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Local population studies in the era of 'big data'

Local population studies in the era of 'big data'
Local population studies in the era of 'big data'
Recent years have seen a proliferation of very large data sets in historical demography, many of which have assembled individual-level data for entire populations. It might be thought that these data sets pose a challenge to local population studies, as they remove one of the rationales for work at the local level: that research using individual-level data was only logistically possible for small populations. This paper argues that, to the contrary, the advent of ‘big data’ sets provides new opportunities for work on local populations. Many of the old arguments in favour of local history still hold, but ‘big data’ can direct researchers to those places where local studies can potentially make the biggest contribution, and thus give local population studies a new lease of life.
local history, big data, population studies
0143-2974
69-81
Hinde, Andrew
0691a8ab-dcdb-4694-93b4-40d5e71f672d
Hinde, Andrew
0691a8ab-dcdb-4694-93b4-40d5e71f672d

Hinde, Andrew (2019) Local population studies in the era of 'big data'. Local Population Studies, 102 (1), 69-81.

Record type: Article

Abstract

Recent years have seen a proliferation of very large data sets in historical demography, many of which have assembled individual-level data for entire populations. It might be thought that these data sets pose a challenge to local population studies, as they remove one of the rationales for work at the local level: that research using individual-level data was only logistically possible for small populations. This paper argues that, to the contrary, the advent of ‘big data’ sets provides new opportunities for work on local populations. Many of the old arguments in favour of local history still hold, but ‘big data’ can direct researchers to those places where local studies can potentially make the biggest contribution, and thus give local population studies a new lease of life.

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LPS 102 Hinde - Accepted Manuscript
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More information

Accepted/In Press date: 3 June 2019
Published date: 1 July 2019
Keywords: local history, big data, population studies

Identifiers

Local EPrints ID: 433461
URI: http://eprints.soton.ac.uk/id/eprint/433461
ISSN: 0143-2974
PURE UUID: 3c09f967-3f26-499a-88d2-6c353dd38cae
ORCID for Andrew Hinde: ORCID iD orcid.org/0000-0002-8909-9152

Catalogue record

Date deposited: 22 Aug 2019 16:30
Last modified: 17 Mar 2024 02:39

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