Google Dataset Search by the Numbers

TL;DR

This paper analyzes the growth and characteristics of datasets indexed by Google's Dataset Search, highlighting its scale, diversity, and potential for improving data discoverability on the Web.

Contribution

It provides the largest analysis of schema.org-described datasets, revealing trends, gaps, and future directions for dataset discoverability.

Findings

Number of datasets grew from 500K to 30M since 2016

Datasets cover diverse topics and formats

Insights into user search interests and data gaps

Abstract

Scientists, governments, and companies increasingly publish datasets on the Web. Google's Dataset Search extracts dataset metadata -- expressed using schema.org and similar vocabularies -- from Web pages in order to make datasets discoverable. Since we started the work on Dataset Search in 2016, the number of datasets described in schema.org has grown from about 500K to almost 30M. Thus, this corpus has become a valuable snapshot of data on the Web. To the best of our knowledge, this corpus is the largest and most diverse of its kind. We analyze this corpus and discuss where the datasets originate from, what topics they cover, which form they take, and what people searching for datasets are interested in. Based on this analysis, we identify gaps and possible future work to help make data more discoverable.