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Quality driven workflow environment for 
digitisation of natural history specimens 
Tero Mononen, Riitta Tegelberg, Mira Sääskilahti, 
Markku A. Huttunen, Marko Tähtinen, Hannu Saarenmaa 
Features 
DigiWeb 
http://digitarium.fi/ 
Four main views: Monitoring of digitisation, 
browsing, transcribing and administration 
User access control manages visibility of views 
and permitted operations 
ISO 2859 standard based acceptance procedure 
for specimen data 
Support for multiple internal and external data 
sources 
Utilizes Java EE, JSF2, PrimeFaces, RDBMS, 
Darwin Core and file system 
Test project 
In total 168,500 herbarium specimens were imaged 
Transcribing started in 2013 
Training period was provided for personnel before 
access to production data 
Workflow defined a responsible party for every state of 
specimen 
The route in workflow depended on the difficulty of 
specimen and experience of transcriber 
In acceptance procedure 80 of 1,000 (batch) specimens 
were verified manually and ≥ 4 flawed specimens 
caused rejection of whole batch 
Results 
Performance and accuracy 
improved significantly after 
two months work 
Location was the main cause 
for rejection in quality check

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TDWG 2014: DigiWeb - Quality driven workflow environment for digitisation of natural history specimens

  • 1. Quality driven workflow environment for digitisation of natural history specimens Tero Mononen, Riitta Tegelberg, Mira Sääskilahti, Markku A. Huttunen, Marko Tähtinen, Hannu Saarenmaa Features DigiWeb http://digitarium.fi/ Four main views: Monitoring of digitisation, browsing, transcribing and administration User access control manages visibility of views and permitted operations ISO 2859 standard based acceptance procedure for specimen data Support for multiple internal and external data sources Utilizes Java EE, JSF2, PrimeFaces, RDBMS, Darwin Core and file system Test project In total 168,500 herbarium specimens were imaged Transcribing started in 2013 Training period was provided for personnel before access to production data Workflow defined a responsible party for every state of specimen The route in workflow depended on the difficulty of specimen and experience of transcriber In acceptance procedure 80 of 1,000 (batch) specimens were verified manually and ≥ 4 flawed specimens caused rejection of whole batch Results Performance and accuracy improved significantly after two months work Location was the main cause for rejection in quality check