ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2017, Vol. 54 ›› Issue (6): 1198-1212.doi: 10.7544/issn1000-1239.2017.20160806

Special Issue: 2017优青专题

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Survey of Database Usability for Query Results

Liu Qing1, Gao Yunjun1,2   

  1. 1(College of Computer Science and Technology, Zhejiang University, Hangzhou 310027); 2(Key Laboratory of Big Data Intelligent Computing of Zhejiang Province (Zhejiang University), Hangzhou 310027)
  • Online:2017-06-01

Abstract: Database usability has received much attention in the database community because of its importance. The goal of database usability is to help users utilize database more efficiently and conveniently, and thus improving the user’s satisfaction for the database. In this survey, we focus on the database usability for query results. Currently, the queries only return the query results to users. If the query result is unexpected for the users, it will frustrate users. However, the database system neither gives explanations for the unexpected query results, nor offers any suggestion on how to get the expected results for users. The users only can debug the queries by themselves, which is cumbersome and time-consuming. If the database system can offer such explanations and suggestions, it helps the users understand initial query better, and know how to change the query until the satisfactory results are found, hence improving the usability of the database. Towards this, the studies on unexpected query results have been explored. In this paper, we provide a comprehensive survey of the most recent research on database usability for query results. The paper first analyses the unexpected query results, and introduces the corresponding three problems, i.e., causality & responsibility, why-not & why questions, and why-few & why-many questions, and highlights the importance of these three problems. Then, the state of the art progresses of the unexpected query result research have been surveyed and summarized. Finally, the paper raises some directions for the future work.

Key words: database usability, why-not questions, why questions, causality &, responsibility, why-few questions, why-many questions

CLC Number: