Introduction Interoperability of collected dataset has been distress for researchers. Introduction of database management software made some improvements, however, still we need many of craftworks to convert and clean up original dataset before the beginning of statistical analysis. To improve procedure of data management by raising interoperability of dataset, we technically examined a standard-based object-oriented data model for a common database between data entry system and statistical analysing system, and estimated how the process of data management was changed with the new data model.
Methods We adopted the Archetypes data model, which is a standard of ISO 13606, as the storage for collected dataset and the R language and environment for statistical computing as the statistical software. An example dataset was sampled from a cohort study. We simulated to develop an exclusive data entry sheet for the study. To estimate effect of introducing Archetypes database, we enumerated operations which will be required to build the system, input, review, clean, transfer, and analysis the example dataset. The complexity of each operation was estimated. For control, same estimation was performed on a system with traditional database.
Results Archetypes approach was expected to require more complicated procedures to build the data entry system than traditional approach, however, more software components was expected to reusable between other datasets. Both approaches were expected to require similar number of operations to manage datasets.
Conclusion For electrical data collection of epidemiological study, introduction of standardised data model might lead to efficient development of data entry system.