BigCube: A Metamodel for Managing Multidimensional Data

New emerging scientific applications in geosciences, sensor and spatio-temporal domains require adaptive analysis frameworks that can handle large datasets with multiple dimensions. However, existing conceptual design strategies for multidimensional data using the data warehousing framework are not suitable for users, since they involve complex extensions of traditional database design frameworks like E/R and UML diagrams, or the relational star and snowflake schema. There is a lack of a generalized model that provides a tric design approach to let analysts abstractly design and query multidimensional data. In this paper, we propose a solution to this problem by presenting a generic metamodel for multidimensional data that keeps the user as the focal point and achieves a straction for all users. Our model called the BigCube provides users with a set of multidimensional abstract data types for data modeling and includes aggregate operations for performing analysis. Overall, we provide ...

• Type: Journal
• Year: 2010
• Where: SEDE
• Authors: Ganesh Viswanathan, Markus Schneider
• Keywords: Multidimensional, Multidimensional Abstract Data, Multidimensional Data, SEDE 2010, Software Engineering