Understanding movement data quality. (2nd January 2016) - Andrienko, Gennady; Andrienko, Natalia; Fuchs, Georg
Abstract: Understanding of data quality is essential for choosing suitable analysis methods and interpreting their results. Investigation of quality of movement data, due to their spatio-temporal nature, requires consideration from multiple perspectives at different scales. We review the key properties of movement data and, on their basis, create a typology of possible data quality problems and suggest approaches to identify these types of problems.