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Unveiling Archive Users: Understanding Their Characteristics and Motivations

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Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration (ICADL 2023)

Abstract

An institution must understand its users to provide quality services, and archives are no exception. Over the years, archives have adapted to the technological world, and their users have also changed. To understand archive users’ characteristics and motivations, we conducted a study in the context of the Portuguese Archives. For this purpose, we analysed a survey and complemented this analysis with information gathered in interviews with archivists. Based on the most frequent reasons for visiting the archives, we defined six main archival profiles (genealogical research, historical research, legal purposes, academic work, institutional purposes and publication purposes), later characterised using the results of the previous analysis. For each profile, we created a persona for a more visual and realistic representation of users.

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Notes

  1. 1.

    Website CRAV—Available at: https://crav.arquivos.pt/login.

  2. 2.

    Website DigitArq—Available at: https://digitarq.arquivos.pt/.

  3. 3.

    Available at: https://www.surveymonkey.com/r/X8MMNBJ.

  4. 4.

    https://antt.dglab.gov.pt/sondagem-aos-clientes/.

References

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Acknowledgements

Special thanks to Dr José Furtado for his help in the initial phase of this study and for providing the data from the satisfaction surveys. Thanks, also, to all the DGLAB archivists for their willingness to participate in this study. This work is financed by National Funds through the Portuguese funding agency, FCT – Fundação para a Ciência e a Tecnologia within project DSAIPA/DS/0023/2018. Inês Koch is also financed by National Funds through the Portuguese funding agency, FCT, within the research grant 2020.08755.BD.

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Correspondence to Inês Koch .

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Ponte, L., Koch, I., Teixeira Lopes, C. (2023). Unveiling Archive Users: Understanding Their Characteristics and Motivations. In: Goh, D.H., Chen, SJ., Tuarob, S. (eds) Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. ICADL 2023. Lecture Notes in Computer Science, vol 14458. Springer, Singapore. https://doi.org/10.1007/978-981-99-8088-8_10

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  • DOI: https://doi.org/10.1007/978-981-99-8088-8_10

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