Complexity and Confidentiality: GIS Data Management in Cultural Resources

August 21, 2019

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Archaeology and cultural resources are both fascinating and frustrating fields in which to do GIS. The fascination lies in the excitement of telling so many untold stories, and the potential of so many stories still to come. The frustration is how to manage all of these data to make them geographically discoverable and usable.

In April, I visited several national parks and monuments in Arizona, where I met with cultural resource managers and GIS specialists. Despite their small sizes, National Park Service sites can serve as laboratories for cultural resource data development with GST. By preserving and studying small but important places, much can be learned about our natural and cultural history.

From Development to Deployment

The NPS protects over 400 sites honoring America’s greatest treasures. Some are natural wonders; others are of historical significance. Nearly all of these places have a connection to our human heritage. Among all federal land management agencies, this connection makes the NPS unique in its mission.

Consequently, when the Department of Interior began to develop enterprise data standards, the cultural resource data standards were assigned to the NPS. Two standards were developed: one for all cultural resources, including archaeological sites and surveys, and one specifically for buildings, many of which are also cultural resources.

As with all data models, these were subject to much discussion and revision. Both models were built in an ArcGIS geodatabase with unique IDs for each feature, multiple domains and subtypes, and many related tables. The development and population of the GDB proved challenging; it took me months to build it for Crater Lake National Park. In theory though, once built, it would be easy to deploy and edit, both on the desktop and in the field.

In 2005 came the opportunity and necessity to test the efficacy of this model. Immediately after Hurricane Katrina slammed into New Orleans, recovery efforts began. Mapping the destruction was a critical element in recovery operations. When FEMA initiated the Incident Command System, thousands of responders were deployed from dozens of agencies. Assessing damage to structures in this metropolis of a half-million people was an enormous task.

GST was essential in this operation. The buildings data model developed by the NPS was used with ArcPad on mobile devices to record building locations and conditions, as well as for navigation. With so many places flooded and unrecognizable, having a location-aware data collection system was essential. While spatial accuracy varied with the devices used, all information was in a common data structure that was incorporated into an enterprise database that was subsequently used for many recovery efforts, including those by the American Red Cross.

Database Adaptability is Critical

Katrina was a success in terms of GST deployment on an urgent incident. That was in the built environment. However, cultural resources span millennia, from ancient rock carvings to modern structures and vast landscapes, many of which, like Glen Canyon National Recreation Area, have never been systematically explored for cultural resources.

GLCA’s 2,000 square miles of rugged and diverse landscapes reach from Arizona to Utah with recreational opportunities, geologic wonders, and a vast panorama of human history. As is the case with many NPS units, there are potential conflicts between preservation and recreation, both of which are components of the NPS mission.

Off-highway vehicle use is popular at GLCA. To balance recreation and preservation, park staff developed a cultural resource stewardship plan to protect these resources. Leveraging R software with a Random Forests Model, GIS staff and archaeologists built rasters of potential archaeological site areas, which included site types and landscape variables which were used in park planning.

A resilient data model needs to be flexible and adaptable for multiple purposes and missions. At CRLA, I modified the NPS CRGIS data model for more efficient data entry. I had an intern whose primary task was to turn a paper map into a digital database. There was a time crunch, so the geodatabase had to be populated quickly from a very comprehensive paper map. (Never underestimate the value of paper maps)! Although the data model was simplified, it still allowed for cross-connections to the NPS data standards, which could be accomplished later, after the field season.

This illustrates one of the challenges for CR data as well as all other data: connecting to other databases. A single resource, such as a historic building or an ancient ball court, can have records in the Archaeological Sites Management System, the Facility Management Software System, and each state’s State Historic Preservation Office, as well as the national database.

Database design is a field unto itself, but lessons learned from my experiences are that a well-vetted and adaptable data schema is critical, and that the work involved in development is worth it. Unique IDs and pivot fields are likewise critical. However, this only works if the people building and populating the database are competent and committed.

It’s All About the Data

“Some things you just can’t farm out,” GIS Specialist Mark Nebel at Grand Canyon National Park advised me. In an effort to validate spatial locations for an already-existing spatial database, GRCA used interns from the local university and museum. Without direct oversight from the NPS, the results were disappointing, and NPS staff spent two years cleaning up the errors.

Along with the elements of human fallibility and multiple databases, there is also environmental variability. “Hard” resources, like buildings and ruins, are relatively stable. But “soft” resources, such as pictographs, lithic scatters and wooden remains, can be easily compromised by fire, flood or aeolian erosion. However, disturbances can also lead to discoveries. A wildfire at Lava Beds National Monument opened up the brush-covered surface, revealing previously undiscovered sites.

Fortunately, GST can mitigate these factors somewhat. We were searching for a known but unlocated site along CRLA’s historic rim road, the “Last Water Site,” where the old cars would refill their radiators before the last steep climb up the mountain. After arduous surveys to no avail, we turned to LIDAR. It still took ground-pounding to locate the actual site, but GST had narrowed the search area significantly. There it was!

Immediacy and Confidentiality

Another challenge of CR data management is confidentiality. Nobody is likely to steal a historic building or the collection of bent pipes we found above, but other resources, such as pottery, arrowheads and, sadly, human remains, have a greater attraction.

Therefore, unlike much GIS data, CR data requires confidentiality. The paradox is that if you can’t locate it, you can’t protect it, but if too many people know the location of these sites and artifacts, they could be compromised.

READ is the duty code for REsource ADvisor. READs work with responders on fires, hurricanes and other events to mitigate impacts to sensitive resources. Distribution of a READ map requires a delicate balancing act. In order for a resource to be protected, its location must be known, so responders need accurate maps. While nearly all incident staff are conscientious about protecting these resources, in this digital age, data is very easily distributed.

To mitigate this, some READ supervisors require a check-out and check-in of each paper map. In other places, rangers use Collector to record sensitive sites and monitor their condition. In both cases, READs and rangers can also contribute new data. Unexplored areas may be surveyed, and as in the case of LABE above, fires may reveal unfound sites.

Academic Studies

When I was an archaeology student in the 90s, we didn't cover mapping very much beyond the site level. Now the geography and anthropology programs share the same building and there is amazing crossover between these disciplines. Academic archaeologists embraced GST long before it was deployed in the field, and they are the cutting edge in analysis and predictive modeling.

Interestingly, though, not all geographic anthropologists use maps as their primary tool. Instead, they begin with geographic data, then develop models and hypotheses to build a schematic that may illustrate geographic connectivity, as in this example of using ceramic analysis to identify social networks in prehistoric Appalachia.

Like all disciplines, archaeology seeks to reveal the unknown. Whether in archaeology, journalism, or astronomy, GST is an essential tool for discovering the yet-undiscovered. However, mapping cultural resources isn’t only uncovering the past. As our past has defined our present, so will our present define our future. Whether mapping the ancestry of cultures that still thrive today, like Wupatki National Monument, or using data models to map real-time events like Katrina, geography helps turn many small stories into a much bigger story.

While not as glamorous or exciting as field work, developing robust, agile data structures and having good quality control are critical to documenting these stories. As they say, “Garbage in, garbage out.” A model or map is only as good as the data that goes into it. 

Read other articles by Chris Wayne


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