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the process of analyz<strong>in</strong>g <strong>in</strong>dividual letters and the variability of letter<strong>in</strong>g schemes and of evaluat<strong>in</strong>g
their results.
Other advanced research <strong>in</strong> the imag<strong>in</strong>g of <strong>in</strong>scriptions has <strong>in</strong>vestigated the automatic classification of
Greek <strong>in</strong>scriptions, accord<strong>in</strong>g to the writer who carved them (Panagopoulos et al. 2008). One of the
biggest challenges, Panagopoulos et al. noted, <strong>in</strong> study<strong>in</strong>g <strong>in</strong>scriptions carved on stone is that they are
unsigned and undated, and have often been broken up and so are <strong>in</strong> various fragments. At the same
time, they proposed that identify<strong>in</strong>g a writer could be a crucial part of dat<strong>in</strong>g an <strong>in</strong>scription and sett<strong>in</strong>g
it <strong>in</strong> historical context. The major goals of their work were to objectively assign <strong>in</strong>scriptions to writers,
to assist <strong>in</strong> writer identification where archaeological <strong>in</strong>formation and analysis had yielded no results,
and to help resolve archaeological disputes regard<strong>in</strong>g the dat<strong>in</strong>g of events. In sum, they reported that
they hoped to “achieve writer identification employ<strong>in</strong>g only mathematical process<strong>in</strong>g and pattern
recognition methods applied to the letters carved <strong>in</strong> each <strong>in</strong>scription” (Panagopoulos et al. 2008).
One archaeologist worked with several computer scientists to evaluate the f<strong>in</strong>al methodology described
<strong>in</strong> the paper. They obta<strong>in</strong>ed images of 24 <strong>in</strong>scriptions, segmented the images, and extracted the
contours of <strong>in</strong>dividual letters. Us<strong>in</strong>g mathematical process<strong>in</strong>g, they computed “platonic” prototypes for
each alphabet symbol <strong>in</strong> each <strong>in</strong>scription. All <strong>in</strong>scriptions were then “compared pairwise by employ<strong>in</strong>g
these ideal representations and the <strong>in</strong>dividual letter realizations.” Panagopoulos et al. then used several
statistical techniques to reject the “hypothesis that two <strong>in</strong>scriptions are carved by the same writer” and
computed maximum-likelihood considerations <strong>in</strong> order to def<strong>in</strong>itively attribute <strong>in</strong>scriptions <strong>in</strong> their
collections to their <strong>in</strong>dividual writers. To evaluate their framework, they used it to automatically
attribute 24 <strong>in</strong>scriptions from Athens and successfully attributed these <strong>in</strong>scriptions to six different
identified “hands” and matched the expert op<strong>in</strong>ions of epigraphists. A particular strength of their
process, the authors concluded, was that it required no tra<strong>in</strong><strong>in</strong>g data, but they also hypothesized that a
greater mass of <strong>in</strong>scription data on which to test their system would help greatly improve their
accuracy rate.
Manuscript Studies
Any discussion of manuscripts quickly leads to an exam<strong>in</strong>ation of many challenges found across
classical discipl<strong>in</strong>es—challenges that <strong>in</strong>clude the creation of digital editions, the complications of
palaeographic studies, and how to design a digital collection of manuscripts that supports researchers
consider<strong>in</strong>g codicological, 381 historical, or philological questions. Manuscripts are one of the most
complicated and highly used artifacts across discipl<strong>in</strong>es. The data richness of manuscripts, accord<strong>in</strong>g to
Choudhury and St<strong>in</strong>son <strong>in</strong> their analysis of the commonalities between creat<strong>in</strong>g an <strong>in</strong>frastructure for a
manuscript digital library and for a massive dataset <strong>in</strong> physics, makes them an <strong>in</strong>tricate but important
source for humanities data:
Manuscripts, so evidently data-rich <strong>in</strong> the era <strong>in</strong> which they were created, today reta<strong>in</strong> their
former value and mean<strong>in</strong>g while they <strong>in</strong>spire a new generation of humanists to create new sets
of data. This <strong>in</strong>cludes the metadata needed to encode, organize, and understand the texts,
annotations, and the visual art embodied <strong>in</strong> the manuscripts. Not only does this demonstrate the
parallel need for data curation and preservation <strong>in</strong> the humanities and the sciences (for at the
381 Codicology has been def<strong>in</strong>ed as “the study of the physical structure of books, which, when used <strong>in</strong> conjunction with palaeography, reveals a great deal
about the date, place of orig<strong>in</strong>, and subsequent history of a particular codex. The term was first used <strong>in</strong> conjunction with list<strong>in</strong>g texts <strong>in</strong> catalogue form, but
later <strong>in</strong> the 20th century came to be associated primarily with the structural aspects of manuscript production, which had been studied <strong>in</strong> a coherent fashion
s<strong>in</strong>ce the late 19th century.” Timothy Hunter "Codicology." The Oxford Companion to Western Art. Ed. Hugh Brigstocke. Oxford University Press, 2001.
Oxford Reference Onl<strong>in</strong>e. Oxford University Press. Tufts University. 27 April 2010
http://www.oxfordreference.com/views/ENTRY.htmlsubview=Ma<strong>in</strong>&entry=t118.e581