Abstract. This paper describes a work-flow designed to populate a digital library of ancient Greek critical editions with highly accurate OCR scanned text. While the most recently available OCR engines are now able after suitable training to deal with the polytonic Greek fonts used in 19th and 20th century editions, further improvements can also be achieved with postprocessing. In particular, the progressive multiple alignment method applied to different OCR outputs based on the same images is discussed in this paper.

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We present here a method for automatically projecting structural information across translations, including canonical citation structure (such as chapters and sections), speaker information, quotations, markup for people and places, and any other element in TEI-compliant XML that delimits spans of text that are linguistically symmetrical in two languages. We evaluate this technique on two datasets, one containing perfectly transcribed texts and one containing errorful OCR, and achieve an accuracy rate of 88.2% projecting 13,023 XML tags from source documents to their transcribed translations, with an 83.6% accuracy rate when projecting to texts containing uncorrected OCR. This approach has the potential to allow a highly granular multilingual digital library to be bootstrapped by applying the knowledge contained in a small, heavily curated collection to a much larger but unstructured one.

The surviving corpora of Greek and Latin are relatively compact but the shift from books and written objects to digitized texts has already challenged students of these languages to move away from books as organizing metaphors and to ask, instead, what do you do with a billion, or even a trillion, words? We need a new culture of intellectual production in which student researchers and citizen scholars play a central role. And we need as a consequence to reorganize the education that we provide in the humanities, stressing participatory learning, and supporting a virtuous cycle where students contribute data as they learn and learn in order to contribute knowledge. We report on five strategies that we have implemented to further this virtuous cycle: (1) reading environments by which learners can work with languages that they have not studied, (2) feedback for those who choose to internalize knowledge about a particular language, (3) methods whereby those with knowledge of different languages can collaborate to develop interpretations and to produce new annotations, (4) dynamic reading lists that allow learners to assess and to document what they have mastered, and ( 5) general e-portfolios in which learners can track what they have accomplished and document what they have contributed and learned to the public or to particular groups.

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