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Inside-out and Outside-In: Improving and Extending Digital Models for Archaeological Interpretation

Rachel Opitz, James Newhard, Marcello Mogetta, Tyler Johnson, Samantha Lash, and Matt Naglak

(Additional presenters: James Newhard, College of Charleston, Marcello Mogetta University of Michigan, Tyler Johnson University of Arkansas, Samantha Lash Brown University, and Matt Naglak University of Michigan)

The growth in synergies between classicists and other disciplines forms an active place where time-tested processes of inquiry are augmented, providing an environment where interpretations can be challenged, strengthened, and improved. We offer complementary points of reflection on current and emerging processes for modeling the ancient world.

We begin by asking how 3D modeling affects the interpretation of remains of an urban environment. Digital techniques for recording field data and modeling in 3D have advanced rapidly in recent years, creating new opportunities for the study of urban space (e.g. Klein, Vermeulen and Corsi 2012; Paliou 2011; Paliou 2013) while presenting interpretive challenges. Such challenges include balancing the model’s emphasis on visual and spatial aspects of townscapes and the contributions of non-spatial data. More practically, one needs to understand the crucial impact of user interface design on the interpretive process. Using examples from the Gabii Project and the digital archaeological publication project “21st c. Data, 21st c. Publications. 3D Model Publication and Building the Peer Reviewer Community” we illustrate the importance of understanding the links between media and message, beyond paradata and metadata (3DVISA 2007), particularly when using partial evidence from an ongoing excavation of a town with imperfect preservation. Referencing research on domestic space at Pompeii (e.g. Frederick 2013) and rural and ritual landscapes (Earl and Weatley 2002), we emphasize the impact of design choices in a modeling environment on interpretations of the use of spatial and visual cues that guide interaction with(in) urban places.

We then consider how models based on textual, archaeological, and geographical evidence can be developed to strengthen interpretative frameworks. As an example, archaeological survey presented investigators with concentrations of artifacts in contexts that lent to their identification as ‘watchtowers.’ Rather than take this functional assignment as a given, the investigators developed a means to model a variety of functional landscape elements based upon prior archaeological and textual resources and then to evaluate the artifact patterns to this model (Newhard et al. 2012). In so doing, the model not only confirmed these concentrations as defensive, but discriminated between different types of defensive systems. The framework employed provided an iterative, flexible framework of analysis, where additional insights and data could be incorporated.

In sum, emerging approaches offer both an “inside-out” perspective on how to build better models starting from material data, and an “outside-in” perspective on how to build models from proxy data that test interpretations.

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Making Meaning from Data (Joint SCS/AIA Panel)

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