Cultural data markets: Interpreting the popularity of public datasets

Abstract

Data markets are critical sites that organize access to data products, such as datasets. This study argues that data markets increasingly operate as digital platforms for cultural production, where the logic of popularity shapes the cultural value of datasets. We conceptualize these shifts by analyzing how dataset valuation operates within cultural data markets. Through statistical and forensic qualitative analysis, we examine key content features of the most popular public datasets on the data science platform Kaggle and their relationship to different popularity metrics. We find that the logic of popularity establishes a value structure that relies on quantifiable user–dataset interactions, which obfuscates key aspects of data curation and collaboration for assessing the cultural value of datasets. Dataset popularity remains a limited approach for data valuation in cultural markets that requires more comprehensive measures of cultural investments in dataset production.