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implications of handl<strong>in</strong>g archaeological <strong>in</strong>formation digitally… this is [SIC] also perta<strong>in</strong>s to the
broader arts and humanities VRE agenda. The act of publish<strong>in</strong>g a database of archaeological
<strong>in</strong>formation implicitly disguises the fact that creat<strong>in</strong>g the database <strong>in</strong> the first place is an
<strong>in</strong>terpretive process (Dunn 2009).
Dunn’s warn<strong>in</strong>g is an important rem<strong>in</strong>der that the design of any <strong>in</strong>frastructure <strong>in</strong> the humanities must
take <strong>in</strong>to account the <strong>in</strong>terpretative nature of most humanities scholarship. He also further detailed how
archaeological workflows are “idiosyncratic, partly <strong>in</strong>formal, and extremely difficult to def<strong>in</strong>e,” all
factors that make them hard to translate <strong>in</strong>to a digital <strong>in</strong>frastructure (Dunn 2009).
Some recent research us<strong>in</strong>g topic model<strong>in</strong>g and an archaeological database has illustrated how
subjective the human <strong>in</strong>terpretations of archaeological data can be. Recent work by David Mimno
(2009) used topic model<strong>in</strong>g and a database of objects discovered <strong>in</strong> houses from Pompeii 259 to
exam<strong>in</strong>e the validity of the typological classifications that were <strong>in</strong>itially assigned to these objects. This
database conta<strong>in</strong>s 6,000 artifact records for f<strong>in</strong>ds <strong>in</strong> 30 architecturally similar houses <strong>in</strong> Pompeii, and
each artifact is labeled with one of 240 typological categories and the room <strong>in</strong> which it was found.
Because of the large amount of data available, Mimno argued that the use of statistical data-m<strong>in</strong><strong>in</strong>g
tools could help provide some new <strong>in</strong>sights <strong>in</strong>to these data:
In this paper we apply one such tool, statistical topic model<strong>in</strong>g ... <strong>in</strong> which rooms are modeled
as hav<strong>in</strong>g mixtures of functions, and functions are modeled as distributions over a “vocabulary”
of object types. The purpose of this study is not to show that topic model<strong>in</strong>g is the best tool for
archeological <strong>in</strong>vestigation, but that it is an appropriate tool that can provide a complement to
human analysis. To this aim, we attempt to provide a perspective on several issues raised by
Allison, that is, if not unbiased, then at least mathematically concrete <strong>in</strong> its biases (Mimno
2009).
In common archaeological practice, Mimno expla<strong>in</strong>ed, artifacts that are excavated are removed to
secure storage, and while their location is carefully noted <strong>in</strong> modern digs, artifacts <strong>in</strong> storage are
typically analyzed “<strong>in</strong> comparison to typologically similar objects rather than with<strong>in</strong> their orig<strong>in</strong>al
context.” Consequently, Mimno reasoned that determ<strong>in</strong><strong>in</strong>g the function of many artifacts had been
driven by “arbitrary tradition” and the perception of <strong>in</strong>dividual researchers <strong>in</strong> terms of what an artifact
resembles. Two classes of artifacts, <strong>in</strong> fact, the casseruola (casserole dish) and forma di pasticceria
(pastry mold) were named based on similarities to n<strong>in</strong>eteenth-century household objects, and the
creator of the Pompeii database (Penelope Allison) contended that modern archaeologists often made
unvalidated assumptions about objects based on their modern names (Allison 2001).
For these reasons, Mimno decided to use topic model<strong>in</strong>g to reduce this bias and explored the function
of artifact types us<strong>in</strong>g only object co-occurrence data and no typology <strong>in</strong>formation. All object
descriptions were reduced to <strong>in</strong>tegers, and a statistical topic model was then used to detect “clusters of
object cooccurrence” that might <strong>in</strong>dicate functions. While Mimno admitted that this system still relied
on experts hav<strong>in</strong>g accurately classified physical objects <strong>in</strong>to appropriate categories <strong>in</strong> the first place, no
other archaeological assumptions were made by the tra<strong>in</strong><strong>in</strong>g model. The basic assumption was that if
two objects had similar patterns of use they should have a high probability of co-occurrence together <strong>in</strong>
one or more “topics.” Initial analysis of a topic model for the casseruola and forma di pasticceria
illustrated them as hav<strong>in</strong>g little connection to other food-preparation objects and thus supported
Allison’s claim that the modern names for these items are <strong>in</strong>correct. This work illustrates how
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