The Intermediate Data Structure (IDS) provides a common structure for storing and sharing historical demographic data. The structure also facilitates the construction of different open-access software to extract information from these tables and construct new variables. The article Using the Intermediate Data Structure (IDS) to Construct Files for Analysis (Quaranta 2015) presented a series of concepts and programs that allow the user to construct a rectangular episodes file for longitudinal statistical analysis using data stored in the IDS.
The use of longitudinal historical micro-level demographic data for research presents many challenges. The Intermediate Data Structure (IDS) was developed to try to solve some of these challenges by facilitating the storing and sharing of such data. This article proposes an extension to the IDS, which allows the standardization and storage of constructed variables. It also describes how to produce a rectangular episodes file for statistical analysis from data stored in the IDS and presents programs developed for such purpose.
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.
The Intermediate Data Structure (IDS) is a standard data format that has been adopted by several large longitudinal databases on historical populations. Since the publication of the first version in Historical Social Research in 2009, two improved and extended versions have been published in the Collaboratory Historical Life Courses. In this publication we present version 4 which is the latest ‘official’ standard of the IDS.