1. The use of OCR in the digitisation of herbarium specimens Robyn E Drinkwater, Robert Cubey & Elspeth Haston

2. What is happening in digitisation?

4. … and these minimal data records are going to need data added to them.

5. Parse OCR text directly into the database fields Use OCR data to prepare the specimens for manual / semi automated data entry What are the options when using optical character recognition (OCR)?

6. We have had a digitisation project running to digitise all the specimens from SW Asia and the Middle East at RBGE. Minimal data had been captured originally* – Filing name – Geographical filing region – Barcode We have been routinely processing all our specimen images through ABBYY OCR software. * E Haston, R Cubey, DJ Harris (2011). Data concepts and their relevance for data capture in large scale digitisation of biological collections. International Journal of Humanities and Arts Computing 6 (1-2), 111-119.

7. Exploring the data…

8. We used the OCR output text to pull out over 7,000 specimen images and associated data records These were then prepared into batches: – some random – some sorted by collector and / or country Step One

9. A team of six digitisers at RBGE completed a series of trials They used two different protocols for data entry – complete records – partial records (including collector and geographical information but not habitat and description) In total 7,200 specimens were processed Step Two

10. Compared to unsorted, random specimens, those which were sorted based on data from the OCR output were quicker to digitise Of the methods tested here, the most efficient used a protocol based on partial data entry, working with specimens which had been filtered by Collector and Country Results…

11. The human factor…

12. Digitisation staff preferred working with sorted specimens They also preferred working with physical specimens rather than images The human factor…

13. This work is more easily applied than parsing data from the OCR output It can be used in conjunction with other tools later in the digitisation process since these other processes will almost certainly be more efficient with sorted batches of specimens Other tasks can also be built on top of this: eg condition assessment, QC, etc Some more thoughts…

14. It’s surprising what can be used to help filter specimens – the black art of search terms!

15. Acknowledgments The digitisation team at RBGE: Nicky Sharp, David Braidwood, Muhammad Ghazali, Lorna Glancy, Dorota Jaworska, Esther Nieto. The Andrew W Mellon Foundation Dr Antje Ahrends (RBGE) & Dr Chris Glaseby (BIOSS) for statistical advice