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Name of Collaboratory :

 

High Throughput Humanities e-Research (HiTHeR)

 
 

URL :

  http://www.kcl.ac.uk/iss/cerch/projects/completed/hither.html  
 

Collaboratory Status :

 
Completed   Start Date : 2008 End Date : 2009 Info Last Updated : Thu, Dec 2 2010 5:00pm PST
 
 

Primary Collaboratory Function :

  Community Data Systems  
 

Secondary Collaboratory Functions :

  Community Infrastructure Development  
 

Domain(s) :

  HUMANITIES >English and Literature >Literature, English  
 

Brief Description of the Collaboratory :

 

High Throughput Humanities e-Research (HiTHeR) was focused on created a digital system for managing the Nineteenth Century Serials Edition (NCSE) corpus. The NCSE contains around 430,000 articles that originally appeared in roughly 3,500 issues of six 19th Century periodicals.

The project investigated the use of grid technologies and high throughput computing to provide more intuitive ways of searching the NCSE’s large corpus. Specifically, the project set up a prototype campus grid and used it for carrying out text processing on this corpus. The project tied in with campus grid activities at King’s and the National Grid Service.

The website set up to carry out these investigations is being developed further as part of the Forging Restful Services for e-Humanities (FReSH) project at CeRch.

 
 

Access to Instruments :

   
 

Access to Information Resources :

   
 

Access to People as Resources :

   
 

Funding Agency or Sponsor :

 
JISC
 
 
 

Notes on Funding Agencies/Sponsors:

 
 
 
Organizations with Funded Participants:
 
Organization name:
Approx # of participants:
Description of organization's role(s):
King's College, London
   Centre for e-Research (CeRch)
   Centre for Computing in the Humanities (CCH)
 
TOTAL PARTICIPANTS:
 

Notes on Participants/Organizations:

   
     
 
 

Communications Technology Used :

   
 

Technical Capabilities :

   
  Key Articles :    
 

Project-reported performance data :

  Almost impossible to quantify, but:
General impression: it worked quite well
Random inspection / deeper going analysis of singular articles: very satisfactory
Unexpected results:
Discovery of article chains Discovery of mis-classified articles
 
 
         
    
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