Warehousing and OLAPing Complex, Spatial and Spatio-Temporal Data

Preface Complex, spatial and spatio-temporal data arise in a plethora of modern database and data mining applications and complex information systems. Complex, spatial and spatio-temporal data require more and more for effective and efficient models, algorithms and techniques for representing, managing, querying , indexing and discovering useful knowledge beyond such kind of data. A successful solution to issues above consists in applying well-consolidated methodologies coming from the Data Warehousing and OLAP research area. This allows us to take advantages from several nice amenities supported by Data Warehousing and OLAP, such as multidimensional and multi-resolution representation and analysis , multidimensional aggregations, hierarchy-based data representation and mining, complex query answering tools, and so forth. Application fields where Data Warehousing and OLAP over complex, spatial and spatio-temporal data have already demonstrated their success are many-fold. As orthogonal to these emerging research contexts, a number of research challenges are capturing the attention of a large community of researchers, ranging from models, algorithms and techniques for warehousing and OLAPing non-conventional data to ETL and data integration approaches for supporting this task, from storage issues to privacy-preserving issues of warehousing and OLAPing complex, spatial and spatio-temporal data; from models, algorithms and techniques for querying complex, spatial and spatio-temporal data in warehousing and OLAP environments to models, algorithms and techniques for mining complex, spatial and spatio-temporal data in warehousing and OLAP environments. In order to fulfill innovative research challenges and system-oriented requirements posed by the issue of warehousing and OLAPing such kind of data, this special issue on " Warehousing and OLAPing Complex, Spatial and Spatio-Temporal Data " of Fundamenta Informaticae presents a rigorous selection of best papers of the track Warehousing and OLAPing Complex, Spatial and Spatio-Temporal Data attracted a relevant number of submissions, and, after a rigorous selection two-round review process over the best papers, only 5 papers have been finally accepted for final publication in the special issue on " Warehousing and OLAPing Complex, Spatial and Spatio-Temporal Data ". The aim of the special issue is to offer an innovative, modern research perspective on the issue of warehousing and OLAPing complex, spatial and spatio-temporal data, by highlighting recent top-quality