The Intermediate Data Structure (IDS) for Longitudinal Historical Microdata, version 4

Area of Science:

• Historical demography
• Social science data management
• Computational history

Background:

• The Intermediate Data Structure (IDS) is a foundational data format for historical population databases.
• Previous versions were published in 2009 and subsequently updated.
• Ongoing user engagement has driven the evolution of the IDS standard.

Purpose of the Study:

• To present version 4 of the Intermediate Data Structure (IDS), the latest official standard.
• To detail the significant updates and enhancements incorporated into this new version.
• To provide guidance for the effective use of the IDS in historical research.

Main Methods:

• Incorporation of a new table for hierarchical 'context' relationships.
• Development of decision schemes for recording complex relationships.
• Addition of fields to the metadata table for richer data description.
• Establishment of rules for handling stillbirth data.
• Introduction of a reciprocal model for representing relationships.
• Provision of guidance for linking IDS data with geospatial information.
• Development of an extended IDS for computed variables.

Main Results:

• Version 4 of the IDS offers a more robust and flexible framework for historical population data.
• Enhanced relationship modeling and metadata capabilities improve data integration and analysis.
• Specific guidelines address previously complex data types like stillbirths.
• The extended IDS facilitates the inclusion of derived and computed variables.

Conclusions:

• Version 4 represents a significant advancement in the standardization of historical population data.
• The updated IDS supports more sophisticated and comprehensive analyses of longitudinal datasets.
• This standard will benefit researchers working with large-scale historical population data.