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The study of socioeconomic status has been reformed by the availability ofdigital records containing data on real estate, points of interest, traffic andsocial media trends such as micro-blogging. In this paper, we describe aheterogeneous, multi-source, multi-modal, multi-view and multi-distributionaldataset named "H4M". The mixed dataset contains data on real estatetransactions, points of interest, traffic patterns and micro-blogging trendsfrom Beijing, China. The unique composition of H4M makes it an ideal test bedfor methodologies and approaches aimed at studying and solving problems relatedto real estate, traffic, urban mobility planning, social sentiment analysisetc. The dataset is available at: https://indigopurple.github.io/H4M/index.html

H4M: Heterogeneous, Multi-source, Multi-modal, Multi-view and Multi-distributional Dataset for Socioeconomic Analytics in the Case of Beijing