This document describes a method for digitizing specimen label data using crowdsourced labor. Labels are scanned using OCR software to extract text. Volunteers then view the OCR output and images to identify fields like scientific names, dates, and locations. They assign values to these fields which are assembled into structured occurrence records. The records are exported in formats like Darwin Core and made available via web services. Volunteers earn tokens for their work that can be used to support science-related causes through an online store, creating a sustainable model where collections are digitized at low cost while benefiting volunteer contributors.

1. Developed by
LABEL PROCESSING METHOD SilverBiology
HELPINGSCIENCE.ORG Michael Giddens

2. GOAL (REPEAT 60+ MILLION TIMES)
From This To This
• StateProvince: Arkansas
• County: Bradley
• Genus: Botr ychium
• SpecificEpithet: biternatum
• Authorship: (Sav.) Under wood
• Collector: Sherri Leslie, Kaylon
Cornish
• CollectorNumber: 593
• DateCollected: 1984-09-23
• TRS: Sec. 3, T12S, R9W
Species Lookup: http://ecat-dev.gbif.org/usage/2650191

3. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

4. IDENTIFYING LABELS
Step 1 To This
 Sign In
 Request Image
 Click & Drag
 Click & Drag
 <Enter>
 Repeat
 Average Time: 300/hr
per person

5. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

6. EVERNOTE OCR PROCESSING
Sample JPG label
$5/1GB per month JSON output
~ label cost: $0.001

7. AFTER EVERNOTE

8. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

9. STEP 2) IDENTIFYING LABELS
What we capture. What we leave on the label.
• Scientific Information • Habitat Information
( Fa m i l y, G e n u s , S p e c i e s , S u b s p e c i e s , A u t h o r )
• Locality Description
• Collection Information
( N a m e , N u m b e r, D a t e ) • Collector Notes
• Geographical Information • Other
( C o u n t r y, S t a t e , C o u n t y, L o c a l i t y,
Lat/Lon, TRS)
• Determination Information
( D e t e r m i n e r, S c i e n t i f i c N a m e , D a t e
Determined)
• Extra Information
( A c c e s s i o n N u m b e r, Ty p e S t a t u s )

10. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

11. LEXICAL GROUPING
Internal Step
 Compare words to
OCR value and if
it is distinct assign
to lexical set.
 Send image to
data entry.

12. BULK VALIDATION
Internal Step
 Look at the value
that will be assigned
to the list of images
if any are not the
correct value move to
manual data entry
blacklist.
 Repeat
 Based on Lexical Groups

13. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

14. DATA ENTRY
Public Step
 Multiple Interfaces
 Dates
 Lat/Lng
 Names
 Scientific Names
 User receive virtual
tokens to use in the
store for every correct
word

15. DATA ENTRY VARIATIONS

16. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

17. FIELD VERIFICATION
Computer: Asplenium Frequency
Volunteer 2: Asplenium Asplenium: 2
Volunteer 3: Asplenlum Asplenlum: 1
Volunteer 4: Asplenium Asplenium: 3
Asplenium: 1
Points Earned: Volunteer 2 & 4

18. WORKFLOW
Identify Enter Accept
Lexical
Identify OCR Primary Values Value Assemble
Grouping &
Labels Labels DwC for for Each Label Data
Verification
Fields Fields Field

19. OCCURRENCE DATA
 Export Formats
 CSV
 Darwin Core Archive
 Other on request
 Filters
 By any combination of DarwinCore Fields
 Restful web services

20. SUSTAINABILIT Y
 HelpingScience depends on a symbiotic relationship between
collections providing specimen sheets and volunteers to per form data
entr y.
 Volunteers are given HS Tokens to be used in the HS Store in
exchange for their time.
 The store is a percentage of the cost per label that is given back to
the community.
The Store
 Fundraisers
 Small micro loans given to botany undergraduate students for research
 Sponsorships for students to attend scientific conferences
 K12 equipment funding for science departments
 Charitable Organizations
 Fund Small Herbaria Digitization

21. HELPINGSCIENCE.ORG
If you manage a collection and interested in testing or
processing labels please contact:
mikegiddens@silverbiology.com
www.SilverBiology.com