2015/02/27 by Jácome Cunha, Cunha, Jácome, João Paulo Fernandes +5 · 1 citation
Computer Science · Psychology · #Advanced Database Systems and Queries #Educational Games and Gamification #FOS: Computer and information sciences #Software Engineering (cs.SE) #Spreadsheets and End-User Computing #cs.SE
paper · pdf · doi:10.48550/arxiv.1502.07948
arxiv created 2015/02/27 · openalex publication_date 2015/02/27 · arxiv updated 2015/03/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
One of the most important assets of any company is being able to easily access information on itself and on its business. In this line, it has been observed that this important information is often stored in one of the millions of spreadsheets created every year, due to simplicity in using and manipulating such an artifact. Unfortunately, in many cases it is quite difficult to retrieve the intended information from a spreadsheet: information is often stored in a huge unstructured matrix, with no care for readability or comprehensiveness. In an attempt to aid users in the task of extracting information from a spreadsheet, researchers have been working on models, languages and tools to query. In this paper we present an empirical study evaluating such proposals assessing their usage to query spreadsheets. We investigate the use of the Google Query Function, textual model-driven querying, and visual model-driven querying. To compare these different querying approaches we present an empirical study whose results show that the end-users' productivity increases when using model-driven queries, specially using its visual representation.