IEEE Transactions on Knowledge and Data Engineering (TKDE) is an archival journal published monthly. The information published in this journal is designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area. We are interested in well-defined theoretical results and empirical studies that have potential impact on the acquisition, management, storage, and graceful degeneration of knowledge and data, as well as in provision of knowledge and data services. We welcome treatments of the role of knowledge and data in the development and use of information systems and in the simplification of software and hardware development and maintenance. Since the journal is archival, it is assumed that the ideas presented are important, have been well analyzed or empirically validated, and are of value to the knowledge and data engineering research community. Specific topics include, but are not limited to: (a) knowledge discovery and data mining, (b) data modeling and management, (c) underlying computational platforms for knowledge and data engineering tools, techniques and systems, and (d) emerging knowledge and data engineering applications.