Article ID Journal Published Year Pages File Type
4968198 Journal of Visual Languages & Computing 2017 15 Pages PDF
Abstract
Web services offer a more reliable and efficient way to access online data than scraping web pages. However, interacting with web services to retrieve data often requires people to write a lot of code. Moreover, many web services return data in complex hierarchical structures that make it difficult for people to perform any further data manipulation. We developed Gneiss, a tool that extends the familiar spreadsheet metaphor to support using structured web service data. Gneiss lets users retrieve or stream arbitrary JSON data returned from web services to a spreadsheet using interaction techniques without writing any code. It introduces a novel visualization that represents hierarchies in data using nested spreadsheet cells and allows users to easily reshape and regroup the extracted structured data. Data flow is two-way between the spreadsheet and the web services, enabling people to easily make a new web service call and retrieve new data by modifying spreadsheet cells. We report results form a user study that showed that Gneiss helped spreadsheet users use and analyze structured data more efficiently than Excel and even outperform professional programmers writing code. We further use a set of examples to demonstrate our tool's ability to create reusable data extraction and manipulation programs that work with complex web service data.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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