* Semantic caching * Data warehousing and semantic data mining * Spatial, temporal, multimedia and multimodal semantics * Semantics in data visualization * Semantic services for mobile users * Supporting tools * Applications of semantic-driven approaches These topics are to be understood as specifically related to semantic issues.
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. This volume constitutes a special issue on semantic data warehouses.
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
The increasing application of data enriched with spatio-temporal features spans various domains, including environmental management and geo-marketing. However, the development of new spatio-temporal applications faces challenges due to a lack of conceptual design methods that can handle the complexity of spatio-temporal data. This complexity arises from the unique semantics of space and time and the necessity for multiple representations to meet the diverse needs of heterogeneous user communities. Effective conceptual design methods are crucial for facilitating data exchange and reuse, especially in geographical data management where collection costs are high. Unfortunately, current practices in geographical information systems and moving objects databases often overlook these methods. This book demonstrates that a conceptual design approach for spatio-temporal databases is both feasible and accessible. It provides a solid foundation through an extensive discussion of traditional data modeling concepts while focusing on modeling spatial and temporal information. The authors present a comprehensive description of their approach, MADS (Modeling of Application Data with Spatio-temporal features), and survey alternative models from both industry and academia. The text is rich with visual notations and examples, making it invaluable for advanced professionals, researchers, and students in spatio-temporal databases and geographical
For over 20 years, the Conceptual Modeling – ER conferences have served as a platform for researchers and practitioners to share and discuss findings in database design and conceptual modeling. Initially focused on database design, the conferences have broadened their scope to encompass more universal aspects of conceptual modeling, emphasizing the organization of poorly structured information through various principles, models, and theories for diverse applications. Concurrently, numerous technical approaches have emerged to aid in implementing advanced conceptual models. Central to this field is the process of conceptualization, which is vital for system structuring and justifying information systems development. This process enhances understanding, explanation, prediction, and reasoning regarding information and knowledge, as well as their manipulation within systems. It also aids in designing system functions. The goal of conceptualization is to develop relevant concepts for the specific knowledge and information system. However, there is often a disconnect between the concepts held in human cognition and their representations in computerized systems, with the former frequently overlooked. Both aspects must be considered in effective conceptual modeling.