Information Flow Frameworks: Communication of Research-Based Information into Policy

student submissionThe demand for usable scientific information is increasing along with a greater need to understand how research-based information flows in pathways into both policy and practice settings. Yet, a number of issues with respect to the pathways, through which information is obtained, can impede the use of research in decision-making. The literature on this subject over the past three decades provides examples of the channels that policy makers and practitioners use to access and use research. In addition, the literature discusses several frameworks that aim to explain information flow and also address limitations of information use. The pathway models can be categorised into two main types: linear and non-linear. Linear models focus on traditional, one-way flow of information, streaming from research to society at large (McNie, 2007). The non-linear models show network-like characteristics that promote the notion of two-way communication and interaction among producers of information (e.g., scientists), and the potential users of the information (e.g., policy makers and practitioners) (Duff, 1997; McNie, 2007; Nutley, Walter & Davies, 2007; Parag, Hamilton, White & Hogan, 2013). The key element implied in recent approaches is that communication among the researchers and decision-makers is to be encouraged in order to achieve more effective production and use of research based information (Hartley & Glass, 2010; McNie, 2007). Note, in this post, the terms “policy makers and decision-makers”; and “research-based, evidence-based, and scientific information” are used interchangeably.

Pathways of Research-Based Information: Factors Affecting Information Flow and Use

Policy makers and practitioners acquire research-based information in diverse ways. The more traditional way is from published materials, such as books, research reports and summaries, and journal articles. These forms of information often appeal to policy makers more than practitioners, who may seek more detailed research materials in their field (Nutley et al., 2007). Several methods of information dissemination—including local resource centers, dissemination systems within organizations, and knowledge brokers—are among the main pathways to obtain evidence-based information (Duff, 1997; McNie, 2007; Nutley et al., 2007). Both policy makers and practitioners mentioned that they use a variety of additional sources of scientific information such as conferences and workshops, the news media, personal and interpersonal contacts, individual networking, and increasingly the Internet (Duff, 1997; McNie, 2007; Nutley et al., 2007). Caveats that apply to some of these sources range from limited access and information overload to bias in the selection of research findings, all of which may affect decision-making (Nutley et al., 2007).

Factors Influencing the Use of Research-Based Information

The majority of the literature referenced in this post acknowledges the significance of the following factors on research use in policy and practice:

Credibility and Quality

Credibility refers the ability to validate research information on the basis of the research methods and the quality of the data used in the research (UNEP & IOC-UNESCO, 2009). Policy-makers and practitioners generally seek information of high quality and aim to not use questionable information, which may arise from the absence of competent research methodology (Nutley et al., 2007). In addition, the credibility and reputation of the information sources are highly significant in determining whether information should be used in policy development (Nutley et al., 2007). Scientific credibility is a core value that is required to enable the use and influence of research-based information in policy contexts (Hartley & Glass, 2010), especially given the recent rise in public demand for greater scrutiny of policy and decision-making (McNie, 2007).

Relevance (Salience)

Salience relates to the audience and its information needs. Relevance and timeliness may be more important than other factors for some users when they assess the usefulness of the research for their needs (Nutley et al., 2007; UNEP & IOC-UNESCO, 2009). This issue may not necessarily be about a shortage of scientific information, but rather about the production of relevant, and thus useful, information that meets the decision-maker’s needs (McNie, 2007). Additionally, the values of stakeholders and the way information is packaged and communicated can determine its relevance and thus its use (McNie, 2007).


Legitimacy refers to objective and unbiased information, and transparency of production and transmission processes of information (McNie, 2007; UNEP & IOC-UNESCO, 2009). This factor also highlights the importance of including stakeholders’ interests and concerns without bias (McNie, 2007; UNEP & IOC-UNESCO, 2009)


Iterativity underscores the requirement for assessment frameworks that help to shape effective internal and external networks through repetitive interaction (McNie, 2007) such as the Regular Review Process and Assessment of Assessments (UNEP & IOC-UNESCO, 2009). This factor supports capacity building and improved networking between science, decisions makers, and multiple stakeholders, all of which can promote suitable and effective information-flow (McNie, 2007; UNEP & IOC-UNESCO, 2009).

Models for Understanding the Flow of Research-Based Information

Linear Information Pathway Models

Duff (1997) presented a range of post-World War II models that explored the information flow and communication processes. One example of the top-down models is the document network articulated by P. J. Judge in 1967 that conceptualizes the information chain by recognizing different producing bodies (e.g., government and non-government) and distinct types of information such as primary, secondary and gray literature (Duff, 1997). The drawbacks of this model (and linear models in general) are: it is characterized by one-way information flow, it is inapplicable to the present-day complex information world given the rise of the Internet, and it oversimplifies the dynamic relationship of science and society, and thus contributes to a gap between science and society (Duff, 1997; McNie, 2007).

Non-Linear Information Pathway Models

Recent models present a more dynamic nature between science and policy decisions and society. The 1993 Royal Society Pathways of information flow framework, for example, assumes a theory of the information chain that recognizes a range of information types (e.g., gray literature), and formal and informal information routes (e.g., conferences, electronic hosts, and email), and potential routes that were overlooked by the earlier post-war linear models (Duff, 1997). A dynamic or collaborative approach is considered to be more effective in producing useful information and in bridging the gap between science and policy than the linear approaches (McNie, 2007). The dynamic models highlight the concept of network analysis of information systems, which advances understanding of the communication processes and their efficiency (Parag et al., 2013).

Present Day Approaches: Communication between Science and Policy

More recent approaches have employed network analysis to study the science-policy interface. Network analysis helps to uncover decision-making structures and processes as well as the flow and influence of scientific information within them (Hartley & Glass, 2010). Social network analysis offers insights about connections between different actors, both individuals and organizations, and with a stronger focus on communication, network analysis can examine the access routes to scientific information, communication pathways, and patterns that actors generate (Hartley & Glass, 2010). One of the main communication limitations that this analysis can illustrate is the heavy dependence on individuals or organizations acting as bridges, whose absence can threaten the connectivity of a network (Hartley & Glass, 2010). Building and maintaining active networks of scientists and society (or policy practitioners) can build robust capacity to support effective information flow and stronger relations between researchers and stakeholders (McNie, 2007). This interaction enhances the science-policy process and emphasises the contributions of stakeholders in shaping science and policy (McNie, 2007).

Another concept that enhances the production and the use of scientific information is the Reconciling Supply and Demand approach (RSD) (McNie, 2007). This perspective provides an opportunity to assess the usefulness of evidence-based information by focusing on the demand perspective (i.e., users’ needs) (McNie, 2007). This framework can help to bridge the gap between researchers and decision-makers and achieve an effective supply of research information that is beneficial for policy- and decision-makers (McNie, 2007).

Final Remarks

The models and approaches discussed above are examples that allow building understanding of information flow and its complexity and also address issues related to science and policy (and vice versa). For instance, some approaches provide insights on how to meet the needs of research users through establishing networks that enhance credibility and legitimacy of information (Hartley and Glass, 2010). Additionally, such collaborative approaches, as opposed to linear models, increase two-way communication and understanding of the science-policy relationships (McNie, 2007). One important message for researchers and scientists is to clearly identify key audiences, to ensure productive communication, and thus, meet their specific information needs (UNEP & IOC-UNESCO, 2009). From a policy perspective, decision makers should be able to assess their use of research information, its relevance to decision-making processes, and hence, determine their policy information needs and detect gaps currently existing in the information chain process (McNie, 2007; UNEP & IOC-UNESCO, 2009). Mutual communication is, therefore, key to reduce, if not bridge, the gap between science and society for better mobilization of research based-information and enhanced decision making.



Duff, A. S. (1997). Some post-war models of the information chain. Journal of Librarianship and Information Science, 29, 179-187.

Hartley, T. W., & Glass, C. (2010). Science-to-management pathways in US Atlantic herring management: Using governance network structure and function to track information flow and potential influence. ICES Journal of Marine Science, 67, 1154-1163.

McNie, E. (2007). Reconciling the supply of scientific information with user demands: An analysis of the problem and review of the literature. Environmental Science & Policy, 10, 17-38.

Nutley, S. M., Walter, I., & Davies, H. T. O. (2007). Using evidence. How research can inform public services. Bristol: The Policy Press.

Parag, Y., Hamilton, J., White, V., & Hogan, B. (2013). Network approach for local and

community governance of energy: The case of Oxfordshire. Energy Policy, 62, 1064-1077

UNEP & IOC-UNESCO. (2009). An assessment of assessments, findings of the group of

experts. Summary for decision makers. Retrieved from


Author: Noha AlSharif


This blog post is part of a series of posts authored by students in the graduate course “The Role of Information in Public Policy and Decision Making,” offered at Dalhousie University.

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