Assessing quantitative methods in archaeology via simulated datasets: The Archaeoriddle challenge. Concept, project and motivations Article Swipe
Alfredo Cortell‐Nicolau
,
Simon Carrignon
,
I. Rodíguez-Palomo
,
Daniel Devatman Hromada
,
R. Kahlenberg
,
A. Mes
,
Deborah Priß
,
Paul J. Yaworsky
,
Xiutang Zhang
,
Leah M. Brainerd
,
Jason Lewis
,
DI Redhouse
,
Christopher S. Simmons
,
María Coto-Sarmiento
,
Devin Daems
,
Aniruddha Deb
,
D. Lawrence
,
Michael J. O’Brien
,
Felix Riede
,
Xavier Rubio‐Campillo
,
Enrico R. Crema
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.jas.2025.106179
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.jas.2025.106179
Compared to what is found in many other scientific disciplines, archaeological data are typically scarce, biased and fragmented. This, coupled with the fact that archaeologists can rarely test their hypotheses using experimental design, makes archaeological inference and our ability to assess the robustness of quantitative methods used to make such inferences challenging. Archaeoriddle is a project that was born as an attempt to compare archaeological methods in an artificial scenario where the behaviour to be reconstructed was known. In this project we organised an experiment where a virtual archaeological record generated from a simulated interaction between hunter–gatherers and early farmers in a fictional landscape was shared with interested participants. Three archaeological questions were posed and the participants were challenged to answer them with the data that the developer team made available. The model and the generative processes behind the virtual record were known to the developers of the virtual world (Rabbithole) but not to the participants. Additionally, players were allowed to sample only a subset of the data from Rabbithole, mimicking real-life archaeological research and sampling efforts. The long-term aim of the project is to assess how different methods performed under a controlled environment since, in this case, we knew the correct answers to the questions posed. This experience provided us with some insights into (1) how efficient various archaeological methods are in answering complex questions; (2) the degree of interest from archaeologists in improving their analytical techniques; and (3) the potential of archaeological method when free from external constraints (e.g. budget, fieldwork, etc.).
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jas.2025.106179
- OA Status
- hybrid
- Cited By
- 2
- References
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- Related Works
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- OpenAlex ID
- https://openalex.org/W4407850066
All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1016/j.jas.2025.106179Digital Object Identifier
- Title
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Assessing quantitative methods in archaeology via simulated datasets: The Archaeoriddle challenge. Concept, project and motivationsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-02-22Full publication date if available
- Authors
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Alfredo Cortell‐Nicolau, Simon Carrignon, I. Rodíguez-Palomo, Daniel Devatman Hromada, R. Kahlenberg, A. Mes, Deborah Priß, Paul J. Yaworsky, Xiutang Zhang, Leah M. Brainerd, Jason Lewis, DI Redhouse, Christopher S. Simmons, María Coto-Sarmiento, Devin Daems, Aniruddha Deb, D. Lawrence, Michael J. O’Brien, Felix Riede, Xavier Rubio‐Campillo, Enrico R. CremaList of authors in order
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https://doi.org/10.1016/j.jas.2025.106179Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.jas.2025.106179Direct OA link when available
- Concepts
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Archaeology, Computer science, Data science, GeographyTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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