Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-25T01:12:54.009Z Has data issue: false hasContentIssue false

Ethics and Best Practices for Mapping Archaeological Sites

Published online by Cambridge University Press:  29 May 2020

Cecilia Smith*
Affiliation:
University of Chicago Library, University of Chicago, 1100 East 57th Street, Chicago, IL60637, USA

Abstract

Archaeologists are tasked with balancing a call to open data and the need to maintain confidentiality of sensitive archaeological site locations. Low-resolution mapping and data aggregation are the methods most commonly used to hide site locations; however, we understand little of the effectiveness of these practices. Trends in geomasking, obscuring observed geographic points, to anonymize public health data are suggested as a source of methods for sharing archaeological site data. Archaeologists have available to them a number of geomasking methods that balance open data and site security in different ways. Low-resolution mapping at several scales and random direction with fixed radius, random perturbation donut, and Gaussian donut techniques are tested on a set of archaeological site locations. Random perturbation donuts resulted in the best balance between obscuring archaeological locations and conveying observed spatial patterning. Researchers should carefully consider how they convey archaeological location data, as commonly used low-resolution scales may not provide the desired level of obscurity. Researchers should also be explicit as to how and why their methods of site visualization are chosen.

Los arqueólogos tienen la tarea de equilibrar un llamamiento a las prácticas de datos abiertos y de mantener la confidencialidad de sitios arqueológicos sensibles. La cartografía de baja resolución y la agregación de datos son los métodos más utilizados para ocultar los lugares de los sitios; sin embargo, entendemos poco de la eficacia de estas prácticas. Se sugieren tendencias en el enmascaramiento de la ubicación, el ocultamiento de puntos geográficos observados, para anonimizar los datos de salud pública como fuente de métodos para compartir los datos de los sitios arqueológicos. Los arqueólogos tienen a su disposición una serie de métodos de enmascaramiento de la ubicación que equilibran los datos abiertos y la seguridad del sitio de diferentes maneras. En un conjunto de emplazamientos de sitios arqueológicos se ensayan técnicas de cartografía de baja resolución a varias escalas, dirección aleatoria con radio fijo, rosquillas de perturbación aleatoria y de rosquilla gaussiana. Las rosquillas de perturbación aleatoria dieron como resultado el mejor equilibrio entre el ocultamiento de los sitios arqueológicos y la transmisión de los patrones espaciales observados. Los investigadores deben considerar cuidadosamente cómo transmiten los datos de los emplazamientos arqueológicos, ya que las escalas de baja resolución comúnmente utilizadas podrían no proporcionar el nivel de ocultamiento deseado. Los investigadores también deben ser explícitos en cuanto a cómo y por qué se escogen sus métodos de visualización de los sitios.

Type
Articles
Copyright
Copyright 2020 © Society for American Archaeology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES CITED

Advisory Council on Historic Preservation 2016 Frequently Asked Questions on Protecting Sensitive Information about Historical Properties under Section 204 of the NHPA. Electronic document, https://www.achp.gov/digital-library-section-106-landing/frequently-asked-questions-protecting-sensitive-information, accessed January 8, 2019.Google Scholar
Allshouse, William B., Fitch, Molly K., Hampton, Kristen H., Gesink, Dionne C., Doherty, Irene A., Leone, Peter A., Serre, Marc L., and Miller, William C. 2010 Geomasking Sensitive Health Data and Privacy Protection: An Evaluation Using an E911 Database. Geocarto International 25:443452.CrossRefGoogle ScholarPubMed
Anderson, David, Bissett, Thaddeus G., Yerka, Stephen J., Wells, Joshua J., Kansa, Eric C., Kansa, Sarah W., Myers, Kelsey Noack, Carl DeMuth, R., and White, Devin A. 2017 Sea-Level Rise and Archaeological Site Destruction: An Example from the Southeastern United States Using DINAA (Digital Index of North American Archaeology). PLoS ONE 12(11):e0188142.CrossRefGoogle Scholar
Anderson, David, Kansa, Eric, Kansa, Sarah, Yerka, Stephen, and Wells, Joshua 2011 Developing the Cyberinfrastructure for a National Archaeological Site Database. Electronic document, http://ux.opencontext.org/wp-content/uploads/2012/09/DINAA-NASD-Technical-Proposal-2011.pdf, accessed August 8, 2019.Google Scholar
Boulos, Maged N. Kamel, Andrew J.Curtis, and Philip AbdelMalik, 2009 Musings on Privacy Issues in Health Research Involving Disaggregate Geographic Data about Individuals. International Journal of Health Geographics 8:article 46. DOI:10.1186/1476-072X-8-46.CrossRefGoogle ScholarPubMed
Brownstein, John S., Cassa, Christopher A., Kohane, Isaac S., and Mandl, Kenneth D. 2006 An Unsupervised Classification Method for Inferring Original Case Locations from Low-Resolution Disease Maps. International Journal of Health Geographics 5:article 56. DOI:10.1186/1476-072X-5-56.CrossRefGoogle ScholarPubMed
Brownstein, John S., Cassa, Christopher A., and Mandl, Kenneth D. 2006 No Place to Hide: Reverse Identification of Patients from Published Maps. New England Journal of Medicine 355:17411742.CrossRefGoogle ScholarPubMed
Clarke, Keith C. 2016 A Multiscale Masking Method for Point Geographic Data. International Journal of Geographical Information Science 30:300315.CrossRefGoogle Scholar
Congressional Research Service 2018 The Geospatial Data Act of 2018. Electronic document, https://crsreports.congress.gov/product/pdf/R/R45348, accessed April 9, 2020.Google Scholar
Costa, Stefano, Beck, Anthony, Bevan, A. H., and Ogden, Jessica 2013 Defining and Advocating Open Data in Archaeology. In Proceedings of the 40th Annual Conference of Computer Applications and Quantitative Methods in Archaeology, pp. 449456. Amsterdam University Press, Amsterdam, the Netherlands.Google Scholar
Croft, William Lee, Shi, Wei, Sack, Jörg-Rüdiger, and Corriveau, Jean-Pierre 2016 Location-Based Anonymization: Comparison and Evaluation of the Voronoi-Based Aggregation System. International Journal of Geographical Information Science 30:22532275.CrossRefGoogle Scholar
Digital Index of North American Archaeology 2013 DINAA Sensitive Data Security Measures and SHPO Collaboration. Electronic document, http://ux.opencontext.org/archaeology-site-data/dinaa-sensitive-data-security-measures-and-shpo-collaboration/, accessed August 8, 2019.Google Scholar
Esri and TomTom North America 2019 USA State Boundaries. Electronic document, https://www.arcgis.com/home/item.html?id=540003aa59b047d7a1f465f7b1df1950, accessed February 7, 2019.Google Scholar
Fronterrè, Claudio, Giorgi, Emanuele, and Diggle, Peter 2018 Geostatistical Inference in the Presence of Geomasking: A Composite-Likelihood Approach. Spatial Statistics 28:319330.CrossRefGoogle Scholar
GlobalXplorer° 2019 Frequently Asked Questions. Electronic document, https://www.globalxplorer.org/faq, accessed April 9, 2020.Google Scholar
GRASS GIS 2020 GRASS GIS 7.8.2. GRASS Development Team. Electronic document, http://grass.osgeo.org, accessed February 5, 2020.Google Scholar
Hampton, Kristen H., Fitch, Molly K., Allshouse, William B., Doherty, Irene A., Gesink, Dionne C., Leone, Peter A., Serre, Marc L., and Miller, William C. 2010 Mapping Health Data: Improved Privacy Protection with Donut Method Geomasking. American Journal of Epidemiology 172:10621069.CrossRefGoogle ScholarPubMed
Huggett, Jeremy 2014 Promise and Paradox: Accessing Open Data in Archaeology. In Proceedings of the Digital Humanities Congress 2012, by Mills, Clare, Pidd, Michael, and Ward, Esther. Studies in the Digital Humanities. Digital Humanities Institute, Sheffield, UK. https://www.dhi.ac.uk/openbook/chapter/dhc2012-huggett, accessed April 9, 2020.Google Scholar
Kounadi, Ourania, and Leitner, Michael 2014 Spatial Information Divergence: Using Global and Local Indices to Compare Geographical Masks Applied to Crime Data. Transactions in GIS 19:737757.CrossRefGoogle Scholar
Kounadi, Ourania, and Resch, Bernd 2018 A Geoprivacy by Design Guideline for Research Campaigns That Use Participatory Sensing Data. Journal of Empirical Research on Human Research Ethics 13:203222. DOI:10.1177/1556264618759877.CrossRefGoogle ScholarPubMed
McCoy, Mark D. 2017 Geospatial Big Data and Archaeology: Prospects and Problems Too Great to Ignore. Journal of Archaeological Science 84:7494.CrossRefGoogle Scholar
National Geographic Society and i-cubed 2019 USA Topo Maps. Electronic document, https://www.arcgis.com/home/item.html?id=99cd5fbd98934028802b4f797c4b1732, accessed February 7, 2020.Google Scholar
NPS (National Park Service) 1997 Secretary of the Interior's Standards for Archeological Documentation. In Archeology and Historic Preservation: Secretary of the Interior's Standards and Guidelines. Electronic document, https://www.nps.gov/history/local-law/arch_stnds_7.htm, accessed April 9. 2020.Google Scholar
NPS (National Park Service) 2014 Cultural Resource Spatial Data Transfer Standards: Guidelines for Use and Implementation. Cultural Resource GIS Facility, Preservation Assistance Programs. Electronic document, https://irma.nps.gov/Datastore/DownloadFile/489140, accessed February 5, 2020.Google Scholar
NPS (National Park Service) 2019 Draft Set of Standards for Cultural Resource Spatial Data. Cultural Resource Geographic Information System Facility, Heritage Documentation Programs. Electronic document, https://www.nps.gov/hdp/standards/crgisstandards.htm, accessed February 5, 2020.Google Scholar
Proulx, Blythe Bowman 2013 Archaeological Site Looting in “Glocal” Perspective: Nature, Scope, and Frequency. American Journal of Archaeology 117:111125.CrossRefGoogle Scholar
Seidl, Dara E., Jankowski, Piotr, and Clarke, Keith C. 2017 Privacy and False Identification Risk in Geomasking Techniques. Geographical Analysis 50:280297.CrossRefGoogle Scholar
Seidl, Dara E., Jankowski, Piotr, and Nara, Atsushi 2018 An Empirical Test of Household Identification Risk in Geomasked Maps. Cartography and Geographic Information Science 46. DOI:10.1080/15230406.2018.1544932.Google Scholar
Smith, Kimbra L. 2005 Looting and the Politics of Archaeological Knowledge in Northern Peru. Ethnos 70:149170.CrossRefGoogle Scholar
Strupler, Néhémie, and Wilkinson, Toby C. 2017 Reproducibility in the Field: Transparency, Version Control and Collaboration on the Project Panormos Survey. Open Archaeology 3:279304.CrossRefGoogle Scholar
University of Wyoming Department of Geography, Wyoming Geographic Information Science Center, and Wyoming Geographic Alliance 2017 Selected Archaeological Sites in Wyoming (2013). In Wyoming Student Atlas Online. Electronic document, https://www.arcgis.com/home/item.html?id=6b4e33541a8a4338b7be994396df669c, accessed August 8, 2019.Google Scholar
Wieland, Shannon C., Cassa, Christopher A., Mandl, Kenneth D., and Berger, Bonnie 2008 Revealing the Spatial Distribution of a Disease while Preserving Privacy. Proceedings of the National Academy of Sciences of the United States of America 105:1760817613.CrossRefGoogle ScholarPubMed
Zandbergen, Paul A. 2014 Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data. Advances in Medicine 2014. DOI:10.1177/1556264618759877.CrossRefGoogle ScholarPubMed
Zhang, Su, Freundschuh, Scott M., Lenzer, Kate, and Zandbergen, Paul A. 2017 The Location Swapping Method for Geomasking. Cartography and Geographic Information Science 44:2234.CrossRefGoogle Scholar
Supplementary material: File

Smith supplementary material

Smith supplementary material

Download Smith supplementary material(File)
File 62 KB