Understanding movement data quality
Andrienko, G., Andrienko, N. & Fuchs, G. (2016). Understanding movement data quality. Journal of Location Based Services, 10(1), pp. 31-46. doi: 10.1080/17489725.2016.1169322
Abstract
© 2016 Informa UK Limited, trading as Taylor & Francis Group. 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.
Publication Type: | Article |
---|---|
Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis in 'Journal of Location Based Services' on 22 April 2016, available online: http://www.tandfonline.com/10.1080/17489725.2016.1169322. |
Publisher Keywords: | Movement data; data quality; visual analytics. |
Subjects: | Q Science > QA Mathematics |
Departments: | School of Science & Technology > Computer Science School of Science & Technology > Computer Science > giCentre |
SWORD Depositor: |
Download (1MB) | Preview
Export
Downloads
Downloads per month over past year