Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data
The Intermediate Data Structure (IDS) is a standardised database structure for longitudinal historical databases. Such a common structure facilitates data sharing and comparative research. In this study, we propose an extended version of IDS, named IDS-Geo, that also includes geographic data. The ge...
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| Language: | English |
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International Institute of Social History
2014-09-01
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| Series: | Historical Life Course Studies |
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| Online Access: | https://test.openjournals.nl/hlcs/article/view/9289 |
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| author | Finn Hedefalk Lars Harrie Patrick Svensson |
| author_facet | Finn Hedefalk Lars Harrie Patrick Svensson |
| author_sort | Finn Hedefalk |
| collection | DOAJ |
| description | The Intermediate Data Structure (IDS) is a standardised database structure for longitudinal historical databases. Such a common structure facilitates data sharing and comparative research. In this study, we propose an extended version of IDS, named IDS-Geo, that also includes geographic data. The geographic data that will be stored in IDS-Geo are primarily buildings and/or property units, and the purpose of these geographic data is mainly to link individuals to places in space. When we want to assign such detailed spatial locations to individuals (in times before there were any detailed house addresses available), we often have to create tailored geographic datasets. In those cases, there are benefits of storing geographic data in the same structure as the demographic data. Moreover, we propose the export of data from IDS-Geo using an eXtensible Markup Language (XML) Schema. IDS-Geo is implemented in a case study using historical property units, for the period 1804 to 1913, stored in a geographically extended version of the Scanian Economic Demographic Database (SEDD). To fit into the IDS-Geo data structure, we included an object lifeline representation of all of the property units (based on the snapshot time representation of single historical maps and poll-tax registers). The case study verifies that the IDS-Geo model is capable of handling geographic data that can be linked to demographic data. |
| format | Article |
| id | doaj-art-06cea2d318854800aaa0c91f7b78d671 |
| institution | Kabale University |
| issn | 2352-6343 |
| language | English |
| publishDate | 2014-09-01 |
| publisher | International Institute of Social History |
| record_format | Article |
| series | Historical Life Course Studies |
| spelling | doaj-art-06cea2d318854800aaa0c91f7b78d6712025-02-02T12:39:41ZengInternational Institute of Social HistoryHistorical Life Course Studies2352-63432014-09-011Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic dataFinn HedefalkLars HarriePatrick SvenssonThe Intermediate Data Structure (IDS) is a standardised database structure for longitudinal historical databases. Such a common structure facilitates data sharing and comparative research. In this study, we propose an extended version of IDS, named IDS-Geo, that also includes geographic data. The geographic data that will be stored in IDS-Geo are primarily buildings and/or property units, and the purpose of these geographic data is mainly to link individuals to places in space. When we want to assign such detailed spatial locations to individuals (in times before there were any detailed house addresses available), we often have to create tailored geographic datasets. In those cases, there are benefits of storing geographic data in the same structure as the demographic data. Moreover, we propose the export of data from IDS-Geo using an eXtensible Markup Language (XML) Schema. IDS-Geo is implemented in a case study using historical property units, for the period 1804 to 1913, stored in a geographically extended version of the Scanian Economic Demographic Database (SEDD). To fit into the IDS-Geo data structure, we included an object lifeline representation of all of the property units (based on the snapshot time representation of single historical maps and poll-tax registers). The case study verifies that the IDS-Geo model is capable of handling geographic data that can be linked to demographic data.https://test.openjournals.nl/hlcs/article/view/9289XMLData modelStandardisationLongitudinal historical dataGeographic dataIDS-Geo |
| spellingShingle | Finn Hedefalk Lars Harrie Patrick Svensson Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data Historical Life Course Studies XML Data model Standardisation Longitudinal historical data Geographic data IDS-Geo |
| title | Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data |
| title_full | Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data |
| title_fullStr | Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data |
| title_full_unstemmed | Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data |
| title_short | Extending the Intermediate Data Structure (IDS) for longitudinal historical databases to include geographic data |
| title_sort | extending the intermediate data structure ids for longitudinal historical databases to include geographic data |
| topic | XML Data model Standardisation Longitudinal historical data Geographic data IDS-Geo |
| url | https://test.openjournals.nl/hlcs/article/view/9289 |
| work_keys_str_mv | AT finnhedefalk extendingtheintermediatedatastructureidsforlongitudinalhistoricaldatabasestoincludegeographicdata AT larsharrie extendingtheintermediatedatastructureidsforlongitudinalhistoricaldatabasestoincludegeographicdata AT patricksvensson extendingtheintermediatedatastructureidsforlongitudinalhistoricaldatabasestoincludegeographicdata |