A data model and a cataloguing, storage and retrieval system for ancient document archives

  • Pasquale Savino ISTI-CNR - Italian Research Council - Information Science and Technology Institute http://orcid.org/0000-0002-8841-5440
  • Anna Tonazzini ISTI-CNR - Italian Research Council - Information Science and Technology Institute
  • Franca Debole ISTI-CNR - Italian Research Council - Information Science and Technology Institute

Abstract

Digitalization of ancient manuscripts is becoming a common practice in many archives and libraries, mainly for preservation purposes. This opens many new opportunities for the diffusion of these precious cultural assets, since several scholars and researchers, as well as the general public, may access and use them for research purposes, for study, and for general information. This is made possible if the documents, their descriptions, and the result of all processing activities performed on them are acquired at a good quality and can be easily accessed by using simple and powerful retrieval mechanisms.Acquired manuscripts suffer of degradations that may require different types of elaborations on the digital images, to improve their visual quality and legibility, or to discover hidden text that is not visible. Natural Language Processing requires the creation of transcriptions of the text contained in the manuscript, as well as encoding of the document structure and creation of user annotations.This paper presents a document management system and a metadata schema that make possible the storage and content-based retrieval of original documents, elaborations performed to improve their readability, textual transcriptions, and linguistic annotations. The archive will offer the possibility of describing, storing and accessing all the available manuscript versions, document transcriptions and annotations, and to search and retrieve documents based on all this information.
Published
Sep 14, 2019
How to Cite
SAVINO, Pasquale; TONAZZINI, Anna; DEBOLE, Franca. A data model and a cataloguing, storage and retrieval system for ancient document archives. International Journal of Information Science and Technology, [S.l.], v. 3, n. 5, p. 6 - 15, sep. 2019. ISSN 2550-5114. Available at: <https://innove.org/ijist/index.php/ijist/article/view/132>. Date accessed: 02 oct. 2022.
Section
Special Issue : Machine Learning and Natural Language Processing