Metadata plays an important role in web-based environmental information systems (EIS). It structures existing information and provides background information about technical issues as well as the context in which information has been generated or should be interpreted. Further, many systems such as the BUISY (Bremer Umweltinformationssystem) use metadata in order to provide content-based search facilities. Such methods, however, depend on the correctness and completeness of the metadata. In this paper, we discuss an approach for automatically analyzing the metadata of web-based information systems that is based on machine learning techniques and its application to different environmental systems. We analyze three web-based EIS and discuss our results.
展开▼
