Easing access to relational databases:investigating access to relational databases in the context of both novice and would-be expert users

摘要

Relational databases are commonplace in a wide variety of applications and are used by a broad range of users with varying levels of technical understanding. Extracting information from relational databases can be difficu novice users should be able to do so without any understanding of the database structure or query languages and those who wish to become experts can find it difficult to learn the skills required. Many applications designed for the novice user demand some understanding of the underlying database and/or are limited in their ability to translate keywords to appropriate results. Some educational applications often fail to provide assistance in key areas such as using joins, learning textual SQL and building queries from scratch. This thesis presents two applications: Context Aware Free Text ANalysis (CAFTAN) that aims to provide accurate keyword query interpretations for novices, and SQL in Steps (SiS) designed for students learning SQL. Both CAFTAN and SiS are subject to detailed evaluations; the former is shown to be capable of interpreting keyword queries in a way similar to humans; the latter was integrated into an undergraduate databases course and showed the potential benefits of introducing graphical aids into a student's learning process. The findings presented in this thesis have the potential to improve keyword search over relational databases in both a generic and customised context, as well as easing the process of learning SQL for new experts.