Document Open Access Logo

Digital Art Technical Sources for the Netherlands: Integration and Improvement of Sources on Glass for a Sustainable Future – Art DATIS

Authors Carlotta Capurro , Vera Provatorova , Marieke Hendriksen , Evangelos Kanoulas , Sven Dupré

PDF
Thumbnail PDF

File

OASIcs.Commit2Data.9.pdf
  • Filesize: 7.15 MB
  • 11 pages

Document Identifiers

Author Details

Carlotta Capurro
  • Utrecht University, The Netherlands
Vera Provatorova
  • University of Amsterdam, The Netherlands
Marieke Hendriksen
  • Huygens Institute, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands
Evangelos Kanoulas
  • University of Amsterdam, The Netherlands
Sven Dupré
  • Utrecht University, The Netherlands

Funding

NWO Innovational Research Incentives Scheme Vidi (016.Vidi.189.039), grant number NWO Smart Culture - Big Data/Digital Humanities, 314-99-301.

Cite AsGet BibTex

Carlotta Capurro, Vera Provatorova, Marieke Hendriksen, Evangelos Kanoulas, and Sven Dupré. Digital Art Technical Sources for the Netherlands: Integration and Improvement of Sources on Glass for a Sustainable Future – Art DATIS. In Commit2Data. Open Access Series in Informatics (OASIcs), Volume 124, pp. 9:1-9:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/OASIcs.Commit2Data.9

Abstract

Art DATIS (Digital Art Technical sources for the Netherlands: Integration and improvement of sources on glass for a Sustainable future) is a five-year research project (2018-2023) within the Netherlands Organisation for Scientific Research’s (NWO) Big Data / Digital Humanities program. The project is a collaboration between the Universities of Utrecht and Amsterdam, RKD Netherlands Institute for Art History, the Vrij Glas Foundation, and Picturae. The project investigates how to approach the automatic transcription and documentation of heterogeneous archival resources. The central object of the project is the archive of the Dutch glass artist Sybren Valkema (1916–96). Documents were digitised, and their content was made searchable through the processes of OCR and HTR. Through digitisation and the analysis of archival documents, the project aims to understand how traditional knowledge and practices of glassmaking were innovated during the twentieth century.

Subject Classification

ACM Subject Classification
  • Applied computing → Fine arts
  • Computing methodologies → Neural networks
Keywords
  • Digital Humanities
  • Archives
  • Digitisation
  • Datafication
  • Digital Art History
  • Technical Art History

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

References

  1. ARTECHNE. ARTECHNE - Technique in the Arts, 1500-1950 bar Technique in the Arts, 1500-1950: Concepts, Practices, Expertise. URL: https://artechne.wp.hum.uu.nl.
  2. Joan Falconer Byrd and Harvey K. Littleton. Harvey K. Littleton - a life in glass: founder of America’s studio glass movement. Skira Rizzoli, New York, 2011. Google Scholar
  3. Fiona Cameron and Helena Robinson. Digital Knowledgescapes: Cultural, Theoretical, Practical, and Usage Issues Facing Museum Collection Databases in a Digital Epoch. In Fiona Cameron and Sarah Kenderdine, editors, Theorizing Digital Cultural Heritage, pages 165-191. The MIT Press, March 2007. URL: https://doi.org/10.7551/mitpress/9780262033534.003.0010.
  4. Carlotta Capurro and Gertjan Plets. Europeana, EDM, and the Europeanisation of cultural heritage institutions. Digital Culture and Society, 6(2):163-189, 2020. URL: https://doi.org/DOI 10.14361/dcs-2020-0209.
  5. Carlotta Capurro, Vera Provatorova, and Evangelos Kanoulas. Experimenting with training a neural network in transkribus to recognise text in a multilingual and multi-authored manuscript collection. Heritage, 6(1212):7482-7494, December 2023. URL: https://doi.org/10.3390/heritage6120392.
  6. Sebastian Colutto, Philip Kahle, Hackl Guenter, and Guenter Muehlberger. Transkribus. A Platform for Automated Text Recognition and Searching of Historical Documents. In 2019 15th International Conference on eScience (eScience), pages 463-466, San Diego, CA, USA, September 2019. IEEE. URL: https://doi.org/10.1109/eScience.2019.00060.
  7. Read Coop. Training models. data preparation, 2023. URL: https://help.transkribus.org/data-preparation.
  8. Art DATIS. Art DATIS project. URL: https://artdatis.nl.
  9. Sven Dupré. Art Educational Reforms and the Studio Glass Movement: Artists’ Ambivalent Self-Representation as Actors of Lost Knowledge. In Johan Östling, David Larsson Heidenblad, and Anna Nilsson Hammar, editors, Knowledge Actors: Revisiting Agency in the History of Knowledge. Nordic Academic Press, Lund, 2023. Google Scholar
  10. Susanne Kaatherine Frantz. Artists and Glass. A History of International Studio Glass. PhD thesis, The University of Arizona, 1987. Google Scholar
  11. Maya R. Gupta, Nathaniel P. Jacobson, and Eric K. Garcia. Ocr binarization and image pre-processing for searching historical documents. Pattern Recognit., 40:389-397, 2007. URL: https://api.semanticscholar.org/CorpusID:15012496, URL: https://doi.org/10.1016/J.PATCOG.2006.04.043.
  12. Stuart Hall. Constituting an archive. Third Text, 15(54):89-92, March 2001. URL: https://doi.org/10.1080/09528820108576903.
  13. Karin Hansson, Anna Näslund Dahlgren, and Teresa Cerratto Pargman. Datafication and cultural heritage: Critical perspectives on exhibition and collection practices. Information I& Culture, 57(1):1-5, March 2022. URL: https://doi.org/10.7560/IC57101.
  14. Marieke M. A. Hendriksen. Building the ARTECHNE Database: How to Develop a Multi-Purpose Database for an Interdisciplinary Project. IDEAH, May 2020. URL: https://doi.org/10.21428/f1f23564.e6779c76.
  15. Anthony Kay. Tesseract: an Open-Source Optical Character Recognition Engine bar Linux Journal. LINUX Journal, July 2007. URL: https://www.linuxjournal.com/article/9676.
  16. M.D. Lynn. American Studio Glass, 1960-1990. Hudson Hills Press, 2004. URL: https://books.google.nl/books?id=b4KhNlxnyOEC.
  17. Sue Newell and Marco Marabelli. Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of “datification”. Journal of Strategic Information Systems, 24(2644093), March 2015. URL: https://doi.org/10.2139/ssrn.2644093.
  18. NWO. Smart culture - nwo, February 2022. URL: https://www.nwo.nl/en/researchprogrammes/creative-industry/smart-culture.
  19. Ada Polak. Modern Glass. Faber I& Faber, New York, thomas yoseloff edition, 1962. Google Scholar
  20. Vera Provatorova, Samarth Bhargav, Svitlana Vakulenko, and Evangelos Kanoulas. Robustness evaluation of entity disambiguation using prior probes: the case of entity overshadowing. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 10501-10510, 2021. URL: https://doi.org/10.18653/V1/2021.EMNLP-MAIN.820.
  21. Vera Provatorova, Simone Tedeschi, Svitlana Vakulenko, Roberto Navigli, and Evangelos Kanoulas. Focusing on context is nice: Improving overshadowed entity disambiguation, 2022. https://arxiv.org/abs/2210.06164, URL: https://doi.org/10.48550/arXiv.2210.06164.
  22. Vera Provatorova, Svitlana Vakulenko, Evangelos Kanoulas, and Johannes M van Hulst. Named entity recognition and linking on historical newspapers: Uva.ilps i& rel at. In CEUR-WS, volume 2696, Thessaloniki, 2020. URL: https://ceur-ws.org/Vol-2696/paper_209.pdf.
  23. RKD. Archief Sybren Valkema. URL: https://rkd.nl/nl/projecten-en-publicaties/projecten/265-archief-sybren-valkema.
  24. Sybren Valkema and Klaas Laansma. Sybren Valkema. De Prom, Baarn, 1994. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact