Selectivity Of Big Data：大数据的选择性精品.pdfVIP

Discussion Paper Selectivity of Big data The views expressed in this paper are those of the author(s) and do not necessarily reflect the policies of Statistics Netherlands 2014 | 11 Bart Buelens Piet Daas Joep Burger Marco Puts Jan van den Brakel 28 March 2014 Selectivity of Big data Bart Buelens, Piet Daas, Joep Burger, Marco Puts, Jan van den Brakel Data sources referred to as Big data become available for use by NSIs. A major concern when considering if and how these data can be of value, is their potential selectivity. The data generating mechanisms underlying Big data vary widely, but have in common that they are very different from probability sampling, the data collection strategy ordinarily used at NSIs. Assessment of selectivity of Big data sets is generally not straightforward, if at all possible. Some approaches are proposed in this paper. It is argued that the degree to which selectivity – or its assessment – is an issue, depends on the way the data are used for production of statistics. The role Big data can play in that process ranges from minor over supplementary to vital. Methods for inference that are in part or wholly based on Big data need to be developed, with particular attention to their capabilities of dealing with or correcting for selectivity of Big data. This paper elaborates on the current view on these matters at Statistics Netherlands, and concludes with some discussion points for further consideration or research. This paper has been presented at the Statistics Netherlands Advisory Council meeting on 11 Feb. 2014. Keywords: representativeness, selection bias, model-based estimation, algorithmic inference, data science Selectivity of Big data 2 1. Introduction When Big data are discussed in relation