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“An alarmingly casual indifference to accuracy and authenticity.” What we know about digital surrogates
In a new article in Portal, Diana Kichuk examines the reliability and accuracy of digital text extracted from printed books in five digital libraries: the Internet Archive, Project Gutenberg, the HathiTrust, Google Books, and the Digital Public Library of America. She focuses particularly on the accuracy and utility of the digital text for reading in e-book formats and on the accuracy of metadata derived from extracted text.
- Kichuk, Diana. “Loose, Falling Characters and Sentences: The Persistence of the OCR Problem in Digital Repository E-Books.” Portal: Libraries and the Academy 15, no. 1 (2015): 59–91. doi:10.1353/pla.2015.0005.
This study, along with a couple of others cited below, are very relevant to the repeated calls by some within the Federal Depository Library Program to digitize and discard the historic FDLP paper collections. These studies, even though they do not focus on government publications, provide examples, data, and standards that should be critical to review before the depository community implements discarding policies that will have irreversible effects.
Kichuk’s article is well worth reading in its entirety as she identifies many problems with digital text created during digitization of paper books by OCR (Optical Character Recognition) technologies, and she gives specific examples. The two most important problems that she highlights are that digitized texts often fail to accurately represent the original, and that the metadata that is automatically created from such text is too often woefully inaccurate. These problems have real effects on libraries and library users. Readers will find it difficult to accurately identify and even find the books they are looking for in digital libraries and libraries will find it difficult to confidently attribute authenticity and provenance to digitized books.
Kichuk says that digitized text versions of print books are often unrecognizable as surrogates for the print book and it may be “misleading at best” to refer to them even as “equivalent” to the original. Although she only examined a small number of e-books (approximately seventy-five), she found “abundant evidence” of OCR problems that suggest to her the likelihood of widespread and endemic problems.
A 2012 report by the HathiTrust Research Center reinforces Kichuk’s findings. That study found that 84.9 percent of the volumes it examined had one or more OCR errors, 11% of the pages had one or more errors, and the average number of errors per volume was 156 (HathiTrust, Update on February 2012 Activities March 9, 2012).
Most of the examples we have of current-generation digitization projects, particularly mass-digitization projects, provide access to digital “page images” (essentially pictures of pages) of books in addition to OCR’d digital text. So, to get a more complete picture of the state of digitization it is instructive to compare Kichuk’s study of OCR’d text to a study by Paul Conway of page images in the HathiTrust.
- Conway, Paul. “Preserving Imperfection: Assessing the Incidence of Digital Imaging Error in HathiTrust,” 2013. .
Fully one-quarter of the 1000 volumes examined by Conway contained at least one page image whose content was “unreadable.” Only 64.9% of the volumes examined were considered accurate and complete enough to be considered “reliably intelligible surrogates.” Presumably, that means more than 35% of the volumes examined were not reliable surrogates.
Conway’s study reinforces the findings of the Center for Research Libraries when it certified HathiTrust as a Trusted Digital Repository in 2011. (Full disclosure: I was part of the team that audited HT.) CRL said explicitly that, although some libraries will want to discard print copies of books that are in HT, “the quality assurance measures for HathiTrust digital content do not yet support this goal.”
Currently, and despite significant efforts to identify and correct systemic problems in digitization, HathiTrust only attests to the integrity of the transferred file, and not to the completeness of the original digitization effort. This may impact institutions’ workflow for print archiving and divestiture. (Certification Report on the HathiTrust Digital Repository).
Together, these reports provide some solid (if preliminary) data which should help libraries make informed decisions. Specifically, all these studies show that it would be risky to use digitized copies of FDLP historic collections as reliable surrogates for the original paper copies. That means it would be risky to discard original paper copies of documents simply because they had been digitized.
Although Conway suggests, as others have, that libraries (and users) may have to accept incomplete, inaccurate page images as a “new norm” and accept that they are not faithful copies, he also realizes that “questions remain about the advisability of withdrawing from libraries the hard-copy original volumes that are the sources of the surrogates.”
Kichuk goes further in her conclusions. She wisely envisions that the “uncorrected, often unreadable, raw OCR text” that most mass-digitization projects produce today, will be inadequate for future, more sophisticated uses. She looks specifically to a future when users will want and expect ebooks created from digitized text. She warns that current digitization standards, coupled with insufficient funding, are not creating text that is accurate or complete enough to meet the needs of users in the near future. And she recognizes that librarians are not stepping up to correct this situation. She describes “an alarmingly casual indifference to accuracy and authenticity” of OCR’d text and says that this “willful blindness” to the OCR problem is suppressing any sense of urgency to remedy the problem.
She concludes from her small sample that there should be a more systematic review by the digital repository community prior to the development of a new digitized e-book standard, especially for metadata and text file formats.
I agree with Kichuk and Conway and CRL that more work needs to be done before libraries discard their paper collections. Librarians and their communities need to have a better understanding of the quality of page images and digitized text that digitization projects produce. With that in mind, James R. Jacobs and I addressed this very problem in 2013 and suggested a new standard for the quality of page images — which we call the “digital Surrogate Seal of Approval” (DSSOA)) in 2013:
- Jacobs, James A., and James R. Jacobs. “The Digital-Surrogate Seal of Approval: A Consumer-Oriented Standard.” D-Lib Magazine 19, no. 3/4 (March 2013). doi:10.1045/march2013-jacobs.
Libraries that are concerned about their future and their role in the information ecosystem should look to the future needs of users when evaluating digitization projects.
FDLP libraries have a special obligation to the country to preserve the historic collections in their charge. It would be irresponsible to discard the complete, original record of our democracy and preserve only an incomplete, inaccurate record it.
The Update on February 2012 Activities of the HathiTrust reports on research being done by the HathiTrust Research Center (HTRC) to quantify occurrences of Optical Character Recognition (OCR) errors in the HathiTrust corpus. OCR is the technology that converts a scanned image to text that can be searched and analyzed. Members of the HTRC examined 256,000 non-Google digitized volumes from HathiTrust using a clever algorithm that compared OCR text to a dictionary of known words. Using a supercomputer and a set of rules that were verified by a human expert, they found that 84.9 percent of the volumes examined (217,754 of the 256,416) had one or more OCR errors and 11% of the pages (7,745,034 of the 69,297,000) had one or more errors. The average number of errors per volume was 156.
As we at FGI have argued here before, we believe that it essential to take into account OCR accuracy and error rates when digitizing paper collections. This is particularly important when digitizing books that contain statistical tables since it is harder to use current OCR technologies to accurately convert image scans to numbers than it is to convert scans to text. It is also harder to evaluate the accuracy of such conversions; you can’t use a dictionary of known statistics the way you can use a dictionary of known words. (The HTRC study did not, apparently, examine accuracy of statistical table conversions.) Because of the large volume of such information in government publications, this is a very important issue as we collectively try to digitize our paper collections, evaluate their accuracy and usability, and determine how many paper copies we need to keep after digitization (see Achieving a collaborative FDLP future).