Digitization Projects Tech Con 2006
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The document summarizes the digitization projects and lessons learned from digitizing collections at the State Library of Pennsylvania. It discusses the hardware and software used, including scanners, Photoshop, and OCR software. It also covers what criteria are used to select items for digitization, challenges that arise like bureaucracy and storage, and considerations for creating metadata like using a data dictionary and dealing with variations in names and citations.
![Questions? Call or email one of us Bill Fee 717-783-7014 wfee@state.pa.us Kurt Bodling 717-783-5996 kbodling@state.pa.us Bill Nork 717-787-9128 [email_address]](https://image.slidesharecdn.com/digitizationprojectstechcon2006-1221241272389651-8/85/Digitization-Projects-Tech-Con-2006-44-320.jpg)
Digitization Projects Tech Con 2006
- 1. Digitization Projects at the State Library of Pennsylvania: Where the Past and Future Meet Bill Nork Head of Systems & Preservation William Fee Digital Collections Librarian Kurt Bodling Digital Resources Cataloger Pennsylvania Department of Education, State Library of Pennsylvania
- 2. www.statelibrary.state.pa.us/digital_projects Or Visit the State Library of PA Website www.statelibrary.state.pa.us Select Digital Projects of the State Library
- 3. Digitization things learned the hard way Or why do I drink so much coffee? By Bill Fee Try to plan things out as much as you can before starting a project No matter how much you plan, something will blow up in your face. Its often better to throw people at a problem than equipment (if they hit just right, this also counts as percussive maintenance) Loud, obnoxious and driving punk rock and techno really improve the workflow (though that could be just a personal preference)
- 4. Hardware & Software We run a Dell Optiplex GX260 with a 2.26 Ghz non-hyperthreaded processor. Alas, were a PC shop. Scanner-wise, we have a $25,000 Minolta PS 7000 overhead engine book scanner and an HP ScanJet 7400C thats up for replacement.
- 5. Hardware & Software- again Direct scans into Photoshop.油油 I can save the archival TIFF, then edit it and create the access JPEG right there.油 As a library you should be able to get an educational license, which is a heck of a lot cheaper.油 The program itself油 may seem more full featured than you need, but things like batch process when you're doing a whole directory of images with the same edits and sizing really save time.油 Get them to pay for classes, though- about 200 per but well worth it.
- 6. Still More Hardware & Software We use Omnipage for OCR.油 You'll save yourself a heck of a lot of correction time by doing a dual scan- 1 into Photoshop, one directly into the OCR program, whichever you use.油 Omnipage has about a 98 or 99 percent accuracy for anything but newspapers, but there are others just as good.油 Hit up ComputerShopper.com and read reviews. If I'm doing a web page, I use the Composer feature in Mozilla or Netscape. Ive been using these programs and essentially the same hardware since the bad old pre-standards Dark Ages of 5 years ago, and they seem to work.
- 7. What criteria do you use to have an item digitized? Must be PA related. Usually in such poor shape that it cannot circulate, or from the Rare Book Room, or ordered by the Director or Commissioner. Must have less than 5-10 holding libraries in FirstSearch (not counting us). Usually fits a theme- current is the VLaT project- Violence, Labor and Transportation = riots, train wrecks, mine accidents, etc.
- 8. Other problems you will find Bureaucracy Shipment File and folder nomenclature Poor scans and OCR Storage Personnel High-priority projects New software, new uses for software, new problem with software that only come up because its a new project.
- 9. Metadata Considerations Kurt A.T. Bodling Digital Resources Cataloger State Library of Pennsylvania
- 10. The Starting Place What is the digital object? Something newly created? Already cataloged? A collection? A single item? A selection from an item? Who is it for?
- 11. 油
- 12. 油
- 13. Ben Franklin solutions Easy call: siphon data from OPAC Tougher: dealing with chapters and single letters
- 14. 油
- 15. General solution to obit challenges Sampling and testing Hunting down exceptions Creating a data dictionary And, of course, going back later to make changes
- 16. Data Dictionary defined MARC : AACR2 :: Dublin Core : Data Dictionary
- 17. 油
- 18. 油
- 19. Creating the data dictionary Simple issues first: Steal data from the catalog Use boilerplate rights management statement Get repeated data into a template
- 20. Creating the data dictionary More difficult challenges Names of the deceased Citation to original source newspapers Omissions Enhancements Difficulties caused by original scrapbooking
- 21. Names of the deceased Not authority controlled Variations between two obit versions Variations within one obit Lacking first name
- 22. Name variations:
- 23. Anonymous child:
- 24. Names of the deceased Solutions: Enter only surname, but Enter all spellings that appear
- 25. Citations to original sources Visible on microfilm, but NOT in jpeg Easily recoverable
- 26. Citations to original sources Solution: Leave this information out of metadata
- 27. Omissions Blank pages Pages glued together Military unit information
- 29. Omissions Solutions: Record page numbers as they appear Note when pages dont appear Omit unit information
- 30. Enhancements Geographic info Occupational info Marital status And on and on and on.
- 31. 油
- 32. 油
- 33. Enhancements Solutions: Forego most enrichment Include former slave Include some terms like suicide and murder
- 34. Scrapbook difficulties Running on to second page Running on to 3 rd , 4 th , 5 th pages
- 36. Scrapbook difficulties Repeated obituaries
- 37. Scrapbook difficulties Label at bottom of page, obit on next
- 38. Text and title split:
- 39. Scrapbook difficulties Year-end cumulative death notice Articles that were not obits at all Volumes containing two years
- 41. Not an obit:
- 42. My Lessons Learned Metadata isnt (arent?) scary Patience and perseverance win out Small crew = quick decisions
- 43. What Did we Learn? More man-hours than we thought More staffing to complete task Decisions about how deep to go with metadata
- 44. Questions? Call or email one of us Bill Fee 717-783-7014 wfee@state.pa.us Kurt Bodling 717-783-5996 kbodling@state.pa.us Bill Nork 717-787-9128 [email_address]