lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Artificial Intelligence and Pattern Recognition Technologies for Cultural Heritage: Involvement of Optical Character Recognition Software for Citizen Science in the processes for Crowdsourcing of Ancient Italian Texts.
Linnaeus University, Faculty of Arts and Humanities, Department of Cultural Sciences. Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (Digital Humanities)
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
Sustainable development
Not refering to any SDG
Abstract [en]

Cultural heritage makes reference to an extremely diverse set of sources. More specifically, historical artifacts as well as intangible elements of a community’s history, pertain to cultural heritage. However, when looking at the conservation, the enrichment, and the divulgation of these elements, the question becomes more complex. Even more so, when a context of nebulous regulation, unequal distribution of resources and funding of cultural heritage institutions, as well as a bureaucratically complex division of competencies between territories, are present. This is the case in Italy, and more specifically, Southern and Central Italy, where all these issues are present, and further hinder the exploration of undiscovered historical material, as well as the organization and divulgation of discovered material. 

Following this discrepancy along the lines of legal and practical restrictions, this thesis aims to explore and evaluate how technology can obviate to said issues. For instance, a methodological exercise was endeavored by scanning some ancient texts, in Latin and in Old Italian, and by running an optical character recognition software on the latter. 

More specifically, this thesis applies the paradigm of citizen science for crowdsourcing to explore how well optical character recognition software works in terms of accessibility and efficiency. As such, this methodological exercise does not consist primarily of a technological evaluation but aims at opening up new ways for the public to interact with cultural heritage institutions, for exchanging historical information while respecting the legal and practical considerations that were mentioned. In conclusion, by highlighting this issue, it would be possible to further research and enrich the publicly available data on Italian educational history between the 18th and the 19th Century.  

 

Place, publisher, year, edition, pages
2022. , p. 247
Keywords [en]
Artificial Intelligence, Pattern Recognition, Web-Technologies, Cultural Heritage, Crowdsourcing, Citizen Science, Optical Character Recognition, Accessibility.
National Category
Humanities and the Arts
Identifiers
URN: urn:nbn:se:lnu:diva-114820OAI: oai:DiVA.org:lnu-114820DiVA, id: diva2:1676488
Subject / course
Digital humanities
Educational program
Digital humanities, master programme, 120 credits
Supervisors
Examiners
Available from: 2022-07-01 Created: 2022-06-26 Last updated: 2022-07-01Bibliographically approved

Open Access in DiVA

fulltext(10105 kB)500 downloads
File information
File name FULLTEXT01.pdfFile size 10105 kBChecksum SHA-512
b78f67b47492f0fb6efa2cccec4a69a154add40e6a53a43022f2fa4d852b3aa5eea26ae6426ba4246d3add892cb12d843af73adb47eaf69ec45eed6983bebd80
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Ballerino, Julie
By organisation
Department of Cultural SciencesDepartment of computer science and media technology (CM)
Humanities and the Arts

Search outside of DiVA

GoogleGoogle Scholar
Total: 501 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 843 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf