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doi: 10.1038/s41597-019-0137-z , 10.5281/zenodo.1402953 , 10.48550/arxiv.1808.09267 , 10.5281/zenodo.2578459 , 10.5281/zenodo.1402952
pmid: 31420560
pmc: PMC6697727
arXiv: 1808.09267
handle: 11343/244761
doi: 10.1038/s41597-019-0137-z , 10.5281/zenodo.1402953 , 10.48550/arxiv.1808.09267 , 10.5281/zenodo.2578459 , 10.5281/zenodo.1402952
pmid: 31420560
pmc: PMC6697727
arXiv: 1808.09267
handle: 11343/244761
AbstractBetween the 2011 and 2016 national censuses, the Australian Bureau of Statistics changed its anonymity policy compliance system for the distribution of census data. The new method has resulted in dramatic inconsistencies when comparing low-resolution data to aggregated high-resolution data. Hence, aggregated totals do not match true totals, and the mismatch gets worse as the data resolution gets finer. Here, we address several aspects of this inconsistency with respect to the 2016 usual-residence to place-of-work travel data. We introduce a re-sampling system that rectifies many of the artifacts introduced by the new ABS protocol, ensuring a higher level of consistency across partition sizes. We offer a surrogate high-resolution 2016 commuter dataset that reduces the difference between the aggregated and true commuter totals from ~34% to only ~7%, which is on the order of the discrepancy across partition resolutions in data from earlier years.
Statistics and Probability, FOS: Computer and information sciences, Data Descriptor, 330, Databases (cs.DB), Library and Information Sciences, Computer Science Applications, Education, Computer Science - Databases, Statistics, Probability and Uncertainty, Information Systems
Statistics and Probability, FOS: Computer and information sciences, Data Descriptor, 330, Databases (cs.DB), Library and Information Sciences, Computer Science Applications, Education, Computer Science - Databases, Statistics, Probability and Uncertainty, Information Systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 23 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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