Reusing published datasets on the Web is of great interest to researchers and developers. Their data needs may be met by submitting queries to a dataset search engine to retrieve relevant datasets. In this ongoing work towards developing a more usable dataset search engine, we characterize real data needs by annotating the semantics of 1,947 queries using a novel fine-grained scheme, to provide implications for enhancing dataset search. Based on the findings, we present a query-centered framework for dataset search, and explore the implementation of snippet generation and evaluate it with a preliminary user study.
@article{arxiv.1908.11146,
title = {Towards More Usable Dataset Search: From Query Characterization to Snippet Generation},
author = {Jinchi Chen and Xiaxia Wang and Gong Cheng and Evgeny Kharlamov and Yuzhong Qu},
journal= {arXiv preprint arXiv:1908.11146},
year = {2019}
}
Comments
4 pages, The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019)