ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution

TL;DR

ICE-ID is a comprehensive historical census dataset from Iceland covering 220 years, designed to advance longitudinal identity resolution with unique challenges like hierarchical geography and naming conventions.

Contribution

The paper introduces ICE-ID, a novel, large-scale dataset for long-term identity resolution, including detailed analysis and tools for benchmarking and research.

Findings

Dataset covers 220 years of Icelandic census data.

Includes hierarchical geography and kinship links.

Provides baseline models and analysis artifacts.

Abstract

We introduce \textbf{ICE-ID}, a benchmark dataset comprising 984,028 records from 16 Icelandic census waves spanning 220 years (1703--1920), with 226,864 expert-curated person identifiers. ICE-ID combines hierarchical geography (farm$\to$parish$\to$district$\to$county), patronymic naming conventions, sparse kinship links (partner, father, mother), and multi-decadal temporal drift -- challenges not captured by standard product-matching or citation datasets. This paper presents an artifact-backed analysis of temporal coverage, missingness, identifier ambiguity, candidate-generation efficiency, and cluster distributions, and situates ICE-ID against classical ER benchmarks (Abt--Buy, Amazon--Google, DBLP--ACM, DBLP--Scholar, Walmart--Amazon, iTunes--Amazon, Beer, Fodors--Zagats). We also define a deployment-faithful temporal OOD protocol and release the dataset, splits, regeneration scripts, analysis artifacts, and a dashboard for interactive exploration. Baseline model comparisons and end-to-end ER results are reported in the companion methods paper.