Patterns in ink khipus are linked to size and cataloging factors
Structural Pattern Mining in Inka Khipus: A KFG Re-Analysis
Computation and LanguageMachine Learning
Summary
The paper looks again at hundreds of Inka khipus, which are knotted strings used for record-keeping, by switching to a different database after running into problems with the first. The researchers found that the size of a khipu affects many measurements and must be taken into account. They also discovered that the naming codes on khipus relate to who cataloged them rather than when or where they come from, which influences data completeness. Lastly, they tried grouping khipus based on structure but found these patterns similar to random data, meaning strong structural groupings are hard to confirm.
What this means in practice
- •For digital archivists: Improve digital cataloging systems for khipu records by incorporating size and cataloger-based adjustments to reduce bias in structural analyses.
- •For cultural heritage data teams: Refine detection methods for calendar-related khipus by applying validated spatial-block heuristics to identify candidate artifacts more accurately.
Authors
Maria Contreras
Abstract
This paper reports a methodological pivot from the Open Khipu Repository to the Khipu Field Guide (KFG) database, prompted by stalled progress on the OKR, and a full re-analysis of the resulting 650-khipu sample. Three findings recur across every analysis attempted. First, khipu size confounds nearly every derived structural count, explaining 42-70% of its variance; all subsequent models control for it. Second, the two-letter name prefix (AS, UR, HP, QU, JC, MM, KH) identifies the original cataloger, not a site or period, which turns documentation completeness into a second confound that must be modeled explicitly. Controlling for both, khipus cataloged by Hugo Pereyra's Proyecto Quipu (HP) show significantly fewer Ascher sum-relation types than Gary Urton's (UR) khipus (p = 0.044), while the Ascher-cataloged (AS) khipus are too collinear with their own near-total lack of side/direction documentation to assess (VIF = 5.0). Third, generic structural clustering (UMAP+HDBSCAN) does not separate the pooled 650-khipu sample from two independent null models (permutation and Gaussian), corroborating an independent conclusion already reached by the KFG itself; the same test restricted to a single cataloger (UR) proved not reproducible across runtime environments and is reported here as a methodological caveat rather than evidence of structure. A targeted replication of the KFG's own S/Z-knot spatial-block heuristic for calendar/astronomical khipus recovers 8 of 10 published candidates and proposes 34 additional ones under the same criterion.