Academic Librarianship and Information Research

Academic Librarianship and Information Research

From Managing Static Information Resources to Managing Dynamic Information Flows: Redefining the Role of Librarians and Information Professionals in the Face of Transformative Technologies

Document Type : Editorial Note

Author
Department of Information Science and Knowledge Management, Faculty of Public Administration and Organizational Sciences, School of Management, University of Tehran, Tehran.
10.22059/jlib.2026.108444
Abstract
Objective: This study examines the paradigmatic shift in Library and Information Science (LIS) from managing static information resources, characterized by fixed identity, well-defined boundaries, and stable metadata, to managing dynamic information flows generated by transformative technologies including the dynamic web, Internet of Things (IoT), social media, and generative artificial intelligence (GenAI). The study aims to redefine the role of librarians and information professionals in response to this transformation and address the growing disconnect between LIS education, research, and practice.
Method: This conceptual analysis adopts an interdisciplinary approach, synthesizing theoretical frameworks from data science, software engineering, social network analysis, communication studies, and LIS. The study reviews ontological theories of information flow alongside sociological theories. It employs comparative analysis between the traditional “access paradigm” and the emergent “information flow management paradigm”, examining their respective key questions, primary roles, tools, units of analysis, and temporal dimensions.
Results: The analysis reveals that dynamic information flows fundamentally challenge traditional LIS assumptions regarding information identity, retrieval models, needs assessment, and classification systems. Information units in dynamic flows possess momentary, context-dependent identities that elude traditional metadata schemas such as MARC and Dublin Core. The “store-then-retrieve” model is being superseded by “real-time monitoring–filtering–push” models, wherein information must be proactively channeled to users before explicit requests are articulated. Traditional needs assessment methods prove inadequate for identifying emerging patterns, while rigid subject classifications lose effectiveness against non-linear, tag-based interconnections. The findings demonstrate that LIS curricula, textbooks, and information systems remain predominantly designed around static resource management, despite practical organizational requirements to engage with dynamic flows.
Conclusions: This study concludes that LIS must redefine itself from a discipline focused on organizing static documents for future access to one actively engaged in monitoring, filtering, and directing dynamic information flows. The role of librarians and information professionals evolves from “gatekeeper” to “navigator”, a facilitator who determines what information should be retained, discarded, and to whom and when it should be delivered. This paradigm shift carries practical, theoretical, educational, and methodological implications requiring curricular redesign, adoption of computational research methods, and interdisciplinary engagement with data science and communication studies. Failure to address this transformation risks marginalizing the discipline, while proactive engagement offers opportunity to revitalize the strategic role of librarians and information professionals in the era of big data, IoT, and GenAI.
Keywords

Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136. https://doi.org/10.2307/3250961
Barwise, J., & Seligman, J. (1997). Information flow: The logic of distributed systems. Cambridge University Press.
Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554-571. https://doi.org/10.1287/mnsc.32.5.554
Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Harvard Business School Press.
Dervin, B. (1998). Sense-making theory and practice: An overview of user interests in knowledge seeking and use. Journal of Knowledge Management, 2(2), 36–46.
Domínguez, E. (2018). The theory of info-dynamics: Rational foundations of information-knowledge dynamics. Springer. 
Ellis, D. (1989). A behavioural approach to information retrieval system design. Journal of Documentation, 45(3), 171–212.
Fisher, K. E., Durrance, J. C., & Hinton, M. B. (2004). Information grounds and the use of need-based services by immigrants in Queens, New York: A context-based, outcome evaluation approach. Journal of the American Society for Information Science and Technology, 55(8), 754–766. 
Floridi, L. (2011). The philosophy of information. Oxford University Press.
Gama, J. (2010). Knowledge discovery from data streams. Chapman and Hall/CRC. 
Isaac, A. M. (2019). The semantics latent in Shannon information. The British Journal for the Philosophy of Science, 70(1), 103-125. https://doi.org/10.1093/bjps/axx029
Katz, E., & Lazarsfeld, P. F. (1955). Personal influence: The part played by people in the flow of mass communications. Free Press. 
Kuhlthau, C. C. (1991). Inside the search process: Information seeking from the user’s perspective. Journal of the American Society for Information Science, 42(5), 361–371.
Lazarsfeld, P. F., Berelson, B., & Gaudet, H. (1948). The people’s choice: How the voter makes up his mind in a presidential campaign. Columbia University Press. 
Leitner, G., & Jinmin, H. (2019). From gatekeeper to gateway to gate-opener: A new role for the global library field. Journal of Library Science in China, 45(5), 27-32. https://doi.org/10.13530/j.cnki.jlis.190038
Lewin, K. (1947). Frontiers in group dynamics: Concept, method and reality in social science; social equilibria and social change. Human Relations, 1(1), 5–41. https://doi.org/10.1177/001872674700100103
Lievrouw, L. A., & Finn, T. A. (1996). New information technologies and informality: comparing organizational information flows using the CSM. International Journal of Technology Management, 11(1-2), 28-42. https://doi.org/10.1504/IJTM.1996.025415 
Marijuán, P. C., & Navarro, J. (2014). New times and new challenges for information science: From cellular systems to human societies. Information, 5(1), 101–119. 
Mushakoji, S. (1994). Scientific information flow as a series of scientific texts: A new framework for research. Library and Information Science, 32, 65-84.
Mushakoji, S. (2004). How 'knowledge' is situated in some research areas of library and information science. Library and Information Science, (52), 1-42. https://doi.org/10.46895/lis.52.1
Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press.
Pettigrew, K. E. (1999). Waiting for chiropody: Contextual results from an ethnographic study of the information behaviour among attendees at community clinics. Information Processing & Management, 35(6), 801–817.  https://doi.org/10.1016/S0306-4573(99)00027-8
Saracevic, T. (1975). Relevance: A review of and a framework for the thinking on the notion in information science. Journal of the American Society for Information Science, 26(6), 321–343. https://doi.org/10.1002/asi.4630260604
 Saracevic, T. (2007). Relevance: A review of the literature and a framework for thinking on the notion in information science. Journal of the American Society for Information Science and Technology, 58(14), 2126–2144. https://doi.org/10.1002/asi.20681
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423.
Sommaruga, G. (Ed.). (2009). Formal Theories of Information: From Shannon to Semantic Information theory and general concepts of information. Springer. http://doi.org/10.1007/978-3-642-00659-3
Tidke, B., Mehta, R. G., & Dhanani, J. (2018). Real-time bigdata analytics: A stream data mining approach. In Recent findings in intelligent computing techniques: Proceedings of the 5th ICACNI 2017 (Vol. 2, pp. 345–351). Springer.