Gneiss: spreadsheet programming using structured web service data

نویسندگان

  • Kerry Shih-Ping Chang
  • Brad A. Myers
چکیده

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. & 2016 Elsevier Ltd. All rights reserved.

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عنوان ژورنال:
  • J. Vis. Lang. Comput.

دوره 39  شماره 

صفحات  -

تاریخ انتشار 2017