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Accessibility and search engine optimization on scalable vector graphics

The purpose of this paper was to carry out a study about techniques for description of images in Scalable Vector Graphics (SVG), and also assess the way in which search engines index this content. The study addressed the importance of the description of images, how this description has an impact on the web accessibility for screen reader users, and the way in which this content is indexed by search engines. The execution of the study involved a process of empirical observation, which represented a typical environment for the publication of a SVG code on a Web page. The base of the experiment was the publication of content within SVG elements, on a HTML5 (HyperText Markup Language version 5) webpage. After indexing by search engines, an investigation was carried out to see which elements were indexed. We observed the behaviour of the elements <title>, <desc>, <text>, and also the aria-label attribute, as well as support by browsers and assistive technology, and its indexing by search engines. The hypothesis behind this work is that some elements and attributes that are important for accessibility of the SVG content are also useful for indexing the content by search engines. The conclusion of this study has shown that elements such as <desc> and <text> are indexed by search engines, and their combination with other elements and attributes may expand the accessibility of the page and also contribute for the indexing by search engines.