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ScrAPIr: Making Web Data APIs Accessible to End Users
Name
scrapir.pdf
Description
Accepted version
Size
8.36 MB
Format
Adobe PDF
Checksum (MD5)
b1d330ec7f3aae5d565b4422f50be7e0
Author(s)
Alrashed, Tarfah
Almahmoud, Jumana
Zhang, Amy Xian
Karger, David R
Date Issued
April 2020
Journal
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Publisher
Association for Computing Machinery (ACM)
Citation
Alrashed, Tarfah et al. "ScrAPIr: Making Web Data APIs Accessible to End Users." Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, April 2020, Honolulu, Hawaii, Association for Computing Machinery, April 2020. © 2020 The Authors
Version
Author's final manuscript
Abstract
Users have long struggled to extract and repurpose data from websites by laboriously copying or scraping content from web pages. An alternative is to write scripts that pull data through APIs. This provides a cleaner way to access data than scraping; however, APIs are effortful for programmers and nigh-impossible for non-programmers to use. In this work, we empower users to access APIs without programming. We evolve a schema for declaratively specifying how to interact with a data API. We then develop ScrAPIr: a standard query GUI that enables users to fetch data through any API for which a specification exists, and a second GUI that lets users author and share the specification for a given API. From a lab evaluation, we find that even non-programmers can access APIs using ScrAPIr, while programmers can access APIs 3.8 times faster on average using ScrAPIr than using programming.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1145/3313831.3376691
