Data collection is strongly influenced by national conventions. Their source, the purpose for which they were gathered, the criteria used and the method of collection may vary considerably from one country to another, and the criteria adopted for coding data may change over time. In some areas, national records may be non-existent or may not go back very far. Official statistics may be produced in too highly aggregated a form and may not have been collected systematically over time. In many multinational studies, much time and effort is expended on trying to reduce classifications to a common base.
Agreement is therefore difficult to reach over research parameters and units of comparison.
Even the definition of a country or society can be problematic, since there is no single identifiable, durable and relatively stable sociological unit equivalent to the total geographical territory of a nation. Language can present a major obstacle to effective international collaboration, since it is not simply a medium for conveying concepts, but part of the conceptual system, reflecting institutions, thought processes, values and ideology, and implying that the approach to a topic and interpretations of it will differ according to the language of expression. Although defining a time span may appear to be a simple matter for a longitudinal study, innumerable problems can arise when national datasets are being used. These problems are compounded when comparisons are based on secondary analysis of existing national datasets, since it may not always be possible to apply agreed criteria uniformly. The problems of building and managing a research team can often be resolved only by a process of trial and error, and the quality of the contributions to multinational projects may be very uneven.