Accessibility and smart data: the case study of mPASS

The growing availability of data gathered by people via personal sensing and crowdsourcing is changing the way data are collected, provided and perceived. Information is becoming too much to actually make sense and this leads to an increasing demand of Smart Data. We can intend Smart Data as information obtained by large data and extracted by intelligent algorithms to meet people needs. This concept easily matches with well-known accessibility issues, solutions and techniques. Moreover, Smart Data is an emerging solution to prevent the large amount of data from becoming a new challenge in the e-accessibility field. In this context, my research is devoted to apply Smart Data to improve e-accessibility in a mobile crowdsourcing and sensing application designed to support users with disabilities in avoiding urban accessibility barriers.