Processing Metadata for Empirical Data - The Example of the Clearing House for Transport Data & Transport Models

Kurzfassung

In terms of statistical data the importance and usefulness of reliable metadata is undisputed and generally accepted. In any case, a profound, professional analysis of empirical data, in particular secondary analysis, demands extensive documentation about the survey itself and the associated data set. This documentation should include background information, sample design and procedures, the applied data collection methods, coding schemes, technical file formats and so forth. Comprehensive metadata are even more important if a certain database is supposed to be used across various disciplines. For example, transport data are not only relevant for transportation research but also for urban and regional studies. From the user perspective a standardized description format is extremely helpful. It not only supports efficient information retrieval via search engines, but also allows a direct comparison of different data sources. Therefore metadata has to be prepared, presented and disseminated in a more or less formal way. This presentation will focus on the whole process of preparation, presentation and dissemination of metadata within the "Clearing House for Transport Data and Transport Models". The initial preparation of metadata is a complex timeconsuming task. An overall metadata structure has to be defined (for example the DDI metadata standard), already available explanatory material has to be collected, and the relevant information has to be extracted. If necessary, related datasets have to be checked or even recoded. For presentation and dissemination of metadata a web interface was developed. Especially for the presentation of survey data the NESSTAR system is used.