Even now, users with disabilities encounter serious barriers when accessing the Web. In particular, blind and visually impaired users encounter difficulties browsing and reading the contents of a website. Screen readers provide some assistance, yet, as they are unable to interpret the Web structure, they summarise information and read specific labelled fragments. Therefore, the overall comprehension of the text remains challenging. In this sense, in order to improve the accessibility of websites on the fly, we propose a Web augmentation framework for accessibility (WAFRA). Our framework uses Web augmentation techniques that extend the website with voice interaction and new actions: label text fragments, read aloud these fragments, facilitate navigation, increase font size and show videos. In order to perform this accessibility improvement, we automatically provide annotations from DBPedia regarding important information for end users. Moreover, we also provide the option that intermediary users add new annotations for labelling or including more specific information, which can be shared with other users by crowdsourcing. The evaluation of the framework shows its usefulness to ease website access for users with visual disabilities compared to using screen readers.

Virtual assistants allow users to interact with apps using a conversational mode. A particular kind of device supporting virtual assistants is the smart speaker, which allows end users to access contents and services, perform searches and command smart environments via voice interaction. These devices are gaining relevance among users, and the number of apps available for giving them more conversational capabilities grows constantly. However, there is a gap between what can be achieved using these devices and the information available on the web, i.e. most web apps don't have one smart speaker app counterpart. In this work, we present a two-step approach to defining conversational interfaces for virtual assistants based on existing web sites. During the first step, the user creates web content blocks, which describe target contents and the strategy for retrieving them. In the second step, the user uses web content blocks to specify the conversational interface. Although the approach could be considered generic enough for any kind of conversational interface, we focus our research on voice user interfaces, considering smart speaker apps as a major target. With our approach, apps based on voice user interfaces for smart speakers may be developed in a no-code manner. We describe and illustrate the approach by presenting usage examples and an evaluation using the Alexa service and an Amazon Echo device. The evaluation shows promising results for two case studies where there is no significant difference between the user experience when comparing solutions developed using the Alexa SDK versus apps using our approach.

Nowadays, Web browser extensions are the more convenient way to modify existing Web applications and the browser itself to satisfy non-contemplated requirements. Extensions play an important role because of the relevance that the Web and the Web browser have in our daily life. The functionality offered by Web extensions varies. Many Web extensions are tools that improve the interaction with existing Web sites based on techniques such as mashups and Web augmentation. Accessing and manipulating Web sites’ content is a challenge for the development and maintenance of extensions. In this paper, we present a data service layer that allows extension developers to create APIs based on Web annotations to access existing Web content. The data service layer simplifies the retrieval of structured information from Web pages, without the need of DOM manipulation in the extension code. We provide visual programming tools to create these APIs so there is no need for advanced programming skills, making extension development and maintenance easier.

Abstract In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations of items into arbitrary websites on client-side. For this we have developed a generic meta-model to capture recommender system configuration parameters in general as well as in a web augmentation context. Thereupon, we have implemented a wizard in the form of an easy-to-use browser plug-in, allowing the generation of so-called user scripts, which are executed in the browser to engage collaborative filtering functionality from a provided external rest service. We discuss functionality and limitations of the approach, and in a study with end-users we assess the usability and show its suitability for combining recommender systems with web augmentation techniques, aiming to empower end-users to implement controllable recommender applications for a more personalized browsing experience.

Usability and user interaction improvement is a central task in web development to guarantee the success of a web application. However, designers are barely able to keep up with the current development cycle because their practices are too costly, while interaction issues accumulate in applications that end-users keep suffering. In this work, we propose a method for designers to rapidly explore solutions through visual programming to the interaction problems of an application under development, even when it has been already deployed. The method is realized by a tool called UX-Painter, an exploratory tool for designers to apply quick fixes to interaction issues at the client-side of a web application without the need of any script programming knowledge. The palette of available fixes in UX-Painter are client-side web refactorings, i.e., changes to web page elements that solve specific user interaction problems without changing the underlying functionality. UX-Painter allows designers to quickly set up new versions of a web application by combining refactorings to create alternative designs for user testing or an inspection review. UX-Painter also provides the means to communicate design improvements, as a sequence of refactorings with clear semantics. We show the feedback provided by interviews with designers about UX-Painter's functionality and the results of a user test about its usability.

Websites augmentations have been adopted as a mean for improving the User Experience of applications \nthat often are not owned by the user. The augmentations alter the page in order to add, modify and even \nremove its content pursuing the satisfaction of a user’s need. However, these augmentations are limited to \npage modification or transcluding content from another site on Internet. Moreover, advance server-side based \naugmentations have been released only by developers because of the required technical skill for the task. In \nthis work, we have presented a novel approach for designing Web Augmentation coping client-side and server side using a Model-Driven Web Engineering approach. The approach rises the abstraction level for server side developments allowing end-users to design, and even implement the new functionalities. Additionally, \nthe approach uses advance separation of concern principles thus we provide a set of tools for designing the \ncomposition of the core application and the augmentation. We show as running example an augmentation that \nintroduces a site community’s review support upon an agriculture e-commerce site.