A Temporal Object-Oriented Data Warehouse Model

Author(s):  
Franck Ravat ◽  
Olivier Teste
2003 ◽  
Vol 12 (03) ◽  
pp. 325-363 ◽  
Author(s):  
Joseph Fong ◽  
Qing Li ◽  
Shi-Ming Huang

Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.


Author(s):  
D. Xuan Le ◽  
J. Wenny Rahayu ◽  
David Taniar

This paper proposes a data warehouse integration technique that combines data and documents from different underlying documents and database design approaches. The well-defined and structured data such as Relational, Object- oriented and Object Relational data, semi-structured data such as XML, and unstructured data such as HTML documents are integrated into a Web data warehouse system. The user specified requirement and data sources are combined to assist with the definitions of the hierarchical structures, which serve specific requirements and represent a certain type of data semantics using object-oriented features including inheritance, aggregation, association and collection. A conceptual integrated data warehouse model is then specified based on a combination of user requirements and data source structure, which creates the need for a logical integrated data warehouse model. A case study is then developed into a prototype in a Web-based environment that enables the evaluation. The evaluation of the proposed integration Web data warehouse methodology includes the verification of correctness of the integrated data, and the overall benefits of utilizing this proposed integration technique.


1999 ◽  
pp. 145-168 ◽  
Author(s):  
Vera Goebel ◽  
Ilan Eini ◽  
Ketil Lund ◽  
Thomas Plagemann

1998 ◽  
Vol 07 (03) ◽  
pp. 341-371 ◽  
Author(s):  
STANLEY Y. W. SU ◽  
HSIN-HSING M. CHEN

There has been a considerable amount of work on object-oriented databases, active databases, and deductive databases. The common objective of these efforts is to produce highly intelligent and active systems for supporting the next generation of database applications. These future systems must be capable of capturing the concepts of time and managing not just temporal data but temporal knowledge expressed by knowledge rules. In this paper, we describe our efforts on a temporal object-oriented knowledge model, OSAM*/T, its associated temporal query language, OQL/T, an underlying temporal algebra, TA-algebra, and some implementation techniques. In addition to the features of the traditional object-oriented paradigm, the model is characterized by its strong support of association types and its incorporation of temporal knowledge rules for specifying temporal and other types of semantic constraints associated with object classes and their temporal object instances. The query language is featured by its pattern-based specification of temporal object associations, which allows complex queries with various time constraints to be formulated in a relatively simple way. The temporal algebra provides a set of primitive operators for manipulating homogeneous and/or heterogeneous patterns of temporal object associations, thus providing the needed mathematical foundation for processing and optimizing temporal queries. The implementation techniques include a Delta-Instance and Multi-Snapshot Storage Model, as well as data partitioning and clustering schemes for storage management of temporal knowledge bases.


2002 ◽  
Vol 6 (3) ◽  
pp. 277-294 ◽  
Author(s):  
Ali Frihida ◽  
Danielle J. Marceau ◽  
Marius Theriault

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