The anonymisation decision-making framework M Elliot, E Mackey, K O'Hara, C Tudor UKAN, 2016 | 161 | 2016 |
Are ‘pseudonymised’data always personal data? Implications of the GDPR for administrative data research in the UK M Mourby, E Mackey, M Elliot, H Gowans, SE Wallace, J Bell, H Smith, ... Computer Law & Security Review 34 (2), 222-233, 2018 | 150 | 2018 |
Functional anonymisation: Personal data and the data environment M Elliot, K O'hara, C Raab, CM O'Keefe, E Mackey, C Dibben, H Gowans, ... Computer Law & Security Review 34 (2), 204-221, 2018 | 59 | 2018 |
An introduction to data linkage K Harron, E Mackay, M Elliot ADRN, 2016 | 27 | 2016 |
Understanding the data environment E Mackey, M Elliot XRDS: Crossroads, The ACM Magazine for Students 20 (1), 36-39, 2013 | 27 | 2013 |
Data environment analysis and the key variable mapping system M Elliot, S Lomax, E Mackey, K Purdam Privacy in Statistical Databases: UNESCO Chair in Data Privacy …, 2010 | 25 | 2010 |
The anonymisation decision-making framework 2nd Edition: European practitioners' guide M Elliot, E Mackey, K O'Hara UKAN, 2020 | 23 | 2020 |
The de-identification decision-making framework CM O’Keefe, S Otorepec, M Elliot, E Mackey, K O’Hara CSIRO Reports EP173122 and EP175702 Canberra: Australian Government Office …, 2017 | 18 | 2017 |
An application of game theory to understanding statistical disclosure events EC Mackey, MJ Elliot UNECE http://www. unece. org/stats/documents/ece/ces/ge 46, 2009, 2009 | 16* | 2009 |
The social data environment M Elliot, E Mackey Digital Enlightenment Yearbook 2014, 253-263, 2014 | 12* | 2014 |
The regulation of the personal DK Purdam, ME Mackey, DM Elliot Policy Studies 25 (4), 267-281, 2004 | 12 | 2004 |
End user licence to open government data? A simulated penetration attack on two social survey datasets M Elliot, E Mackey, S O’Shea, C Tudor, K Spicer Journal of official statistics 32 (2), 329-348, 2016 | 11* | 2016 |
Formalizing the selection of key variables in disclosure risk M Elliot, E Mackey, K Purdam Proceedings of the 58th Congress of the International Statistical Institute, ISI, 2011 | 11* | 2011 |
Are ‘pseudonymised’data always personal data? Implications of the GDPR for administrative data research in the UK. Computer Law & Security Review, 34 (2), 222–233 M Mourby, E Mackey, M Elliot, H Gowans, SE Wallace, J Bell, H Smith, ... | 9 | 2018 |
Ensuring the confidentiality of statistical outputs from the ADRN P Lowthian, F Ritchie, E Mackay, M Elliot ADRN, 2017 | 8 | 2017 |
Functional Anonymisation: The crucial role of the data environment in determining the classification of data as (non-) personal MJ Elliot, C Dibben, H Gowans, E Mackey, D Lightfoot, K O’Hara, ... CMIST work paper 2, 2015 | 8 | 2015 |
Data Horizons M Elliot, K Purdam, E Mackey London: ESRC, 2013 | 6 | 2013 |
Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity): A longitudinal observational study SM Ali, DA Selby, K Khalid, K Dempsey, E Mackey, N Small, ... Journal of Multimorbidity and Comorbidity 11, 26335565211062791, 2021 | 5 | 2021 |
A best practice approach to anonymization E Mackey Handbook of Research Ethics and Scientific Integrity, 323-343, 2020 | 5 | 2020 |
’A Framework for Understanding Statistical Disclosure Control Processes’ E Mackey PhD Thesis, University of Manchester, 2009 | 5 | 2009 |