Digital Antiquity
Data Integration with tDAR
The Digital Archaeological
Record:
The potentials of
archaeozoological data integration
through tDAR
Katherine Spielmann and Keith Kintigh
Arizona State University
ICAZ 2010
Digital Antiquity
Data Integration with tDAR
the Digital Archaeological Record,
.
• Web-based ingest interface: user/contributors
upload data and detailed metadata
• Provides long-term preservation of data &
metadata
• Web-based discovery and access for data and
documents produced by archaeological projects.
• Provide data integration across inconsistent
databases
Digital Antiquity
Data Integration with tDAR
A Bit of History
• Driven by need for synthetic research
• Genesis of the project (1999) was a long-term
collaboration of ASU archaeologists
• Frustrated by the difficulty of
• Obtaining data
• Integrating data that were collected using different
coding schemes by different investigators
• Teamed up with computer scientists and got funding
Digital Antiquity
Data Integration with tDAR
Data Ingest
Digital Antiquity
Data Integration with tDAR
Adding a Project
Digital Antiquity
Data Integration with tDAR
Enter Resource Metadata
Digital Antiquity
Data Integration with tDAR
Additional Metadata
• Collection Procedures:
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Sampling of site
Sampling of bone assemblage
Screen size
Context (room, trash, hearth, pit)
• Quality of faunal collection
• Weathering
• % identifiable
Digital Antiquity
Data Integration with tDAR
Upload Dataset
Digital Antiquity
Data Integration with tDAR
Enter Column Metadata and Attach Coding
Sheet
Digital Antiquity
Data Integration with tDAR
Coding Sheet Metadata
Digital Antiquity
Data Integration with tDAR
• Preserve the original data
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in original format
in a sustainable format (that can be migrated)
on sustainable media
no transformations of original file’s content
users can always download the data as recorded
• Preserve database semantics through
collection and dissemination of metadata
• Ensure users’ attribution of credit to creators
Digital Antiquity
Data Integration with tDAR
Creating General Faunal
Ontologies
Digital Antiquity
Ontologies
• Ontology is a map of the
semantic relationships
among a set of
concepts.
• In tDAR, ontologies are
ordinarily hierarchical
(tree-like) and represent
an arbitrary number of
levels of class-subclass
relationships
Data Integration with tDAR
Digital Antiquity
Data Integration with tDAR
Burning Intensity
First Level
Unburned
Probably
Burned
Burned
Indeterminate
Second Level
Calcined
Charred
Singed
Not
Recorded
Digital Antiquity
Data Integration with tDAR
Butchering
First Level
Not
Butchered
Probably
Butchered
Butchered
Indeterminate
Saw Marks
Chop
Marks
Second Level
Cut Marks
Not
Recorded
Digital Antiquity
Data Integration with tDAR
Ontologies in tDAR
Digital Antiquity
Data Integration with tDAR
Ontology Mapping
• For a variable to be integrated across
databases:
• The values for that variable in each
database are mapped to appropriate nodes
in the ontology tree
• Mapping preferably done by the original analyst
Digital Antiquity
Data Integration with tDAR
Ontology Mapping - Example
• Database 1
• Database has taxon value 107
• Its coding sheet says taxon 107 = “hare”
• Database 2
• Database has taxon value 237
• Coding sheet says 237 = “black-tailed
jackrabbit” described as “Lepus californicus”
Digital Antiquity
Data Integration with tDAR
Digital Antiquity
Data Integration with tDAR
Associate Coding Key With Ontology
Digital Antiquity
Data Integration with tDAR
Map Coding Key to Ontology
Upper Little Colorado Prehistory Project
Pueblo Blanco
Digital Antiquity
Data Integration with tDAR
Perform Data Integration:
Pilot Analysis
Digital Antiquity
Data Integration with tDAR
Zuni
Salinas
Digital Antiquity
Data Integration with tDAR
tDAR Integration
• User queries tDAR to identify databases
• Mark databases to go in user workspace
• Select tables to integrate
Digital Antiquity
Data Integration with tDAR
Workspace with Bookmarked Databases
Digital Antiquity
Data Integration with tDAR
Select Tables to Integrate
Digital Antiquity
Data Integration with tDAR
Select Data Table Columns to Integrate
Digital Antiquity
Data Integration with tDAR
Specify Aggregation and Filtering
Digital Antiquity
Data Integration with tDAR
Output
• Output Database
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observations from both datasets
integration uses common ontology values
filtering eliminates cases
aggregation for consistency and analytical
simplicity
• Database is downloaded and analyzed
by user.
Digital Antiquity
Data Integration with tDAR
Integration Output - Species Only
Digital Antiquity
Data Integration with tDAR
Integration Output – Species & Element
Digital Antiquity
Data Integration with tDAR
Output Spreadsheet – 2 Sheets
Digital Antiquity
Data Integration with tDAR
Output Spreadsheet - Combined
Digital Antiquity
Data Integration with tDAR
Data Table – From SPSS
Species code * DatasetTable Crosstabulation
DatasetTable
PB
Species code
Artiodactyl
Count
5856
7944
40.9%
29.2%
31.6%
26
0
26
.5%
.0%
.1%
31
66
97
% within DatasetTable
.6%
.3%
.4%
Count
153
698
851
% within DatasetTable
3.0%
3.5%
3.4%
Count
2811
13414
16225
55.0%
67.0%
64.5%
5109
20034
25143
100.0%
100.0%
100.0%
Count
% within DatasetTable
Canid
Turkey
Lagomorph
Count
% within DatasetTable
Total
Total
2088
% within DatasetTable
Bos/bison
UCLPP
Count
% within DatasetTable
Digital Antiquity
Data Integration with tDAR
Resource Depression/Overhunting
• How recognize?
• Changing prey abundances
• % NISP of large and small taxa
• index ratios of large versus small taxa
• Is small game anthropogenic
• Burning
Digital Antiquity
Data Integration with tDAR
• Change in prey demographics
• Age of prey
• Fusion
• Change in element frequencies of
large game (transport)
• FUI
• Increased processing of large game
• Condition (% complete)
• Weight
Digital Antiquity
Data Integration with tDAR
Acknowledgments
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Andrew W. Mellon Foundation
National Science Foundation
National Endowment for the Humanities
UK Joint Information Systems Committee
Archaeology Data Service, University of York
Digital Antiquity Board of Directors
Sander van der Leeuw, Arizona
State University (ASU) [chair]
Carol Ackerson, Girl Scouts
Arizona Cactus-Pine Council
Jeffrey Altschul, SRI Foundation
Kim Bullerdick, Owner, BI, L.L.C.
John Howard, University College,
Dublin
Keith Kintigh, ASU
Tim Kohler, Washington State
University
Fred Limp, University of Arkansas
Harry Papp, L. Roy Papp & Associates
Julian Richards, University of York
Dean Snow, The Pennsylvania State
University
Digital Antiquity
Data Integration with tDAR
Questions?
http://tdar.org