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Table · dataset · 2026

Data for: Behavioral architecture for social resilience in a eusocial mammal

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This repository accompanies the paper "Behavioral architecture for social resilience in a eusocial mammal" (Burger, Hart, Kretschmer, Bennett & Barker, 2026) and contains the complete analysis pipeline — code and data together — used to generate every published figure, table, and statistic.

Description

At its core is a SQLite database of long-term radio-frequency identification (RFID) tracking data and derived behavioral/social-network measures from seven captive naked mole-rat (Heterocephalus glaber) colonies — four housed at the Max Planck Institute for Brain Research (Frankfurt, Germany) and three at the University of Pretoria (South Africa) — comprising 141 animals (136 included in baseline behavioral analyses after pre-registered exclusions) tracked continuously for periods ranging from weeks to over a year between 2023 and 2026.

Individual positions within each colony's tunnel system were reconstructed from RFID antenna detections at sub-second resolution using the moleRAT tracking algorithm, whose code is included. From these trajectories, the database stores (1) per-individual movement features — distance traveled, path-length statistics, number of unique paths, proportion of active time, movement-bout counts, location entropy, expected subgroup size — and (2) seven weighted, time-resolved dyadic social networks computed per weekly analysis window: time spent together, time spent together while active/inactive, simultaneous activity, passing interactions, spatial closeness, and following, along with individual-level network centrality (PageRank, degree).

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The database also includes colony composition and demographic metadata (sex, date of birth, body mass over time) and experimental-design metadata marking habituation, baseline, and post-removal periods for five colonies in which two non-breeding individuals were experimentally removed to test social resilience. Alongside the database, the repository includes the Python pipeline that builds it from raw RFID hardware output and derives the behavioral and network features; R scripts that reproduce every published figure and statistic (pre-exported CSVs are included so figures can be regenerated without re-running the Python pipeline); and a tracking-accuracy validation notebook with its supporting raw data and manual video annotations.

READMEs at the repository root and alongside the database describe the folder structure and database schema, and give quick-start examples in Python, R, and the SQLite command line.

Links

Where it is published

Catalogue records · 1

Topics

Stated by source
Biology · Biology
Inferred from text
Tabular 65% · Video 75% · Zoology 74%
Provenance · 2 source records, 28 field assertions
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