the Digital Archaeologial Record Developing an Information Infrastructure for Archaeology Arizona State University School of Human Evolution & Social Change — School of Computing & Informatics

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tDAR Version 2

Needs

Beyond the substantial capabilities of tDAR Stage 1, our vision implies additional requirements.

Maintaining the utility of data over the long term requires:

• Metadata that are sufficient, on their own, to make the data meaningful for future use and integration.

Fostering synthetic and comparative research requires:

• A concept-oriented interface, in which the user does not need to know the specifics of how the data were encoded.
• Data integration methods, sensitive to complex archaeological contexts and recovery techniques, that do not require the reduction of archaeological data to a universal standard but that permit query-driven integration of data produced by different projects using variable data recovery strategies and inconsistent classification schemes.

These requirements imply the need for:

• Entry of column-level metadata for databases that provide the semantic information necessary to interpret encoded data, e.g., metadata that associate numeric codes with meaningful labels or metadata that indicate that a particular column has linear measurements in millimeters.
• Representation of archaeological knowledge in “ontologies” that logically describe and link archaeological concepts. The knowledge base comprised of these ontologies must accommodate alternate and possibly conflicting ontologies for the same concepts
• Data integration tools that can use this detailed metadata and knowledge base, in interaction with the user, to achieve the kinds of data integration that now can only be accomplished in extremely labor intensive ways.

Implementation (late 2008)

The Stage 2 effort focuses on archaeological fauna in two areas of the US, but will be readily extensible to other material classes

Base Ontologies for faunal data sets now under development by faunal experts include element and taxon and alternative ontologies for variables such as fragmentation, modification, and burning.

Ontology Tools. Tools for users to manage simple ontologies.

Column-Level Metadata. Dataset registration tools will solicit column-level metadata of the sort ordinarily contained in coding key sheets. With these tools, nominal values in a given dataset, (e.g., 036=jackrabbit) will be associated with concepts (e.g. “lepus”) in the knowledge base that are also linked to equivalent codes in other databases.

Concept-Oriented Search. In a concept-oriented search for “deer” bones, tDAR would use the identity association of the ontology concept “deer” with the concept “odocoileus” and the parent association of “odocoileus” with the several species of deer. It would further use the concept associations of these species with the arbitrary codes in the different databases to identify the data items that represent deer across databases.

Future Development

Extension of ontologies and tools to additional material domains, e.g., ceramics and lithics. This will require less software development, but considerable participation by groups of archaeologists to build material- and area-specific knowledge bases.

Improvement of data integration tools to deal in more sophisticated ways with archaeological contexts, including sampling considerations.

Extension of tDAR to accommodate resources distributed over the Internet (with tDAR maintaining the central portal and metadata catalog). Note that in contrast to distributed data sources, data deposited directly in tDAR will be assured long-term preservation.
Internationalization of tDAR with multilingual interfaces. tDAR’s use of ontologies will greatly simplify this task.

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This material is based upon work supported by the National Science Foundation under Grant Nos. 0433959 and 0624341. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.