  Several recently published papers in Decision Support Systems discussed
issues related to data quality in Information Systems research. In this short
research note, I build on the work introduced in these papers and document two
data quality issues discovered in a large open dataset commonly used in
research. Inside Airbnb (IA) collects data from places and reviews as posted by
users of Airbnb.com. Visitors can effortlessly download data collected by IA
for several locations around the globe. While the dataset is widely used in
academic research, no thorough investigation of the dataset and its validity
has been conducted. This note examines the dataset and explains an issue of
incorrect data added to the dataset. Findings suggest that this issue can be
attributed to systemic errors in the data collection process. The results
suggest that the use of unverified open datasets can be problematic, although
the discoveries presented in this work may not be significant enough to
challenge all published research that used the IA dataset. Additionally,
findings indicate that the incorrect data happens because of a new feature
implemented by Airbnb. Thus, unless changes are made, it is likely that the
consequences of this issue will only become more severe. Finally, this note
explores why reproducibility is a problem when two different releases of the
dataset are compared.
