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Archives and records management in machine learning technologies context: a research hypothesis on university records

Ioannis Triantafyllou, Christos Chrysanthopoulos, Yannis Stoyannidis, Anastasios Tsolakidis



Purpose - This paper explores the goal and potential of integrating machine learning technologies into archives and records management practices. As the volume and complexity of digital records continue to grow, traditional methods of organising, classifying, and managing records face new challenges. Machine learning technologies offer opportunities to revolutionise how records are maintained, accessed, and used.

Design/methodology/approach - The relationship between records and archive management and machine learning practices is presented through the literature. This paper proposes a case study implementation of machine learning practices for the subject classification of records at the University of West Attica.

Findings - This paper presents a research hypothesis placing the subject classification of records at the center of the discussion. It highlights the necessity of deepening the standardisation of government actions record management processes. 

Originality/value - By exploring this topic, the paper seeks to contribute to a deeper understanding of the transformative role that machine learning technologies can play in archives and records management and to inform future practices and decision-making in the field. It is also the first theoretical part of an ongoing research project on the subject classification of the University of West Attica records.   


Archives and records management; Machine learning; Computational archival science; University archives; Subject classification


Sweeney, S. (2008). The ambiguous origins of the archival principle of "provenance". Libraries & the Cultural Record, 43(2), 193-213.

Hensen, S. L. (1993). The first shall be first: APPM and its impact on American archival description. Archivaria, 35, 64-70.

Duranti, L. (1998). Diplomatics: New Uses for an Old Science. Lanham, MD: Scarecrow Press, in association with the Society of American Archivists and Association of Canadian Archivists, 177.

Duranti, L. (2001). The impact of digital technology on archival science. Archival Science, 1(1), 39-55.

Pandey, N., Sanyal, D. K., Hudait, A., & Sen, A. (2017). Automated classification of software issue reports using machine learning techniques: an empirical study. Innovations in Systems and Software Engineering, 13, 279-297.

Yakel, E., & Torres, D. (2003). AI: Archival intelligence and user expertise. The American Archivist, 66(1), 51-78.

Manghi, P., Mikulicic, M., & Atzori, C. (2012). De-duplication of aggregation authority files. International Journal of Metadata, Semantics, and Ontologies, 7(2), 114-130.

Niu, Y., Ying, L., Yang, J., Bao, M., & Sivaparthipan, C. B. (2021). Organisational business intelligence and decision making using big data analytics. Information Processing & Management, 58(6), 102725.

Fennelly, L. J. (2014). Museum, archive, and library security. Butterworth-Heinemann.

Stančić, H. (2018). Computational archival science. Moderna Arhivistika, 1(2), 323-330. Computational-Archival-Science.pdf (

Traub, M. C., Van Ossenbruggen, J., & Hardman, L. (2015). Impact analysis of OCR quality on research tasks in digital archives. In Research and Advanced Technology for Digital Libraries: 19th International Conference on Theory and Practice of Digital Libraries, TPDL 2015, Poznań, Poland, September 14-18, 2015, Proceedings 19 (pp. 252-263). Springer International Publishing.

Jo, E. S., & Gebru, T. (2020, January). Lessons from archives: Strategies for collecting sociocultural data in machine learning. In Proceedings of the 2020 conference on fairness, accountability, and transparency (pp. 306-316).

Thibodeau, K. (2018, December). Computational Archival Practice: Towards A Theory for Archival Engineering. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 2753-2760). IEEE.

Chrysanthopoulos, C., Drivas, I., Kouis, D., & Giannakopoulos, G. (2023). University archives: the research road travelled and the one ahead. Global Knowledge, Memory and Communication, 72(1/2), 44-68.

Karamagioli, E., Staiou, E. R., & Gouscos, D. (2014). Government spending transparency on the internet: an assessment of Greek bottom-up initiatives over the Diavgeia Project. International Journal of Public Administration in the Digital Age (IJPADA), 1(1), 39-55.

Mastora, A., Koloniari, M., & Monopoli, M. (2021). The Government Information Landscape in Greece. IFLA Professional Reports, 64-82. The Government Information Landscape in Greece - ProQuest

The University of West Attica (UNIWA) was founded in March 2018 by the National Law 4521.

Vorgia, F., Triantafyllou, I., & Koulouris, A. (2017). Hypatia Digital Library: A text classification approach based on abstracts. In Strategic Innovative Marketing: 4th IC-SIM, Mykonos, Greece 2015 (pp. 727-733). Springer International Publishing.

Triantafyllou, I., Vorgia, F., & Koulouris, A. (2019). Hypatia Digital Library: A novel text classification approach for small text fragments. Journal of Integrated Information Management, 4, 16-23.

Cushing, A.L. and Osti, G. (2023), ""So how do we balance all of these needs?": how the concept of AI technology impacts digital archival expertise", Journal of Documentation, 79(7), pp. 12-29.

Triantafyllou, I., Drivas, I. C., & Giannakopoulos, G. (2020). How to Utilise my App Reviews? A Novel Topics Extraction Machine Learning Schema for Strategic Business Purposes. Entropy, 22(11), 1310.

Colavizza, G., Blanke, T., Jeurgens, C., & Noordegraaf, J. (2021). Archives and AI: An overview of current debates and future perspectives. ACM Journal on Computing and Cultural Heritage (JOCCH), 15(1), 1-15.

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DOI: 10.26265/jiim.v8i1.4517


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