Improving interoperability after IDS

Activity: Talk or presentationAcademic

Description

Over the past decades, a wide range of historical demographic datasets have become available. Scholars from Asia, Canada, Europe, South Africa, and the US are well aware of each other’s efforts, as the SSHA and other conferences have been excellent platforms to share good practices and build towards better datasets. As a result, researchers from a wide array of countries now have access to high-quality datasets on individual life courses and family connections.
The wider availability of international databases has been a huge gain and allows for exciting comparisons between contexts. Yet, comparative research has been limited by the fractured nature in which the datasets have been built. Datasets were built at different times, on different sources, by different people who spoke a variety of languages, stored at different locations, and are offered via different methods of retrieval. Thus, the structure in which data is provided has been very different: file formats differ, variable names are different, and categories are unstructured. As a result, research studies often focus on one particular database, hampering comparative research.
To optimize our infrastructure for comparative research, our databases need to become Interoperable. Therefore, the IDS has been developed, so that information from each different database can be exchanged in a similar data format. This made it possible to compare databases on a larger scale (see e.g. Quaranta & Sommerseth, 2018). However, to fully solve issues with Interoperability and Reusability, information from the variables themselves needs to be standardized and made available in an environment that is as FAIR as possible.
Period12 Nov 2021
Degree of RecognitionInternational