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Spatiotemporal historical datasets at micro-level for geocoded individuals in five Swedish parishes, 1813–1914

Hedefalk, Finn LU ; Svensson, Patrick LU and Harrie, Lars LU (2017) In Scientific data 4.
Abstract
This paper presents datasets that enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes, and by linking them to a longitudinal demographic database, we obtain a geocoded population (at the property unit level) for this area for the period 1813–1914. The population is a subset of the Scanian Economic Demographic Database (SEDD). The geographic information includes the following feature types: property units, wetlands, buildings, roads and railroads. The property units and wetlands are stored... (More)
This paper presents datasets that enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes, and by linking them to a longitudinal demographic database, we obtain a geocoded population (at the property unit level) for this area for the period 1813–1914. The population is a subset of the Scanian Economic Demographic Database (SEDD). The geographic information includes the following feature types: property units, wetlands, buildings, roads and railroads. The property units and wetlands are stored in object-lifeline time representations (information about creation, changes and ends of objects are recorded in time), whereas the other feature types are stored as snapshots in time. Thus, the datasets present one of the first opportunities to study historical spatio-temporal patterns at the micro-level. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
geography, history, interdisciplinary studies
in
Scientific data
volume
4
publisher
Nature Publishing Group
external identifiers
  • scopus:85017347649
  • wos:000400151400002
ISSN
2052-4463
DOI
10.1038/sdata.2017.46
language
English
LU publication?
yes
id
0dcbd5a3-c0be-4fc8-99f1-ed9400fd32af
date added to LUP
2017-04-11 15:44:28
date last changed
2018-01-07 11:59:05
@article{0dcbd5a3-c0be-4fc8-99f1-ed9400fd32af,
  abstract     = {This paper presents datasets that enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes, and by linking them to a longitudinal demographic database, we obtain a geocoded population (at the property unit level) for this area for the period 1813–1914. The population is a subset of the Scanian Economic Demographic Database (SEDD). The geographic information includes the following feature types: property units, wetlands, buildings, roads and railroads. The property units and wetlands are stored in object-lifeline time representations (information about creation, changes and ends of objects are recorded in time), whereas the other feature types are stored as snapshots in time. Thus, the datasets present one of the first opportunities to study historical spatio-temporal patterns at the micro-level.},
  articleno    = {170046},
  author       = {Hedefalk, Finn and Svensson, Patrick and Harrie, Lars},
  issn         = {2052-4463},
  keyword      = {geography,history,interdisciplinary studies},
  language     = {eng},
  month        = {04},
  publisher    = {Nature Publishing Group},
  series       = {Scientific data},
  title        = {Spatiotemporal historical datasets at micro-level for geocoded individuals in five Swedish parishes, 1813–1914},
  url          = {http://dx.doi.org/10.1038/sdata.2017.46},
  volume       = {4},
  year         = {2017},
}