-based proxies (San Francisco Declaration on Research Assessment, 2013).

A multidimensional model also has implications for research technology. A future research intelligence platform should ideally connect researcher identity, publication, journal, institution, project, dataset, method, instrument, citation, collaboration, research opportunity and knowledge reach as linked entities within a scholarly knowledge graph, rather than presenting these as disconnected records.

Such a system could provide a research visibility profile rather than simply displaying a publication count or an h-index. For example, a hypothetical researcher profile might read as follows: discoverability, high; accessibility, moderate; recognition, high; engagement, high; connectivity, moderate; citation visibility, high; openness, high; knowledge reach, international. A profile of this kind, illustrated visually in Figure 1 above, would provide substantially richer information than a single citation count.

The framework raises a fundamental measurement question: can research visibility be measured psychometrically? This question should not be answered by assuming that a composite score is automatically valid. Before constructing a Research Visibility Metric, empirical studies should examine the properties summarised in Table 5.

Table 5. Validity and reliability concepts relevant to the future development of a Research Visibility Metric.

These questions will be central to the future empirical development of ResearchTrics as a research programme.

The framework generates ten propositions for future empirical research, listed in Table 6.

Table 6. Research propositions arising from the ResearchTrics Research Visibility Dimensions Framework.

The framework established here creates several immediate research opportunities. Future ResearchTrics Bulletins should investigate the items grouped by theme in Table 7, moving from conceptualisation towards empirical validation.

Table 7. Research agenda for future ResearchTrics Bulletins, grouped by theme.

This sequence provides a direct bridge from conceptualisation to empirical validation, and each theme corresponds to a plausible future Bulletin or empirical study within the series.

Research visibility should be understood as a multidimensional property of scholarly communication and knowledge circulation. Building on the definition established in ResearchTrics Research Bulletin No. 001 and the visibility-impact distinction developed in Bulletin No. 002, this Bulletin proposes eight foundational dimensions: discoverability, accessibility, scholarly recognition, engagement, connectivity, citation visibility, openness and knowledge reach.

These dimensions describe different mechanisms through which research becomes observable, accessible, connected and capable of reaching relevant knowledge communities. The framework deliberately avoids equating visibility with quality or impact. A research output may be highly visible but have limited substantive influence; conversely, important research may generate substantial local or professional impact while remaining poorly represented in conventional bibliometric systems.

Future research should determine empirically whether research visibility is best represented as a set of correlated dimensions, a higher order latent construct, or a dynamic knowledge ecosystem, drawing on the established methodological literature summarised in this Bulletin (Hicks et al., 2015; Wilkinson et al., 2016; Haak et al., 2012; Priem et al., 2010; Merton, 1968). This distinction is essential before any composite research visibility metric is developed.

The ResearchTrics Research Bulletin Series will build upon this framework through subsequent methodological and empirical investigations. The ultimate objective is to move from the narrow question of how many citations a piece of research has, towards a more comprehensive question: how visible is this research across the knowledge ecosystem, through which pathways does that visibility emerge, and how does visibility relate to subsequent scholarly influence and impact?

Recommended Citation

Oladunmoye, E. O. (2026c). The dimensions of research visibility: A multidimensional framework for scholarly discoverability and reach. ResearchTrics Research Bulletin, 3.

In-Text Citation

(Oladunmoye, 2026c)

Recommended Citation for Subsequent ResearchTrics Papers

Research visibility can be conceptualised through multiple dimensions, including discoverability, accessibility, scholarly recognition, engagement, connectivity, citation visibility, openness and knowledge reach (Oladunmoye, 2026c).

Bulletin 003 is intended to function as the dimensional foundation of the ResearchTrics corpus. The citation architecture of the series is therefore cumulative:

• Oladunmoye (2026a): Definition of research visibility
• Oladunmoye (2026b): Visibility versus impact
• Oladunmoye (2026c): Dimensions of research visibility (this Bulletin)

Future papers in the series can legitimately cite all three prior Bulletins where relevant. The next logical paper is ResearchTrics Research Bulletin No. 004, provisionally titled 'A Taxonomy of Research Visibility Indicators: From Discoverability to Knowledge Reach'. That paper is intended to operationalise the eight dimensions introduced here and to serve as a reference point for subsequent empirical work developing and testing a Research Visibility Metric.