Home > People & Projects > Pitt Rivers Luo Visual History

Project Details

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Project Name: 
Pitt Rivers Luo Visual History
Principal Investigator / Director: 
Gilbert Oteyo and Chris Morton
Oxford participants: 
Other Participants: 
not specified
  • Division: Academic Services
  • Unit: Pitt Rivers Museum
  • Sub-Unit: not specified
Start Date: 
not specified
End Date: 
not specified
Partner organizations (inside or outside Oxford): 
David Harris (freelance web development), National Museums of Kenya
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Subject Area: 
Librarianship, Information & Museum Studies
Project Description: 

The Pitt Rivers Luo Visual History is a database of around 350 historical Luo photographs from the collections of the Pitt Rivers Museum, University of Oxford, taken between 1902 and 1936. The website is the result of a collaborative project between the Pitt Rivers Museum and members of the Luo community of Nyanza Province, western Kenya, with the assistance and co-operation of National Museums of Kenya. All of the photographs and documentation seen here has also been deposited with Kisumu Museum under a memorandum of understanding, and printed copies have also been presented to the British Institute in Eastern Africa and the Jaramogi Oginga Odinga Museum and Mausoleum in Bondo. Besides making these collections available to the research community, this project resulted in a series of four local exhibitions in Nyanza in early 2007, centred upon locations where the original photographs had been taken. Exhibiting these images locally enabled further research with members of the community and descendants of those photographed. The website provides a number of ways in which to explore these photographs, such as by photographer, places or people mentioned in the documentation, or even by themes such as archaeology, landscape images, portraits, images of homesteads and cattle-keeping and the famous Luo funerary ceremony of Tero Buru.

ICT Methods: 
Data CaptureImage capture2d Scanning and photography
Textual Input
Data analysisSearching/LinkingContent-based image retrieval
- -Searching and querying
Data structuring and enhancementClassifying and linkingCataloguing and indexing
Image ProcessingImage enhancement
Last updated: 
25/06/2015 16:24:50
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