David Bamman, and
ePhilology: When the Books Talk to Their Readers1
Writing, Phaedrus, has this strange quality, and is very like painting; for the creatures of painting stand like living beings,
but if one asks them a question, they preserve a solemn silence. And so it is with written words; you might think they spoke
as if they had intelligence, but if you question them, wishing to know about their sayings, they always say only one and the
(Plato, Phaedrus 275d)
This chapter suggests directions in which an ePhilology may evolve. Philology here implies that language and literature are
the objects of study but assumes that language and literature must draw upon the full cultural context and thus sees in philological
analysis a starting point for the scientia totius antiquitatis — the systematic study of all ancient culture. The term ePhilology implicitly states that, while our strategic goal may remain
the scientia totius antiquitatis, the practices whereby we pursue this strategic goal must evolve into something qualitatively different from the practices
of the past.
Digital technology is hardly new in classics: there are full professors today who have always searched large bodies of Greek
and Latin, composed their ideas in an electronic form, found secondary sources online and opportunistically exploited whatever
digital tools served their purposes.2 Nevertheless, the inertia of prior practice has preserved intact the forms that evolved to exploit the strengths and minimize
the weaknesses of print culture: we create documents that slavishly mimic their print predecessors; we send these documents
to the same kinds of journals and publishers;3 our reference works and editions have already begun to drift out of date before they are published and stagnate thereafter;
even when new, our publications are static and cannot adapt themselves to the needs of their varying users; while a growing,
global audience could now find the results of our work, we embed our ideas in specialized language and behind subscription
barriers which perpetuate into the twenty-first century the miniscule audiences of the twentieth.4
This chapter makes two fundamental arguments. First, it assumes that the first generation of digital technology has only laid
the groundwork for substantive change in classics and the humanities. Second, it advances arguments about what form an optimal
digital future should assume. While Greek and Latin provide the focus for this chapter, the arguments apply in various ways
to many areas within the humanities.
At least six features distinguish emerging digital resources: (1) they can be delivered to any point on the earth and at any
time; (2) they can be fundamentally hypertextual, supporting comprehensive links between assertions and their evidence; (3)
they dynamically recombine small, well-defined units of information to serve particular people at particular times; (4) they
learn on their own and apply as many automated processes as possible, not only automatic indexing but morphological and syntactic
analysis, named entity recognition, knowledge extraction, machine translation, etc., with changes in automatically generated
results tracked over time; (5) they learn from their human readers and can make effective use of contributions, explicit and
implicit, from a range of users in real time; (6) they automatically adapt themselves to the general background and current
purposes of their users.
Print culture gave us expensive distribution by which we could send static documents to a few thousand restricted locations.
If we can deliver information to any point on the earth and we can tailor that information to the varying backgrounds and
immediate purposes of many people, we can thus address audiences far beyond the physical and, indeed, cultural limitations
which communication — oral and print —has imposed.
In the Phaedrus, Plato's Socrates, a fictive rendering of a historical character scratched into life by pen and preserved as a pattern of
ink, critiques writing — and thus the very medium in which he exerts a living presence to this day. A generation ago, Derrida famously expanded upon
the observation that writing is not so much a cure as a poison for memory5— in a look-up culture not only do our memories decay but we lose in some measure that instant and deep recognition which integrated
knowledge alone can spark. The critique in the Phaedrus is profound and addresses all technologies which represent information abstracted not only from the brain but also from the
personal context in which much learning occurs. Plato's arguments have been echoed ever since, consciously or not — many of us in the first generation of a television society heard similar criticisms from our parents and, in turn, directed
these to our net-oriented children.6
The quote that begins this essay, however, directs a criticism which is just as trenchant but has attracted less attention.
All products of information technology —paintings and poems, novels and newspapers, movies and music — have been static since our ancestors first scratched diagrams in the dirt or pressed visions of their world on the walls
of caves. Other human hands could add or destroy, but the products of our hands could do nothing but decay, prey to the scorching
sun, the worm, or the slow fires of acid within. We can direct our questions to the written word or to the most lifelike painting,
but we can expect only silence.
Now, however, we have created cultural products that can respond, systems that can change and adapt themselves to our needs.
Millions of people around the world will, on the day that I compose these words, seek directions from a mapping service. Natural
language, mathematical formulae, and visual representations of space will interact to generate tailored itineraries, with
estimates of time and customizable maps illustrating the journey from one point to another, in some cases speaking their directions
in an expanding suite of languages. We should not confuse the humble and well-defined goals of such tools with their significance
in the evolution of humanity and indeed life.
The great question that we face is not what we can do but what we want to accomplish. The tools at our disposal today, primitive
as they may appear in the future, are already adequate to create a dynamic space for intellectual life as different from what
precedes it as oral culture differs from a world of writing. At one level, little will change — the Homeric epics, products of an oral culture ironically preserved in writing, are arguably as successful as cultural products
as anything that followed: the ceiling of human creativity has not changed in three thousand years of increasingly sophisticated
information technology — an observation that we should consider as we fret over the codex and print.7
Nevertheless, we can now plan for a world where ideas cross from language to language and from culture to culture with a speed
and authenticity far beyond what we have ever experienced. Consider curious minds in Beijing or Damascus a generation from
now who encounter something that sparks their interest in the Greco-Roman world. It could be a film or a popular novel translated
into Chinese or Arabic or a game that carries them through a virtual space. It could even be something in their formal education
which, as occasionally happens, fires their imagination. The internet as we have it has already increased the chances for
such encounters and provided unprecedented opportunities for Beijing and Damascus to learn about ancient Greece and Rome or
We can, however, do more. The intellectually alive mind asks about a Greek author, perhaps a widely translated one (such as
Homer) or perhaps not. Background information and the text itself are translated into the Chinese or Arabic. The inquirer
has developed a profile, not unlike her medical history, which can record the classes she has taken, the books she has read,
the movies she has seen, the games she has played, and the questions that she has posed.8 The personal reading agent can compare this profile, eagerly developed and shared only in part and under strict conditions,
against the cultural referents implicit in the author or text of interest, then produce not only translations but personalized
briefing materials — maps, timelines, diagrams, simulations, glossary entries — to help that reader contextualize what she has encountered. As the reader begins to ask questions, the system refines its
initial hypotheses, quickly adapting itself to her needs.9 As the system changes, it inspires new kinds of inquiry in the reader, creating a feedback loop that encourages their conversation
to evolve. Far from the static and one-sided interaction of Plato's complaint, this is the definition of dialectic.
As this chapter will suggest, we already possess the technology to build a system of this type that will be effective in many
cases: the professional classicist moving into early modern Latin or even tracking developments in his or her own field, with
text mining identifying trends in the secondary literature or phenomena in the source texts.10
The question that we face is much deeper than the challenge of producing more or, preferably, better articles and monographs.
We must more generally ask what kind of space we wish to produce in which to explore the linguistic record of humanity —whether we are contemplating the Odyssey, administrative records from Sumer, or tracing mathematical thought through Greek and Arabic sources. More important perhaps
than the question of what we can do may be the opportunity to redefine who can do what — to open up intellectual life more broadly than ever before and to create a fertile soil in which humanity can cultivate the
life of the mind with greater vigor and joy.
The systematic application of computing technology to classical languages began in 1968, when David Packard had toiled with
primitive computing in the basement of Harvard's Science Center to produce a full concordance to Livy. The resulting massive
print volumes were both a fundamental new tool and a staple at Harvard University Press remainder sales of the 1970s, illustrating
both the potential of even simple electronic tools and the limitations of the codex. Three fundamental developments quickly
First, the Thesaurus Linguae Graecae (TLG),11 founded in 1972, began developing what would be called a digital library of classical Greek literature. A third of a century
later, the TLG has completed its initial goal of digitizing all published Greek literature up through ad 600 and has extended its coverage through the Byzantine period and beyond.12 The TLG thus provided the first digital well-curated collection of digital resources in classics.
Second, David Packard began in the 1970s to develop a system not only to work with collections such as the TLG but to provide
the first computerized typesetting and word processing for Greek.13 At the Boston APA convention of 1979, for example, Packard could show a working Ibycus computer system. Based on a Hewlett-Packard
minicomputer, the Ibycus included a unique operating system designed for classics. The Ibycus was, by the standards of the
early twenty-first century, astonishingly expensive — it cost tens of thousands of dollars — but it provided scholars with services they needed not only to exploit the TLG but to write and publish. Its contributions
were so important that more than a dozen departments raised the necessary capital.
Third, the TLG and Ibycus system were the products of two distinct organizations, thus promoting a separation of data from
service providers and opening the way for a range of entrepreneurs to create additional services and solutions.14 The TLG website lists more than a dozen packages that were developed to work with the CD ROM texts.
A generation later, classicists still depend upon texts and services designed in the 1970s. Figure 2.1 illustrates the results from a sample search of the TLG in May 2006 as suggested on the TLG website. The system reflects
decades of investment, both from subscriptions and from grants (e.g., a $235,000 grant in 2000 from the National Endowment for the Humanities that provided partial support for "restructuring of data and development of an online search and retrieval system for the Thesaurus Linguae Graecae."15) The resulting in-house system provides a fast, reliable service on which Hellenists depend, especially since the TLG no
longer updates its CD ROM and thus does not generally distribute source texts published after the February 2000 TLG E Disk.16
It would be hard to overstate the importance of searchable text corpora. Classicists are also fortunate to have access to
the Packard Humanities Institute CD ROM for Latin literature, as well as proprietary commercial databases such as the Biblioteca
Teubneriana Latina.17 Classicists have become accustomed to scanning wide swathes of Greek and Latin literature, with full professors today who
have never known a world without searchable texts. Many take for granted this core infrastructure and, when asked, admit that
these tools have had far more impact upon the questions that they ask and the research that they conduct than they readily
articulate. An analysis of primary source citations in the classics journals of JSTOR would give us a better appreciation
of the impact which these collections have had upon published scholarship.
Figure 2.1 TLG Search, May 17, 2006.
In the past thirty years more texts have been added but the essential services and underlying data model visible to the classical
community have not changed. The TLG, as it appeared in May 2006, is selected for analysis because it has successfully served,
and continues to serve, the field and provides a standard of excellence, in terms of continuity and quality of service, but
the analysis offered below applies to many efforts in classics and the humanities. The goal is not to diminish the importance
of what TLG and projects like it have contributed but, by describing the state of the art as it existed when this chapter
was written, to suggest future movements for classics and the humanities.
• String based searching: As this chapter is being written, users do not search for a lexeme (e.g., APODEIKNUMI) but for strings with which to find
inflected forms.18 This reduces precision (the string above would, for example, locate not only forms of the verb APODEIKNUMI but the noun APODECIS)
and recall (to locate all forms of the verb one would need to search for other strings, e.g., APEDEC, APODEIKN, APODEIC, APODEXQ,
etc.) Users need to find many other patterns and we need research and development on a range of searches.19 Lemmatized searches allow users to query a dictionary entry and identify all known inflected forms. Collocational analysis
allows users to find words that co-occur with unusual frequency and thus to uncover idiomatic expressions.20
Users also need to be able to locate syntactic patterns: e.g., what subjects and objects does a particular verb take? How often does the verb actually take the dative in a given corpus? What adjectives modify particular nouns? They need to search for people and places, identifying not only all Alexanders and Alexandrias but also be able to locate
references to the particular Alexander and Alexandria in which they are interested. They should be able to find basic propositional
patterns: e.g., at what locations does person X appear within the corpus?21 They should be able to apply intelligent clustering, automatic summarization, and text mining to searches that produce thousands
of results.22 They should be able to search for secondary sources that talk about directly or are generally relevant to any given passage.
• Texts are encoded as page surrogates: Beta code markup tags the speakers in the Euripides search results pictured above. In the Thucydides and Plutarch results,
the electronic text faithfully reproduces the line-breaks (including hyphenization) of the print original. Users cannot exploit
semantic markup (e.g., search and compare results from the language of Helen and Menelaus in the Helena of Euripides, separate results from spoken vs. narrative text in Thucydides). Even the section breaks are only approximately
encoded, with section breaks, for example, simply inserted at the start of the line rather than in their proper position.
It is not difficult to convert the page layout Beta encoding of the TLG into TEI-compliant SGML or XML,24 but fuller conversion requires substantial editing with enough human interpretation of the meaning implicit in the page layout
for a true XML version to appear as a new edition in its own right. The cost of analyzing and formatting a complex document
(such as a play) is comparable to the cost of double-keyed professional data entry.25
• Texts represent only a single, isolated edition: After consulting with the scholarly community, the TLG chose to encode only the consolidated text, leaving aside variants
and providing only a single edition of each author.26 At the time, the added cost and complexity were determining factors. This initially reluctant measure has become policy:
the TLG suppressed older editions, removing them from circulation and replacing them completely.27 Rather than letting users search both the Murray (which was on the D Disk) and the Diggle edition (which took its place on
the E Disk), users received just the one, more recent edition and (to use the TLG's own language) "suppressed" the older editions.28
• Limited interoperability: The TLG does build in some measure on third party efforts: the TLG can, for example, add links to the open access morphological
and lexicographic data at the Perseus Digital Library but there are no clear methods whereby third party systems can interact
with the TLG. Even sites that erect subscription barriers around their data do not have to be data silos. The TLG Canon could
be distributed, at least in part, via the Open Archives Initiative (OAI), a low-barrier approach well suited to distributing
cataloguing data.29 This would allow pointers to TLG texts to appear in library catalogues and for third party searching and text mining to add
value to the base data. At a more advanced level, even if the TLG does not choose to distribute its newer texts, it could
make search results available via an application programming interface (API) so that subscribing third parties could efficiently
analyze the results of searches and/or create customized front ends. The emerging Classical Texts Services protocol30 would provide a consistent method whereby systems could extract labeled chunks of text — a crucial function as dynamically generated documents emerge.
• Texts cannot be readily repurposed or circulate freely: Publishers assert copyright to the editions which they publish. The legality of this claim is by no means clear,31 and publisher claims represent aspiration rather than settled law — Norton went so far as to claim copyright to the through line numbers in their published facsimile of the First Folio (Hinman 1968) — in fact, a computer program will generate the through line numbers by mechanically counting lines and thus no recognizable
"original expression" is in play. Publishers have, however, traditionally charged permission fees for materials that were in the public domain
and an exploration of rights and practices would provoke interesting lines of inquiry.32 The threat of legal action, however frivolous, has exercised a chilling effect upon scholarship. The publishing institutions
that exist to facilitate the exchange of ideas thus choke the circulation of primary materials, constrain the fundamental
moral right of academic authors to reach the broadest possible audience, and restrict scholarly activity. With no new TLG
CD ROMs, an emphasis on a single propriety site, and no interoperability (not even an OAI harvestable version of the TLG Canon),
Hellenic studies have, if anything, taken a step backwards.
The limitations described above have been acceptable because they support the practices of print culture. Textual corpora
such as the TLG, whether on the web or on CD ROM, are immense, dynamic, flexible concordances. They thus support traditional
work but also provide no incentive for innovative forms of publication. The monolithic website isolates classicists from the
electronic infrastructure which supports them. If our goal is to produce more and better researched articles and monographs
— if we think that the answer to the crisis in academic monographs is to produce more content — then the status quo will serve us well.34
The Future in the Present
At this point, we return to the six features that, at least in part, distinguish digital from print publication. While work
remains at an early stage of development, progress is being made in all six areas. The following section illustrates these
points primarily with work done associated with Perseus for classics, but Perseus and the field of classics are only components
of a much larger process.35
Library subscription budgets shield many scholars — especially those at the most prestigious institutions — from the economic realities with which libraries struggle. Many — probably most — do not realize that the scholarly resources — much of it in the public domain — on which they daily rely are available only through expensive subscriptions. Various open access movements have attacked
this problem — rarely with support, not infrequently with scorn, from academics: Project Gutenberg began in 1971 (one year before the TLG),
hosts a library of 18,000 public domain books and downloads two million of these each month.36 More recently, Google Library and the Open Content Alliance (OCA) have set out to digitize the entire published record of
humanity. Each pursues contrasting rights regimes: Google retains its collection for its proprietary use, while the OCA is
building an open source collection: Yahoo and Microsoft are both backing OCA, with each planning to provide its own set of
unique services to the shared content. Both Google Library and the OCA are, however, open access — the business models of Google, Yahoo, and Microsoft all depend upon maximizing their audiences.37 Open access seems to them to be a better engine for revenue generation than subscription models.38
Within classics, the Latin Library dramatized the hunger for open-source primary materials. Frustrated by proprietary text
corpora, members of the community, most from outside of academia, have spontaneously digitized almost all classical Latin,
and a growing body of post-classical Latin literature and made it freely accessible at a single site.39 It is easy to criticize this work: original scholarship resides along with texts bearing the unnerving label "from an unidentified edition," while other texts combine multiple editions without substantive documentation.40 The site reflects a widespread and heart-felt desire to assemble a critical mass of freely accessible Latin texts. While
professional scholars can criticize some of the texts, we should also ask ourselves why the community felt it necessary to
do so much work to establish such a basic service. Were the publications that we composed with proprietary databases a greater
contribution to intellectual life than a universally accessible library of primary texts?
From the beginning of its web presence in 1995, Perseus provided open access to all of its holdings not otherwise restricted
by third party rights.41 More recently, members of the community — especially the rising generation of classicists — have argued forcefully that all core materials should be available under an open-source license, allowing third parties to
repurpose what we have begun. We have thus moved beyond open access and to open source for all materials to which we have
rights. We chose a Creative Commons attribution/share-alike/non-commercial license.42 Third parties may thus freely create new resources based on what we provide but they must make their additions available
under the same terms and they cannot restrict access to these resources behind a subscription barrier. The non-commercial
license does not exclude advertising-based revenue and we hope that internet services such as Google, Yahoo, and Microsoft
will load everything that we produce into their collections.
Since spring 2005, we have provided a web service that exposes well-formed chunks of our data to third parties. In March 2006,
we have made available under a Creative Commons license the TEI-compliant XML files for the Greek and Latin source texts that
we have created that were based upon public domain editions: c. 13,000,000 words of text. While this collection is much smaller
than the 76,000,000 words on the 2000 TLG E Disk or the 91,000,000 words on the spring 2006 TLG website, it does already contain
most of classical Greek and many classical Latin source texts. All of our unencumbered lexica, encyclopedias, commentaries,
and other reference materials will follow suit and be released under the same license. Likewise, all components of the new
digital library system that underlies Perseus are being written for open source distribution and will, we hope, be integrated
into the next generation of digital library systems.
As with access, hypertextual documents depend upon policy — even web links, primitive though they may be, provide a starting point. Classicist Christopher Blackwell has produced what
may be the best example of a publication that bridges the gap between traditional print and densely hypertextual web publication.
He produced an electronic publication as his tenure book, a website that surveys Athenian democracy.43 Figure 2.2 illustrates a snapshot of this site. The site includes not only PDF visualizations of the text optimized for print but also
HTML representations of the same documents. The HTML documents contain a dense set of primary source citations that are filtered
out of the print-oriented PDF publications. Blackwell has striven to provide the primary source evidence behind every significant
assertion. The secondary scholarship on this subject has grown so tangled that many publications simply cite other secondary
scholarship, leaving readers to dig through multiple sources before they can assess the underlying evidence. Blackwell's publication
assumes the presence of a stable, comprehensive digital library to make the citations actionable links.
Figure 2.2 Hypertextual writing from Christopher Blackwell's Demos, which illustrates a genuine step beyond print monographs.
Hypertextual writing builds on ubiquitous access to source materials. We can create hypertextual documents with links to subscription-based
resources, but in so doing we implicitly define an audience of academics and a handful of committed non-professionals with
access to good libraries. Hypertextual writing hidden from the outside world behind subscription barriers cannot, of course,
reach beyond academic elites. Dense hypertextual links that are in open-access publications but that point to academic subscription-based
sources have no more impact on society as a whole than citations to print-only resources. Only open access publications with
links to open-access sources can increase the transparency of what we in the humanities do and engage a broader audience in
the intellectual discourse that we pursue.44
Aside from the content, Blackwell's work demonstrates the potential of the form and exhibits a scholarly leadership badly
needed within the humanities. Had he worked with a conventional academic publisher he might have earned greater conventional
prestige, but he would have reached a smaller audience and would probably not have had the freedom to create expository texts
so well adapted to the digital environment.
Fine-grained, repurposable digital objects
We need compound documents, dynamically generated to serve particular users at particular times, that draw upon materials
from a range of sources to create a new, unified whole.45 Such documents have two requirements:
• Rights agreements that provide access to source objects and their constituent parts (e.g., TEI XML, the measurements underlying a 3D model) rather than their derivatives (e.g., HTML, QuickTime VR). This reflects
a simple, but profound, commitment that differs from the rights regimes that predominate in the web.
• Well-structured source objects: Access to the digital text of a dictionary does us little good if the text does not mark the headwords and the beginnings
and the senses and other components of individual articles.46 Most SGML/XML documents available online have very simple structures that do not capture crucial data (e.g., the entries
in the book index, which allow us to draw on human, rather than machine, decisions as to whether a particular Salamis is part
of Athens or Cyprus).47
Figure 2.3 illustrates an entry from the Liddell Scott Jones Greek English Lexicon (LSJ 9)48 Notice that the mention of "Pi. Pae." has not been expanded to a textual form but has been linked instead to an authority list (in this case, the numeration of
the TLG Canon49) unambiguously stating that "Pi. Pae." denotes Pindar's Paean odes. Such links are fundamental as collections grow larger and increasingly ambiguous. The beginnings and ends, not only of the
article as a whole but of each sense within it, are clearly marked and each has a unique identifier with which other documents
can cite it.
Third parties can dynamically extract well-formed fragments of XML from the Perseus Digital Library, including canonical chunks
of source texts, articles from various reference works, as well as the entire contents or individual senses from lexica. Figure 2.4 shows the same article as it appears in <http://www.dendrea.org/>, a third party site separate from the Perseus source collection: because it has access to the XML source, this site has
been able to generate services (such as a browser for etymologically related terms, synonyms and antonyms) not available at
Documents that learn from each other
The artificial intelligence pioneer Marvin Minsky suggested that the time would come when no one will imagine that the books
in a library did not talk with one another. While Minsky may have envisioned very powerful artificial intelligence spawning
conversations between books far beyond what is currently possible, our books are already beginning to converse in simple but
substantive ways.50 Put another way, so much material is already online that only machines can scan more than a tiny fraction of what is available.
Smart books are already beginning to appear to provide knowledge-intensive services and offer up more information about themselves
than any reader might have thought to ask.
Figure 2.3 XML entry from LSJ 9 on the Perseus website.
Figure 2.4 LSJ entry from Dendrea website.
Figures 2.5, 2.6, 2.7, and 2.8 illustrate four dynamically generated views based on the interaction of different books within the Perseus digital collection.
Figure 2.5 is a "basic report" from the Perseus website that lists various translations, editions, commentaries, and other resources about a particular
passage of classical Greek — Thucydides' History of the Peloponnesian War, Book 1, chapter 86. While it resembles the page of a book, it reflects the fact that many books have been analyzed and relevant
sections extracted to create a dynamic view that would be not feasible in print. Different works represent Thucydides as "Th.," "Thuc.," "T.," "Thucyd.," etc., the history as "Hist.," "H.," "Pel. War," etc., and the citation as "I, 86," "I.86," "1,86," "1.86." All of these representations are mapped onto a single canonical reference around which we can then cluster a range of information.
When the user calls up one translation, the translation calls out to the library for other translations, Greek editions, commentaries,
lexica, grammars, and other reference works which cite words in this passage. The text in focus thus interacts with a range
of other related resources, which align themselves in real time, ready to provide background information or to become themselves
the focus of attention.
Figure 2.5 Basic report: A user has called up a translation of Thucydides, History of the Peloponnesian War, Book 1, chapter 86.
Figure 2.6 Parallel text analysis: word clusters associated with uses of the Greek word arche in Thucydides' History of the Peloponnesian War (c. 150,000 words) and five English translations. Translation equivalents are underlined.
Figure 2.6 displays the word clusters associated with uses of the Greek word arche in Thucydides' History of the Peloponnesian War (c. 150,000 words) and five English translations. By comparing the English translations with the source text, the automatic
process identified clusters of meaning associated with various Greek words — in effect, creating a rough English/Greek lexicon and semantic network. The clusters capture the senses "empire," "government," "political office," and "beginning." The cluster headed "ancient" (marked in bold) captures a distinct word that happens to share the stem arch. Such parallel text analysis can update its results as new translations and source texts appear within the system, providing
dynamic conclusions based on interaction of books within the digital library.
Likewise, Figure 2.7 shows the results of automatic named entity identification. In this case, a translation of Thucydides compares its vocabulary
to authority lists such as encyclopedias and gazetteers to determine possible names and then uses the context in other books
to resolve ambiguous references in actual text51(e.g., does "Salamis" designate the island near Athens, a place in Cyprus or some other location?).
Figure 2.7 Named entity tagging: an XML fragment of Thucydides with all named entities automatically extracted and disambiguated.
Figure 2.8 A prototype of a basic report of Tacitus' Annales where users have the option to see automatically generated syntactic parses of the sentences. Users can contribute to the
system by correcting the automatic parse (e.g., Romam should not be in apposition to Vrbem) and transforming the partial parse into a complete one (here, by assigning tags to Vrbem and habuere).
Figure 2.8 shows the results of automatic syntactic parsing. Here a parser assigns tags to words by comparing the current text to other
texts that have been syntactically analyzed by hand. By communicating with other texts in this way, the parser can determine
the likelihood that a given morphological sequence (e.g., accusative noun, preposition, ablative noun) has a given syntactic
parse. In the prototype shown in the figure, only tags with a reasonably high probability are assigned (allowing the system
to have higher precision at the expense of greater coverage). If errors arise (as shown at the bottom of the figure, where
Romam should not modify Vrbem as an apposition), users can correct the syntactic dependencies to improve the overall system, providing a valuable feedback
mechanism whereby both the user and the text can productively learn from each other.
The figures above thus provide initial examples of books interacting with each other to create new forms of publication. These
examples point the way toward increasingly intelligent collections which become more powerful and sophisticated as their size
and internal structure improve — the more books communicate with each other, the more information about themselves they can provide.
Documents that learn from their audiences
Documents can learn from each other and drive automated processes to identify people and places in full text, analyze the
contents of collections to provide integrated reports drawing on multiple information sources and perform similar tasks to
apply existing classification or mine new potential knowledge.52 But even when such processes address questions with discrete, decidable answers, users will want to refine the results and
these user-contributed refinements are important not only for other users but for improving the quality of subsequent automated
analysis.53 Thus, an automated system may incorrectly identify "Washington" in one passage as Washing-ton, DC, when it is in fact Washington state. Or it may simply fail because its gazetteer does
not include an entry for the right Washington in a given passage (e.g., Washington, NC). Thus, even when working with very
simple conceptual systems, users should be able to correct system conclusions whether by selecting a different existing answer
or by adding a new possible answer to the existing set. Figure 2.9 shows an existing feedback mechanism whereby users can vote against a machine-generated analysis.
As machines perform more sophisticated analyses where there is no single right answer, user feedback may be even more important:
lexicographers do not always agree on how to describe the senses of a word.54 Machines can infer possible senses by studying the contexts in which a word appears but we still want to be able to modify
the suggested word senses, even if experienced lexicographers would not agree on any one final configuration of senses.
Figure 2.9 A morphological analysis system: this system has calculated the possible analyses for a given form. A simple machine learning
system has ranked the possibilities of each analysis in the given context. Users can now vote for the analysis which they
see as correct.
Documents that adapt themselves to their users
Customization and personalization constitute two other methods by which machines respond dynamically to user behavior. In
customization, users explicitly set parameters to shape subsequent system behavior. Personalization generally implies that
the system takes action on its own, comparing the behavior of a new user to that of other users that it has encountered in
the past.55 Some of us create our own customized versions of internet portals (e.g., "My Yahoo!"). Most humanists had, by 2006, encountered the personalization on sites such as Amazon, which inform us that people who bought
the book that we just chose also bought books X, Y, and Z.56
Both customization and personalization have great potential within the humanities.57
Figure 2.10 illustrates how a user profile can help filter information, showing readers what terms they have and have not encountered.
A reader has informed the system that she has studied Latin from Wheelock's fifth edition. The system has then compared a
passage from Suetonius against the vocabulary in the textbook (drawing upon the morphological analysis system which can match
inflected words to their dictionary entries). Of the 115 possible dictionary words in this passage, the reader has probably
encountered 54 and will find 61 that are new. These new words are then listed according to their frequency in the given passage.
Alternate sorting orders could stress words that would be important in readings that have been assigned for the rest of the
semester, for Suetonius in general or for some particular topic (e.g., military events) of interest to the reader. The technology
can be based on straightforward principles of ranking and filtering from information retrieval but have a significant impact.
The example given addresses language learning but the same techniques are applicable to technical terms. The key to this approach
would be the development of learning profiles which track the contents of many textbooks, handouts, and assigned readings
over different learning which we pursue throughout our lives.58
Figure 2.10 Customization in the Perseus Digital Library. This work was done by David Mimno and Gabriel Weaver, Perseus Project, Tufts
Figure 2.11 illustrates an example of personalization from the Perseus Digital Library. Once a user has asked for information on four
or five words in a 300-word passage of Ovid, we can then predict two-thirds of the subsequent words that will elicit queries.
This recommender system is similar in principle to the systems that Amazon and other e-commerce systems use to show consumers
new products based on the products purchased by people who also bought product X. The application, however, reduces the search
space of a language passage, suggesting words for study rather than products for purchase.59
Customization and personalization are fundamental technologies. While the examples given above address the needs of intermediate
language learning, the same techniques would support professional researchers working with source materials outside of their
own areas of specialization (e.g., an English professor with a background in classical Latin working through sixteenth-century
English Latin prose). Customization and personalization have potential for filtering and structuring information for experts
within their own field of expertise. They are core services for any advanced digital infrastructure underlying ePhilology.
Figure 2.11 Personalization in the Perseus Digital Library. This work was done by D. Sculley, PhD candidate in Computer Science at Tufts
University under the supervision of Professor Carla Brodley, with help from Gabriel Weaver of the Perseus Project.
Building the Infrastructure for ePhilology
The examples in the preceding section illustrate current steps toward future possibilities. This section describes an infrastructure
to move the field forward. On the one hand, we need to exploit emerging technologies. This not only includes downloading applications
and compiling source code but reading research publications and implementing suitable algorithms. At the same time, in the
long run we in classics and in the humanities may primarily contribute the knowledge sources whereby developed tools can analyze
historical materials. Thus, named entity systems applied to texts about the Greco-Roman world will perform much better if
they have access to information about the people and places of the Greco-Roman world than if they must rely wholly on resources
which describe the contemporary world.60
Primary sources and reference materials that evolve in real time should include the following features:
• Open source/polyphonic: We need encoded knowledge that can be maintained in real time and that can incorporate multiple points of view. Core resources
should not be held restricted by rights agreements but should serve as a common resource to which others may add and from
which others may generate new resources.61 New variations on traditional review will emerge, with ongoing usage within the scholarly community complementing — and perhaps in some measure supplanting — the hit or miss preparatory edits of static documents necessary for print. In a digital world, capital information sources
such as editions and reference works evolve: where print publication freezes documents, digital publication only begins its
functional life after publication. We can easily preserve versions of the document as it appeared at any one time (thus allowing
us to see what an author saw when the citation was added to an argument) and track who contributed what and at what time.
• Readable by machines and people alike: Our dictionaries should be able to search new texts for the varying senses claimed for each word; our encyclopedias should
scan secondary sources for, and then summarize the results of, new discussions of the people, places, and topics which they
cover; our texts should collate themselves against other witnesses and editions as these come online. The more machines can
understand, the more effectively they will be able to support the questions that we pose and to provide the personalized background
that we need.62 The need to add the greater structure and consistency needed for machine processing only highlights the need for materials
that we can freely reformat.
These features have at least one profound implication. Once documents become dynamic and can evolve over time, we must evaluate
them according to their potential for growth — their state at any one time constitutes only a single data point. In classics, editions and reference works more than a century
old but which are in the public domain and can be freely updated may thus prove more valuable in an electronic environment
than the best current resources if these are either static or even updated according to a traditional editorial process.
A range of community-driven reference works has emerged in recent years. The most famous, Wikipedia, arguably constitutes
the most important intellectual development of the early twenty-first century: a new form of intellectual production, community
driven and dynamic, has produced more than 1,000,000 general articles in five years.63 If and when the need for new articles diminishes, it will be interesting to see whether this vast resource enters a phase
of refinement, thus suggesting a twofold model: an open phase of development to bootstrap the system, followed by a period
of revision. Criticizing this work is important, but only insofar as such criticism helps us to draw upon and contribute to
this flood of intellectual energy.64 Other community-driven systems with more centralized editorial control have appeared for math and physics.65 A 2005 grant from the National Endowment for the Humanities has even provided support for Pleiades, a community-driven project
on Greco-Roman geography.66
An infrastructure for ePhilology would contain two fundamental components: the primary sources and a network of reference
works, linked to and constructed from the sources. Dynamic and intelligent links should connect all components of the infrastructure.
When changes are suggested to a text, the effects of these changes upon associated reference works should be tracked and all
affected places in all reference works should automatically report the change. Conversely, work based on analysis of a particular
reference work should be noted in the text (e.g., a new study of a particular person that suggests reading one name vs. another).
Technically, this environment needs two things: a set of data structures and data. The Text Encoding Initiative (TEI) provides
serviceable structures for texts themselves.67 Text mining can identify many patterns latent within these texts,68 but once we have ways of identifying people, places, organizations, and other entities within texts we need methods to reason,
at least in rudimentary fashion, about them. Knowledge bases differ from databases in that they are designed to support inferencing:
thus, if the system knows that no events in Herodotus postdate 400 bce, that Alexander the Great was born after 400 bce and that Alexander the Great was a king of Macedon, then it can avoid identifying the Alexander, king of Macedon, in Herodotus
as Alexander the Great. Fortunately, the slowly emerging Semantic Web is designed to support such reasoning. Promising formats
exist for geographic information69 and for museum objects,70 and we now have a well-developed set of guidelines for ontology production in OWL (Web Ontology Language).71 Ontologies, however, rapidly grow idiosyncratic and their development is as much a social as a technical process.72 To drive that development, however, we need enough data for serious experimentation — data structures and data will need to evolve, however cautiously, in tandem. We need services of interest to attract long-term
user communities and enough data to raise issues of scale if we are to engineer solutions that will support intellectual life
The Google Library and especially the Open Content Alliance, which has an open source policy, will help provide access to
image books of virtually all useful public domain materials. These will provide immediate access to Latin and Roman script
publications, with searchable OCR (optical character recognition) for classical Greek probably not far behind. These texts
will provide the foundation on which we can build a dynamic knowledge base that evolves and grows more intelligent.
Moving from print to knowledge involves three steps:
1. Initial markup to capture the basic structural elements: we need the headwords for dictionaries/lexica/gazetteers, clear separation
of headers, footnotes and text, and other basic elements not present in raw OCR.73
2. Semantic analysis: classification of proper names (e.g., is Peneius the river or the river god?) and identification of basic propositional statements (e.g., "a REGION of PLACE," "PERSON born at PLACE in DATE").74
3. Alignment against pre-existing entries common list and identification of new entries: Alexander-12 in encyclopedia-1 may be
equivalent to Alexander-32 in encyclopedia-2 or it may represent an entirely new Alexander not yet attested.75
Automated methods can address all three of the above phases but all methods are imperfect and print sources differ just enough
that methods still need to be tuned for most reference materials. The three steps above constitute the most important and
probably the most difficult work that we face, but they are essential and foundational to any serious infrastructure.
Classicists are fortunate in having a well-developed set of public domain print resources with which to begin their work.
• Texts: These can take older editions as their initial base texts but should then (1) be collated with other editions, both older
and new, and (2) provide an initial database of variants and conjectures that can be expanded over time.76 One well-tagged edition could help automatically identify and provide preliminary tagging for other online editions.77 Perseus contains c. 70 percent of the corpus of classical and Hellenistic Greek and 50 percent of the corpus of classical
Latin in TEI-compliant XML. Both collections are expanding, with coverage of Latin being particularly cost effective: we should
be able to provide coverage of 96 percent of the text on the PHI CD ROM, with later authors not in that collection (e.g.,
Ammianus, Sidonius) and a substantial postclassical collection.
• Translations: Scholars working with any historical language should, as a matter of principle, ensure that (1) translations are readily
available and (2) flag those places where the new edition would impact at least one standard translation. Translations are,
however, not only useful for those with little or no knowledge of the source language: parallel text analysis is a major component
for machine translation (necessary where translations do not exist), automated lexicography, cross-language information retrieval
etc.78 Multiple translations of a single text strengthen statistical analysis. Translations are thus a high priority to any infrastructure
for an ePhilology. In Perseus we have collected at least one translation for most of our sources.
• Morphology: The ability to connect a dictionary entry with its inflected forms is a fundamental service for any language. While the
code needed to recognize legal combinations of stem and ending is challenging in Greek (where we must also consider augments,
preverbs, accent, and diacritics), morphological analysis is a data-intensive process that depends upon lists of endings and
especially stems. Since stems are, in practice, an unbounded set, assembling suitable databases of morphological data is the
greatest challenge to morphological analysis in Latin and Greek. Dictionaries have provided the best general source for the
stems, with Liddell, Scott, Jones (LSJ), and Lewis and Short helping us create databases with 52,700 Greek and 19,800 Latin
stems. In 1990, we provided 100 percent coverage for the one million words of Greek included in Perseus 1.0. Many low frequency
words and most proper nouns are not in these source lexica and only modest progress was made in extending this coverage. The
need to improve morphological analysis provided one, though by no means the only, reason to identify, digitize, and mine more
comprehensive reference works with people and places.
• People and places: For classical texts, the nineteenth-century three-volume Dictionary of Greek and Roman Biography and Mythology (Smith 1873) and Smith's two-volumeDictionary of Greek and Roman Geography (Smith 1854) are more than a century older than the third edition of the Oxford Classical Dictionary (OCD3) (Hornblower and Spawforth 1996). Anyone looking for a survey of standard views from the late twentieth century must, of course, consult OCD3. Nevertheless,
the older Smith dictionaries are better sources for ePhilology because they are more extensive and contain tens of thousands
of machine-extractable source citations. Both dictionaries set out, with reasonable success, to document all significant people
and places mentioned in the literary corpus,79 with 20,000 and 10,000 entries in the biographical and geographical dictionaries. Equally important, we have been able to
extract 37,500 and 25,800 citations, respectively. Each citation not only associates a particular passage with a particular
topic but provides more materials whereby text-mining software can learn to distinguish the various Alexanders and Alexan-drias
when they appear elsewhere in primary and secondary sources alike. The original Smith articles can be mined for information
about birth/death dates, family relations, place locations, and other quantifiable data that can be used for intelligent information
retrieval and general text mining.
• Authors, works, and their citation schemes: Authors comprise a key subset of people, with their works often listed in biographical entries of Smith's biographical dictionary,
as well as good coverage for more than three and a half centuries of printed editions. The TLG and PHI Institute each have
produced up-to-date catalogues of recent editions, as well as lists of author works. Lexica such as LSJ and Lewis and Short
include extensive bibliographies of authors, works, and older editions. While the Oxford Latin Dictionary is a relatively recent publication, it began work in the 1930s and the editions which it cites are almost all in the public
domain today — thus providing an excellent starting point for digitization. Other materials can provide other categories of background:
(Hall 1913), for example, describes the textual traditions for all major classical authors as it was understood in the early twentieth
century (and thus as it appears in most public domain editions). Authors and works that have appeared as separate editions
also have standard names: once we associate Marcus Tullius Cicero, M. Tullius Cicero, and Cicero, for example, with the canonical
name authority form "Cicero, Marcus Tullius," we can automatically search standard library catalogues. Online texts generally provide one citation scheme. Some authors,
however, have multiple citation schemes and we need to manage them all if we are to exploit the full range of citations. These
should be included when the electronic editions are created, with alternate citation schemes added to existing texts as image
books with the alternate citations become available.
• Lexicography: We want to be able to identify not only particular forms and dictionary entries but the distinct senses of particular words
in particular passages. Parallel corpora, with source texts in one language aligned with translations in one or more languages,
have allowed machine translation to make substantial progress in recent years. The machine translation systems can look for
statistical associations between words in the two languages to identify probable translation equivalents for particular words
in particular passages. Machine-readable dictionaries remain crucial tools for machines as well as for human readers.80 Online lexica not only provide reading support but provide a foundation for semantic analysis through comparison of dictionary
definitions and an open inventory of documented senses. LSJ 9 and Lewis and Short,81 augmented by more specialized lexica, provide a reasonable starting point for an electronic infrastructure.
• Syntax: We also want to be able to identify the syntactic relations within a sentence —at the simplest, answering the question "what does this word depend on and what is its function?" Generating accurate parse trees for complete sentences is difficult in any case and increasingly difficult the larger and
more complex the sentence. Nevertheless, even if the complete sentence parse is not correct, enough individual word-to-word
relations are usually correct to detect patterns such as which nouns go with which adjectives, what cases a verb takes, etc.
Grammars are the logical starting point for syntactic data: we have thus digitized the extensive Kühner-Gerth Greek Grammar,82 as well as the shorter Smyth83 and Allen and Greenough84 grammars for Greek and Latin. Highly inflected languages store much of their syntactic information in word forms that less
heavily inflected languages may express in word order. Greek and Latin lexica thus contain much — and arguably more — syntactic information than conventional grammars, since the constructions associated with individual words may be key to
determining the correct parses for a sentence.
• Specialized reference materials: Larger works may contain specialized glossaries on particular topics. (Hall 1913) contains a very useful glossary that explains the Latin names for manuscripts in many editions; (Smyth 1920) contains a glossary of rhetorical terms. Specialized lexica cover the language of particular authors, such as Slater's Pindar
lexicon.85 Once again, the Smith dictionary series provided us with a foundational resource on which to build: the two-volume Dictionary of Greek and Roman Antiquities (Smith, Wayte et al. 1890) contains 3,400 entries and (as of this writing) 25,000 extracted citations covering law, architecture, religion, rhetoric,
and other aspects of life.
• Events: One can easily enter a philosophical funk trying to define what is and is not an event, but modern timelines and ancient
chronologies show us what others chose to identify as significant events and provide us with an objective record of what others
have chosen to label and recall.86
The role of the editor in a digital world
The digital world makes possible a new kind of editor: the corpus editor occupies a middle ground between the algorithm-heavy,
knowledge-light approaches of computer science and the wholly manual practices of traditional editing. The corpus editor works
with thematically coherent bodies of text that are too big to be processed and checked by hand and that therefore demand automated
methods. The corpus editor combines knowledge bases and automated methods to apply automated markup and/or extract information.
The corpus editor cannot check every automated decision but is able both to document how the automated decisions were made
and to provide statistical measures for the accuracy of those decisions.87
The role of the traditional editor also changes in an electronic environment. The traditional editor becomes responsible for
preparing documents for use not only by people but by machines. The ePhilologist reviews a high percentage — and ideally all —of the automated decisions that link a particular text to knowledge sources such as those listed above: the editor manages
the automated processes and reviews the results. The editor checks the morphological analyses and parse trees, comments on
passages where the identification of a person or place is ambiguous, etc. The edited documents in the digital library provide
crucial training sets that improve the performance of automated methods generally: thus, careful work on a few lives of Plutarch
should improve results on the other lives and on similar Greek prose generally.
Digital culture already dominates serious intellectual life, even if its dominance still subordinates itself to the superficial
— and, to a classicist, quite recent — forms of print culture. The previous section described one partial survey of what form classics might take as a digital culture
matures and intellectual practice begins to exploit this digital world for its own strengths. The examples given reflect substantive
work with existing technologies applied to questions common to all students of historical languages. All of the examples above
either are, or could become, general services.88 Nevertheless, they constitute a few first steps in a much larger process.
Much of the above work was possible because the National Science Foundation and the National Endowment for the Humanities
collaborated on the Digital Library Initiative Phase II, a program which supported a range of humanities projects. We cannot
expect such levels of support in the future.89 If we are to move forward as a field, we must use what we have learned from what worked and what did not work in the past
to develop a strategy to help us move forward in the future. Classics may or may not pursue the particular directions suggested
in the previous section, but passively drifting along a broader current of academic practice is a dangerous course. The Mellon
Foundation and American Council on Learned Societies recently funded a "Commission on Cyberinfrastructure for Humanities and Social Sciences."90 A PhD in English (John Unsworth) chaired the commission, which included five humanists, including another person from English
literature (Jerome McGann), an American historian (Roy Rosenzweig), an art historian (Sarah Fraser), and the director of an
archaeological research collection (Bruce Zuckerman). The draft report available in May 2006 makes cursory mention of classics.
Classicists cannot expect colleagues who work primarily in English and with relatively recent sources to anticipate the problems
of working with historical languages. Classics — and all disciplines which draw upon languages of the past — must tirelessly engage in larger conversations and be prepared to defend the significance of language.
One effective solution is the creation of a new area of informatics designed to bridge the gap between a discipline and current
research in computer science — a demanding task, if performed well, because it requires a command of emerging, as well as established, issues in two radically
different disciplines. The field of biology, confronted with overwhelming amounts of raw data, produced the field of bioinfor-matics,
thus creating an intellectual space, primarily grounded in biology, to connect research in computer science with biology research.
Classics probably cannot command a hundredth part of the resources on which biological research depends. We cannot call forth
a major new discipline with the funding to attract the attention of grant-driven computer scientists. Nevertheless, we can
accomplish a great deal.
• All philological inquiry, whether classical or otherwise, is now a special case of corpus linguistics: Its foundational tools should come increasingly from computational linguistics, with human and automated analysis. Vague
statements such as "typical of Greek prose," "common in early Greek," etc. must give way to dynamically generated measurements of well-mapped corpora. Human judgment must draw upon and work in
conjunction with documented mathematically grounded models. The salaries which support Classics faculty are the one resource
which we, as a field, collectively allocate. As at least some, if not most, members of the field begin to see themselves as
computational linguists with a particular focus on Latin and/or Greek, we will soon mobilize over a long period of time far
more intellectual capital than the most generous grants could provide for limited periods.
• We need to rethink what we study: Tasks which we as human readers take for granted often demand substantial analysis when we transfer them to automated systems.
Classicists cannot manually fit all 91,000,000 words in the current TLG into parse trees. Some tasks, such as concordance
generation or even more sophisticated problems such as morphological analysis, can follow well-defined results: e.g., display
all possible instances of the Latin verb facio in the Catilinarians of Cicero. We soon reach problems for which rule sets provide much less accurate results: is a given
instance of the form faciam a subjunctive or future? Which "Alexander" does a particular passage cite? Which accusative noun is the subject of the infinitive and which the object? We need a foundational work on the problem of resolving ambiguities, producing the best possible results and providing accurate
information as to the accuracy of automated results. We need to take a step and work on the tools on which research will rely.
• We must distinguish programming from computer science: We will need quite a bit of advanced programming, even if we are only gluing together tools developed by our colleagues
in computational linguistics. Nevertheless, we must separate analysis of our methods from the code by which we test them.
We need the patience to evaluate multiple methods to solve the same problem and to produce results from which others can learn
— a patience that will become more common as we develop a community of research. We also need to consider our skills: crucial
as programming may be, philologists who wish to draw effectively upon the emerging tools of our world must become familiar
with linear algebra and probability.
• ePhilology is part of a larger, cultural informatics: ePhilology represents one particular approach to a comprehensive analysis of earlier culture: we may center our attention
on words, but our questions will soon lead us to the evidence of material culture. Classics may be big enough to sustain its
own classical informatics, but we would be much better served by contributing to a larger cultural informatics. We should
aggressively establish alliances with partners with similar needs and limit, as much as possible, ourselves to those problems
which only classicists can address. We have developed our own morphological analyzers, syntactic analyzers, and named entity
recognition systems, but it would be much better for us to concentrate on the databases of stems and endings, the grammar,
and the knowledge bases of people, places, etc. Our natural collaborators include not only all of those working with historical
languages but also those struggling to analyze the thousands of languages spoken in our contemporary world. Where cultural
informatics would embrace all sources of information — natural language, relational databases, images, GIS, 2D and 3D models, simulations — ePhilology implies a focus upon linguistic sources.
• We need to identify what structures we need to institutionalize: A generation ago, classicists could get jobs, tenure, and promotion at leading institutions as editors and authors of scholarly
commentaries. Almost all classics faculty under the age of fifty in US departments have, however, made their careers by producing
articles and monographs, with far less emphasis on editing and work on the intellectual infrastructure of the field. A generation
of ePhilologists may emerge to play prominent roles in our departments as the field realizes that we are not just copying
print into digital form but creating a wholly new, qualitatively distinct infrastructure. The changes before us may exceed
those spawned by movable print and may be more comparable to the invention of writing itself. We also need new libraries to
help us maintain into the future the resources that we create. Libraries will need to develop new skills to manage digital
libraries and new ways to use their acquisition budgets to support the creation of content with the structure and the right
regimes needed by humanists.91 We may need new departmental and research structures —combinations of Classics and computer science may become common, to the benefit of both fields. We need to establish relationships
with major commercial entities such as Google, Yahoo, and Microsoft, if these continue to evolve into the public libraries
of the twenty-first century and provide us with new channels to society as a whole.
Some emerging technologies could, if applied to classics and to other philological disciplines, have a swift and dramatic
impact upon the questions that we pursue: machine translation, parallel text analysis, named entity identification, syntactic
analysis, cross-language information retrieval and a range of text mining methods are well suited to a range of needs. The
impact of digital technology will, however, be far broader and more pervasive than any particular tools we can deploy in the
immediate future. The future of classics depends less upon particular tools than upon an emerging digital environment that
integrates an increasing number of tools together into a dynamic world, constantly evolving to answer our questions and support
the life of the mind. From the nineteenth century through the twentieth, we were able to take our scholarly infrastructure
for granted: we had our publishers and libraries, our editions, commentaries, lexica, journals, monographs, and encyclopedias.
We now have the merging of print, broadcast media, and gaming, new commercial entities planning universal access to a better
library than the wealthiest academic institution on earth could provide to its faculty; we have new forms of intellectual
production such as blogs and wikis; we have ontologies and knowledge bases at the core of reference materials; we have a world
of dynamic information —books that read and learn from each other and from their human readers. The challenge now — and it is perhaps the greatest challenge classicists have faced since they found themselves pushed out of the center of the
academy — is to shape this world and negotiate a new place for classical studies within it.
1 The work described here builds on support from a variety of sources, including the Digital Library Initiative, Phase 2, the
National Endowment for the Humanities, the National Science Foundation, and the Institute for Museum and Library Services.
Many individuals have contributed. We mention in particular Carla Brodley, Lisa Cerrato, David Mimno, Adrian Packel, D. Sculley,
and Gabriel Weaver.
2 For some reviews of how technology has been used within classics, please see: Crane 2004, McManus 2003, Latousek 2001, and Hard-wick 2000.
3 Classicists were quick to embrace the Bryn Mawr Classical Review (<http://ccat.sas.upenn.edu/bmcr/>), which began publication in 1990 as a mailing list. BMCR was successful for three reasons: first, it used email to speed
up the pace of scholarly communication, thus addressing a single, nagging problem; second, the electronic form allowed BMCR
greater flexibility than its print counterparts, allowing it to accept a greater range of reviews, thus encouraging a wider
range of submissions; third, its articles were, and remain, electronic analogues of print: they do not challenge their authors
to rethink the substantive form of their work. The Stoa publishing consortium, by contrast, began in 1997 and has supported
a range of more innovative projects (including the Demos project described below).
4 For some recent overviews of the issues with scholarly publishing, please see Unsworth 2003.
5 Derrida 1972.
6 For a discussion of fears that Google and the digitization of libraries will lead to serious decontextualization of learning,
see Garrett 2006.
7 Dino Franco Felluga discusses this issue as well in regards to literary studies; please see Felluga 2005.
8 The idea of a permanent personal digital archive or storehouse of lifetime memories and knowledge has been well articulated
by the creators of MyLifeBits (Gemmell 2006). Neil Beagrie has also explored this concept (Beagrie 2005).
9 A wealth of research has been conducted into how systems can best automatically adapt themselves to the needs of different
readers, such as Russell 2003, Dolog 2004, Niederee 2004, Rouane 2003, Wang 2004, and Terras 2005.
10 Text mining is increasingly being used in humanities applications; see, for example, Kirschenbaum 2006 and Xiang 2006.
12 For one exploration of the impact of the TLG on classical scholarship, please see Ruhleder 1995.
13 For a discussion of some of this work, see Packard 1973.
14 Crane 2004.
17 Biblioteca Teubneriana Latina 2004.
18 Maria Pantelia, the director of the TLG, reported (private communication, September 2006) that lemmatized searching was in
active development and would become part of the core TLG functionality.
19 There is a growing body of research into the need for more complex linguistic querying capabilities, particularly with historical
language materials, please see de Jong 2005, Egan 2005, and Gerlach 2006.
20 See, for example, (Church 1989 and Justeson 1995).
21 The Perseus Digital Library has done extensive research in terms of the importance of named entity recognition and searching;
please see Crane and Jones 2006a, Smith 2001.
22 For an example of a prototype system that supports many of these features, please see Ignat 2005.
23 A search for —pemp- turns up "(4.) OI)KH/TORAS A)POPE/MPEIN. OI(DE/*) EPIDA/MNIOI OU)DE/N AU)TW=N U(P-" with the label Thucydides "Book 1 chapter 26 section 4 line 1." In fact, the word is part of section 3, with section four beginning in the middle of the print line after the period. Simple
programming can capture most of these section breaks, although some lines have more than one full stop and editors may use
commas — or nothing — to mark the divisions of established units.
24 In the late 1990s, while Theodore Brunner was director of the TLG, David Smith of the Perseus Project created an SGML version
of the TLG that validated against the TEI DTD. Mark Olsen of ARTFL also created a similar experimental version at the University
of Chicago. In both cases, understanding the idiosyncratic reference encoding of the TLG proved the major barrier.
25 The largest Greek dramas are, with extensive XML markup, just over 120,000 bytes and would cost $120 to $180 to enter, depending on the vendor.
26 Research into variant editions and how best represent this information digitally has received a growing amount of attention,
for example see Dekhytar 2005, Pierazzo 2006, Schmidt 2005, Audenaert 2005, and Riva 2005, and for an example in classics Bodard 2006.
27 <http://www.tlg.uci.edu CDEworks.html#supp>.
28 The online TLG does not seem to provide any information about the texts that have been "suppressed," in effect consigning these editions to an electronic damnatio memoriae. A print copy of the second edition of the TLG Canon preserves the fact that the TLG had originally contained the Murray
edition of Euripides. The online TLG canon simply lists the Diggle edition of Euripides now included in the TLG.
30 Blackwell 2005. For some examples of how the CTS protocols are being used, please see Porter et al. 2006.
31 According to at least one participant at the international gathering of Hellenists which launched the TLG in the early 1970s,
the experts in the field assumed that the texts of ancient authors, as published in editions, were not copyrightable. We need
automated methods with which not only to compare but to quantify the differences between various electronic editions of the
same text. Preliminary analysis suggests that changes from one edition to another are comparable to copy-editing. The best
model for editors employed by academic institutions may thus be a work-for-hire, with the rights holders more properly being
institutions who paid their salary.
32 The representative of one UK publisher stopped at Perseus years ago en route, as he informed us, to assert rights to electronic
versions of texts that a third project had entered. We paid $7,000 for rights to two editions — only to discover that those editions had unambiguously gone into the public domain by UK law and had never been under copyright
in the US. Another US publisher that had knowingly published materials in the public domain reportedly charges permissions
fees for these materials for which it has no legal rights.
33 For more on the issue of the public domain and copyright issues in the face of mass digitization, please see Thatcher 2006 and Travis 2005.
34 Classicists define their own conventions of what does and does not count, and we can accept monographs published in emerging
institutional repositories — in effect, we would return to a scholarly publication model, separate from university and commercial presses, that has served
us well in the past.
35 For further discussion of Perseus examples, please see Crane et al. 2006a.
37 For discussion of the Google Library project, please see MacColl 2006, for the Open Content Alliance please see Tennant 2005.
38 For a comprehensive look at the open access movement, please see Willinsky 2005.
43 <http://www.stoa.org/projects/demos home>.
44 The work of the Public Knowledge Project attempts to link scholarship to freely available sources in order to support reading
by a broader audience; see Willinsky 2003.
45 This need for reusable digital objects that can draw upon a range of services is a major theme of the recent Mellon-funded
study to support interoperability between digital repositories (Bekaert 2006).
46 For a good overview of the possibilities inherent in better exploiting the semantic content of digital objects, please see
Bearman and Trant, 2005.
47 A similar issue is often raised by those researchers who wish to analyze Wikipedia, but find its unstructured data requires
a great deal of work to support automated processing. See Volkel 2006.
48 Liddell et al. 1940.
49 Berkowitz and Squitier 1990.
50 For more on the potential of what can happen when the knowledge within digitized books interacts, please see Kelly 2006, Crane 2005a, Crane 2005b.
51 Smith 2001. For more on the technical details of this system, see Crane and Jones 2005.
52 A variety of work is beginning to explore how best to exploit both the structured and unstructured knowledge already present
in digital library collections to train other systems with document analysis and machine learning; see for example Nagy and
Lopresti 2005 and Esposito et al. 2005.
53 Research into how to capture the knowledge of users to drive both machine learning processes and personalization is growing
rapidly, see for example Chklovski 2005, Carrera 2005, Gilardoni 2005, Kruk 2005.
54 Some initial work in having user contributions assist in automated word sense disambiguation has been reported in Navigli and Velardi 2005.
55 For an expansion of these definitions see Russell 2003, and for a particular application see Bowen and Fantoni 2004.
56 For more on the Amazon system, please see Linden et al. 2003.
57 There is growing body of literature as to how these technologies might be applied within the humanities, most often digital
libraries, for an overview please see Smeaton and Callan 2005,
58 Developing accurate user models and profiles to support and track learning is a topic of significant study, for some recent
work please see Brusilovsky 2005 and Kavcic 2004.
59 Work on how personalization, particularly recommender systems, might be used within humanities environments has been explored
by Bia 2004, Kim 2004, to name only a few.
60 On the need for historical knowledge sources, see Crane and Jones 2006b and also Siemens 2006.
61 For some recent work on creating reference works that allow users to both edit and create materials, please see Witte 2005 and Kolbistch 2005.
62 For an intriguing exploration of the potential of "machines as readers", see Shamos 2005.
63 As of May 23, 2006, the count for English articles on <http://www.wikipedia.org> stands at 1,145,000.
64 For example, see Rosenzweig 2006.
65 <http://planetmath.org/>; <http://planetphysics.org/>.
68 This is the approach of the Nora text mining project: <http://nora.lis.uiuc.edu/description.php>; Plaisant et al. 2006.
69 <http://www.alexandria.ucsb.edu/gazetteer ContentStandard/version3.2/GCS3.2-guide.htm>.
72 For some particular applications of ontologies in the humanities, see Nagypal 2004, 2005, Mirzaee 2005, and for the merging of various efforts, see Eide 2006 and Doerr 2003.
73 For some lengthier discussion of these issues see Bearman and Trant 2005 and Sankar 2006.
74 Named entity recognition and semantic classification have large bodies of literature, but the use of theses applications in
the humanities is receiving more examination; see Hoekstra 2005 and Shoemaker 2005.
75 For interesting work in this area, see Barzilay 2005.
76 For some previous work in this vein see Spencer 2004.
77 If we have "arma virumque cano Troiae qui primus ab oris" tagged in one text as Aen. 1.1, then we locate other instances of this line and apply the same markup. This strategy draws
upon the fact that runs of repeated words are surprisingly uncommon, even in large corpora.
78 For a recent exploration of the uses of parallel texts, see Mihalcea 2005, and their use in machine translation Smith 2006.
79 Smith 1873: ix: "Some difficulty has been experienced respecting the admission or rejection of certain names, but the following is the general
principle which has been adopted. The names of all persons are inserted, who are mentioned in more than one passage of an
ancient writer: but where a name occurs in only a single passage, and nothing more is known of the person than that passage
contains, that name is in general omitted. On the other hand, the names of such persons are inserted when they are intimately
connected with some great historical event, or there are other persons of the same name with whom they might be confounded"; (Smith 1854: viii: "Separate articles are given to the geographical names which occur in the chief classical authors, as well as to those which
are found in the Geographers and Itineraries, wherever the latter are of importance in consequence of their connection with
more celebrated names, or of their representing modern towns,—or from other causes. But it has been considered worse than useless to load the work with a barren list of names, many of
them corrupt, and of which absolutely nothing is known. The reader, however, is not to conclude that a name is altogether
omitted till he has consulted the Index; since in some cases an account is given, under other articles, of names which did
not deserve a separate notice."
80 For more on machine translation and WSD see Smith 2006, Marcu 2005, and Carpuat 2005.
81 Liddell et al. 1940, Andrews et al. 1879.
82 Kühner et al. 1890.
83 Smyth 1920.
84 Allen et al. 1904.
85 Slater 1969.
86 The use of HEML Historical Event Markup Language could be applicable in this area; see Robertson 2006.
87 For more on the role of corpus editors, see Crane 2000.
88 For examples of potential services, please see Patton 2004 and Crane et al. 2006b.
89 For a discussion for the future of digital library funding, see Griffin 2006.
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91 For more on the needs of new library services and infrastructures, see Dempsey 2006.
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