Some reasons for documenting research data using the Data Documentation Alliance standard

There is acknowledgement among social and behavioral science researchers that metadata are important for data sharing. Researchers however seem not to see any usefulness or investing resources into adequately documenting the primary data they produce. They may create traditional codebooks to accompany the data but they almost invariably do not provide any structured documentation of their data using an internationally accepted structured data documentation standard designed for social and behavioral science data called DDI. They normally leave most of the work of proper documentation of data to archivists. There are however, clear benefits that could be derived from proper documentation of research data. In this paper, we attempt to provide examples of these benefits. This paper aims to show case an example of the usefulness of investing time into data documentation using an international standard called DDI. This study uses the TAZAMA data as an example, it looks at the process used to extract some data from the TAZAMA source database and transforming them into specified requirements using a framework created by DDI documentation of the data. This example will hopefully provide concrete evidence of the benefits to be derived from structured documentation of research data.