Automatically recognising widgets on Web pages
Using a Web page is simpler and easier if you know what to expect, and this is even more important for older people, or for users of assistive technologies. WIMWAT explores the possibilites for analysing the code of a Web page, so that the types of widget - features such as slideshows, data-pickers and tickers – on the page could be identified. Doing this identification in the browser, on the fly, this could improve the way many people are able to use the Web.
Full scientific details: http://www.cs.manchester.ac.uk/our-research/groups/interaction-analysis-and-modelling/areas-and-projects/wimwat
Code repository: https://bitbucket.org/IAMLab/
Data repository: http://iam-data.cs.manchester.ac.uk/investigations
Technical reports: http://iam-data.cs.manchester.ac.uk/investigations
Funded by: Funder
This project is complete
The evolution of the World Wide Web (Web) affects the way people develop Web pages and interact with it. Not too long ago, navigating the Web was simply a matter of clicking links, moving from one static page to another, and Web forms require the page to be reloaded every time communication is required between the client and the server. Now it’s possible to spend a considerable amount of time interacting with a single page through its “dynamic micro-content” – items such as Tickers, Slideshows and search facilities – that update independently, without requiring the page to be reloaded. These concepts are popular among users and they can be found throughout the Web; just take a look at Yahoo! or AOL.
Web pages with the latter capabilities provide an exciting, interactive experience for sighted users. For visually disabled users, however, they simply result in further barriers when accessing these pages. Assistive technologies, such as screen readers, are currently unable to effectively deal with dynamic updates. This is because content has to be presented to the user before Assistive technologies can interpret them, but dynamic micro-content actively changes the presented content accordingly to how the developers designed them. Often these changes go unnoticed as Assistive technologies are not able to adapt to these advancement.
The WIMWAT project aims to address this with a preemptive approach, by identifying the type of dynamic micro-applications (widgets) on the page and where they are located, so that Assistive technologies can warn their users or pay more focus on these areas. Other alternative usage could see WIMWAT applied to assist injection of WAI-ARIA and AxsJAX syntax in the Web page. A framework (WPF) was developed to provide guidance to identify widgets from the Web page. For some ideas of using WPF, please visit Possibilities of WPF page.
Determine a formal method to model different types of popular widgets. Such that users and developers concepts of a widget can converge.
Feasibility of comprehending the full Web page source code to identify clues of a widget (tell-signs) in the page automatically.
Develop a framework for reconstructing and classifying widgets from the tell-signs detected in the Web page’s source code.
Doctoral Consortium Paper Accepted at ASSETS’09 (8/26/2009)
Web Widgets Can Be Identified From Web Page’s Source Code #a11y #accessibility(11/2/2011)
WWW Journal Publication for WIMWAT Project #web #a11y #accessibility #widgets (2/8/2012)
Final Report Summary:
Final Report: Pending