1 Problem addressed Evaluating and collect accessibility status of large sets of Web sites: according to different guidelines (e.g. WCAG 2.0) periodically.

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Presentation transcript:

1 Problem addressed Evaluating and collect accessibility status of large sets of Web sites: according to different guidelines (e.g. WCAG 2.0) periodically and automatically summarizing results, thereby offering an effective and feasible view of the impact of accessibility barriers measured on a large scale sample of Web sites

2 Strategy We designed and implemented AMA, (Accessibility Monitoring Application) to evaluate and collect accessibility status of large sets of Web sites We defined the BIF (Barriers Impact Factor) metrics, to summarize results collected by AMA,so as to quantify: –each accessibility error in terms of how it affects user's browsing by means of assistive technologies

The BIF metrics is computed as follows: BIF(i) = Σerror #error(i) x weight(i) –The lowest value of BIF could be 0 (absence of barriers). –The higher is the BIF value and the higher is the impact of a certain barrier on a specific type of assistive technology/disability. –Barriers have been grouped into 7 sets, per assistive technologies and per disabilities: screen reader/blindness, screen magnifier/low vision, color blindness, input device independence/movement impairments, deafness, cognitive disabilities, photosensitive epilepsy. 3 Strategy (2)

4 BIF on AMA AMA shows also evaluation results based on aBIF (the average barriers impact factor on the whole set of barriers) Weights are set as: the weight of each error which requires a manual control is 0 the weight of any level AAA error is 1 the weight of any level AA error is 2 the weight of any level A error is 3