Effective and efficient data management is vital to today's applications. Traditional data management mainly focuses on information procession involving data within a single organization. Data are unified according to the same schema and there exists an agreement between the interacting units as to the correct mapping between these concepts. Nowadays, data management systems have to handle a variety of data sources, from proprietary ones to data publicly available. Investigating the relevance between data for information sharing has become an essential challenge for data management. This book explores the technology and application of semantic data management by bringing together various research studies in different subfields.