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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History, Grants & Partners

Our first NSF grant funded a December 2004 workshop that provided a vision for the infrastructure and suggested a number of design requirements. The workshop’s full report was published in American Antiquity (July 2006) and has been endorsed by the Society for American Archaeology, the Society for Historical Archaeology, and the American Association of Physical Anthropologists. The workshop included 31 individuals including archaeologists with diverse interests, computer scientists, and domain scientists associated with other science informatics projects.

Our current NSF grant funds development of the pilot infrastructure with the participation of a working group of archaeologists with expertise in faunal analysis. This working group is assisting by adding numerous faunal datasets from the Midwest and Southwest to tDAR and will test and help refine its capabilities in the context of research using tDAR on substantive questions of resource depression.

A grant from the Andrew W. Mellon Foundation led to the creation of archaeoinformatics.org, a partner organization to tDAR. This organization is following up the NSF workshop recommendations to develop a sociologically attractive, technologically feasible, and financially sustainable plan for the organization and operation of a cyberinfrastructure for archaeology. It is led by Keith Kintigh (Arizona State University), Chris Dore (Statistical Research, Inc.), Tim Kohler (Washington State U.), Fred Limp (U. of Arkansas), and Dean Snow (Penn State U.)

Principal Investigators: Keith W. Kintigh, K. Selçuk Candan, Hasan Davulcu, Subbarao Kambhampati, Margaret C. Nelson, and Katherine A. Spielmann
Key ASU Collaborators: Huiping Cao, John Howard, Allen Lee, Mallorie Hatch, Yan Qi, and Ben Schoville
Supported by: NSF Grants SES 0433959 and IIS 0624341 and a Grant from the Andrew W. Mellon Foundation

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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.