Exploring library loan data for modelling the reading culture

Project libDat

Mats Neovius, Kati Launis, Olli Nurmi

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

Reading is evidently a part of the cultural heritage. With respect to nourishing this, Finland is exceptional in the sense that it has a unique library system, used regularly by 80% of the population. The Finnish library system is publicly funded and free-of-charge. On this, the consortium "LibDat: Towards a More Advanced Loaning and Reading Culture and its Information Service" (2017-2021, Academy of Finland) sets out to explore the loaning and reading culture and its information service to the end that this project's results would help officials to elaborate upon Finnish public library services. The project, as well as the data-Analysis, has just started, so the paper contains more hypotheses than final results. The project is part of the constantly growing field of Digital Humanities, and its most important scientific benefit is to show how large "born digital " material, new computational methods and literary-sociological research questions can be integrated into the study of contemporary literary culture. The project's collaborator, Vantaa City Library, has collected daily loan data since July 27, 2016. This loan data is objective, crisp, and big. In this position paper, the main contribution is a discussion on the limitations that the data poses and the literary questions that may be explored by computational means. For this, we describe the data structure of a loan event and outline the dimensions of how to interpret the data.

Original languageEnglish
Title of host publicationProceedings of the Digital Humanities in the Nordic Countries 3rd Conference
EditorsEetu Mäkelä, Mikko Tolonen, Jouni Tuominen
Place of PublicationHelsinki
PublisherUniversity of Helsinki
Pages386-393
Publication statusPublished - 2018
MoE publication typeNot Eligible
Event3rd Conference on Digital Humanities in the Nordic Countries, DHN 2018 - Helsinki, Finland
Duration: 7 Mar 20189 Mar 2018

Publication series

NameCEUR Workshop Proceedings
PublisherRWTH Aachen
Volume2084
ISSN (Print)1613-0073

Conference

Conference3rd Conference on Digital Humanities in the Nordic Countries, DHN 2018
CountryFinland
CityHelsinki
Period7/03/189/03/18

Fingerprint

Information services
Computational methods
Data structures

Keywords

  • Finnish loaning and reading habits
  • Library loan data
  • Sociology of literature

Cite this

Neovius, M., Launis, K., & Nurmi, O. (2018). Exploring library loan data for modelling the reading culture: Project libDat. In E. Mäkelä, M. Tolonen, & J. Tuominen (Eds.), Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference (pp. 386-393). Helsinki: University of Helsinki. CEUR Workshop Proceedings, Vol.. 2084
Neovius, Mats ; Launis, Kati ; Nurmi, Olli. / Exploring library loan data for modelling the reading culture : Project libDat. Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference. editor / Eetu Mäkelä ; Mikko Tolonen ; Jouni Tuominen. Helsinki : University of Helsinki, 2018. pp. 386-393 (CEUR Workshop Proceedings, Vol. 2084).
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Neovius, M, Launis, K & Nurmi, O 2018, Exploring library loan data for modelling the reading culture: Project libDat. in E Mäkelä, M Tolonen & J Tuominen (eds), Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference. University of Helsinki, Helsinki, CEUR Workshop Proceedings, vol. 2084, pp. 386-393, 3rd Conference on Digital Humanities in the Nordic Countries, DHN 2018, Helsinki, Finland, 7/03/18.

Exploring library loan data for modelling the reading culture : Project libDat. / Neovius, Mats; Launis, Kati; Nurmi, Olli.

Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference. ed. / Eetu Mäkelä; Mikko Tolonen; Jouni Tuominen. Helsinki : University of Helsinki, 2018. p. 386-393 (CEUR Workshop Proceedings, Vol. 2084).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AB - Reading is evidently a part of the cultural heritage. With respect to nourishing this, Finland is exceptional in the sense that it has a unique library system, used regularly by 80% of the population. The Finnish library system is publicly funded and free-of-charge. On this, the consortium "LibDat: Towards a More Advanced Loaning and Reading Culture and its Information Service" (2017-2021, Academy of Finland) sets out to explore the loaning and reading culture and its information service to the end that this project's results would help officials to elaborate upon Finnish public library services. The project, as well as the data-Analysis, has just started, so the paper contains more hypotheses than final results. The project is part of the constantly growing field of Digital Humanities, and its most important scientific benefit is to show how large "born digital " material, new computational methods and literary-sociological research questions can be integrated into the study of contemporary literary culture. The project's collaborator, Vantaa City Library, has collected daily loan data since July 27, 2016. This loan data is objective, crisp, and big. In this position paper, the main contribution is a discussion on the limitations that the data poses and the literary questions that may be explored by computational means. For this, we describe the data structure of a loan event and outline the dimensions of how to interpret the data.

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EP - 393

BT - Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference

A2 - Mäkelä, Eetu

A2 - Tolonen, Mikko

A2 - Tuominen, Jouni

PB - University of Helsinki

CY - Helsinki

ER -

Neovius M, Launis K, Nurmi O. Exploring library loan data for modelling the reading culture: Project libDat. In Mäkelä E, Tolonen M, Tuominen J, editors, Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference. Helsinki: University of Helsinki. 2018. p. 386-393. (CEUR Workshop Proceedings, Vol. 2084).