Abstract
Information access to bibliographic metadata needs to be uncomplicated, as users may not benefit from complex and potentially richer data that may be difficult to obtain. Sophisticated research questions including complex aggregations could be answered with complex SQL queries. However, this comes with the cost of high complexity, which requires for a high level of expertise even for trained programmers. A domain-specific query language could provide a straightforward solution to this problem. Although less generic, it can support users not familiar with query construction in the formulation of complex information needs. In this paper, we present and evaluate SchenQL, a simple and applicable query language that is accompanied by a prototypical GUI. SchenQL focuses on querying bibliographic metadata using the vocabulary of domain experts. The easy-to-learn domain-specific query language is suitable for domain experts as well as casual users while still providing the possibility to answer complex information demands. Query construction and information exploration are supported by a prototypical GUI. We present an evaluation of the complete system: different variants for executing SchenQL queries are benchmarked; interviews with domain-experts and a bipartite quantitative user study demonstrate SchenQL’s suitability and high level of users’ acceptance.
Highlights
Scientific writing almost always starts with a thorough bibliographic research on relevant papers, authors, conferences, journals and institutions
Before the actual evaluation of the SchenQL system, we conduct benchmarks for two possible database engine and target languages for the compilation of SchenQL queries: SQL and Cypher
Afterwards, we evaluate the performance of the current implementation of the compiler that translates SchenQL into the target query language
Summary
Scientific writing almost always starts with a thorough bibliographic research on relevant papers, authors, conferences, journals and institutions. E.g. GrapAL3 [7], are capable of answering said complex queries, but come with complex and often not very intuitive query languages Another option would be to use structured query languages such as SQL, a widespread language for querying databases, which tends to be difficult to master [37]. This is critical as in most cases domain-experts are familiar with the schema of the data but are not experienced in using all-purpose query languages such as SQL [1,26]. This is even worse for casual users of digital libraries who
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
