This repository contains the source code and data to produce the Data in Brief article entitled "From Archives to AI: Residential Property Data Across Three Decades in Brunei Darussalam". For attribution, please cite this work as:
H. Jamil, A. Barizah Noorosmawie, H. Waezz Rabu, L. Abdul Razak, From Archives to AI: Residential Property Data Across Three Decades in Brunei Darussalam, Manuscript in Submission (2025). https://github.com/Bruneiverse/house-data.
BibTeX citation:
@article{jamil2025archives,
author = {Jamil, Haziq and Barizah Noorosmawie, Amira and Waezz Rabu,
Hafeezul and Abdul Razak, Lutfi},
title = {From {Archives} to {AI:} {Residential} {Property} {Data}
{Across} {Three} {Decades} in {Brunei} {Darussalam}},
journal = {Manuscript in Submission},
date = {2025},
url = {https://github.com/Bruneiverse/house-data},
langid = {en},
abstract = {This article introduces the first publicly available data
set for analysing the Brunei housing market, covering more than
30,000 property listings from 1993 to early 2025. The data set,
curated from property advertisements in newspapers and online
platforms, includes key attributes such as price, location, property
type, and physical characteristics, enriched with area-level spatial
information. Comprehensive and historical, it complements the Brunei
Darussalam Central Bank’s Residential Property Price Index (RPPI),
addressing the limitations of restricted access to raw RPPI data and
its relatively short timeline since its inception in 2015. Data
collection involved manual transcription from archival sources and
automated web scraping using programmatic methods, supported by
innovative processing with Large Language Models (LLMs) to codify
unstructured text. The data set enables spatial and temporal
analysis, with potential applications in economics, urban planning,
and real estate research. Although listing prices are only a proxy
for market values and may deviate from actual sale prices due to
negotiation dynamics and other factors, this data set still provides
a valuable resource for quantitative analyses of housing market
trends and for informing policy decisions.}
}