A computational pipeline for crowdsourced transcriptions of Ancient Greek papyrus fragments

Alex C. Williams, John F. Wallin, Haoyu Yu, Marco Perale, Hyrum D. Carroll, Anne Francoise Lamblin, Lucy Fortson, Dirk Obbink, Chris J. Lintott, James H. Brusuelas

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

25 Scopus citations

Abstract

In the late nineteenth century, two excavators from the University of Oxford uncovered a vast trove of naturally deteriorated papyri, numbering over 500,000 fragments, from the city of Oxyrhynchus. With varying levels and forms of deterioration, the identification of a papyrus fragment can become a repetitive, long, and exhausting process for a professional papyrologist. The University of Oxford's Ancient Lives project aims to accelerate the identification process through citizen science (or crowdsourcing). In the Ancient Lives interface, volunteer users identify letters by clicking on a location in the image to designate the presence of a letter. To date, over 7 million letter identifications from users across the world have been recorded in the Ancient Lives database. In this paper, we present a computational pipeline for converting crowdsourced letter identifications made through the Ancient Lives interface into digital consensus transcriptions of papyrus fragments. We conclude by explaining the usefulness of the pipeline output in the context of additional computational projects that aim to further accelerate the identification process.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014
EditorsJimmy Lin, Jian Pei, Xiaohua Tony Hu, Wo Chang, Raghunath Nambiar, Charu Aggarwal, Nick Cercone, Vasant Honavar, Jun Huan, Bamshad Mobasher, Saumyadipta Pyne
Pages100-105
Number of pages6
ISBN (Electronic)9781479956654
DOIs
StatePublished - 2014
Event2nd IEEE International Conference on Big Data, IEEE Big Data 2014 - Washington, United States
Duration: Oct 27 2014Oct 30 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014

Conference

Conference2nd IEEE International Conference on Big Data, IEEE Big Data 2014
Country/TerritoryUnited States
CityWashington
Period10/27/1410/30/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Big data
  • Crowdsourcing
  • Human computation
  • Papyrus transcription

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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