A Framework for the Classification and Description of Multidimensional Data Models

Abelló, Alberto; Samos, José; Saltor, Fèlix

doi:10.1007/3-540-44759-8_65

Cited by 42 publications

(25 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most of the multidimensional models documented in the literature are based on business data (Abello et al, 2001) and thus may not meet the requirements of biomedical data warehousing. Pedersen et al (2001) evaluated 14 existing multidimensional models against the requirements of clinical data warehousing and found that none of these models support all the requirements.…”

Section: Application Of Existing Multidimensional Modelsmentioning

confidence: 99%

BioStar models of clinical and genomic data for biomedical data warehouse design

Zhang¹,

Ramanathan²

2005

IJBRA

View full text Add to dashboard Cite

Biomedical research is now generating large amounts of data, ranging from clinical test results to microarray gene expression profiles. The scale and complexity of these datasets give rise to substantial challenges in data management and analysis. It is highly desirable that data warehousing and online analytical processing technologies can be applied to biomedical data integration and mining. The major difficulty probably lies in the task of capturing and modelling diverse biological objects and their complex relationships. This paper describes multidimensional data modelling for biomedical data warehouse design. Since the conventional models such as star schema appear to be insufficient for modelling clinical and genomic data, we develop a new model called BioStar schema. The new model can capture the rich semantics of biomedical data and provide greater extensibility for the fast evolution of biological research methodologies.

show abstract

Section: Application Of Existing Multidimensional Modelsmentioning

confidence: 99%

BioStar models of clinical and genomic data for biomedical data warehouse design

Zhang¹,

Ramanathan²

2005

IJBRA

View full text Add to dashboard Cite

show abstract

“…Transactional Processes (OLTP) and Online Analytical Processes (OLAP) [15]. Figure 11 summarizes these differences.…”

Section: Source Data Misconceptionsmentioning

confidence: 99%

A Data Warehouse to Support Condition Based Maintenance (CBM)

Henderson¹,

Kwinn²

2005

View full text Add to dashboard Cite

The United States Army's legacy maintenance strategy for its helicopter fleet is centered on replacing and repairing components based on aircraft hours flown. This strategy overlooks how variations in environmental conditions, component stresses, and other exogenous factors effect the lifetime of specific components across the entire fleet of Army Aviation Aircraft. This report describes the design and implementation of a data warehouse that subsumes many disparate databases currently housing information about these factors. This data warehouse supports a common synchronized "maintenance picture" that includes state, health, usage, and logistics data for any component on any helicopter in the fleet. This view enables researchers and planners to individually manage component maintenance according to a "condition based" policy. This report discusses a systems engineering approach to creating a data warehouse including logical and physical designs, data management strategies, and an implementation plan. Discussion is also included detailing how the warehouse might be adopted for conditioned-based maintenance of all Army systems. This CBM approach is highly reliant on a common, synchronized, and high-fidelity information system. This system must include all relevant data sources from any aspect of a component's life. Currently, such a system does not exist. The incumbent maintenance system does feature many important wellsprings of maintenance information. However, each of these data sources was developed for a specific purpose, and each has its own way of representing various aspects of the maintenance domain. These data subsystems have very different and inconsistent data definitions, data relationships, and data transformation rules. Operational NeedWhat is needed is a common and freely available data warehouse that not only subsumes these existing data sources, but also accommodates any relevant data source from a component's life. This data warehouse will provide a comprehensive picture of all relevant information about the life of a component, and assist analyst, engineers, and managers with making the transition to condition based maintenance. 7This report focuses on the design of such a data warehouse to support a CBM Prototype. The CBM Prototype is an initial effort that demonstrates and explores the capabilities of the CBM concept. This prototype includes two primary research efforts. The first effort focuses on the engineering and reliability analysis necessary to realize CBM. The second effort, and the focus of our work, examines the data warehouse needed to support this analytical effort. Design MethodologyIn an effort to inject process into the development of the data warehouse, we must first adopt an effective systems engineering methodology. A systems engineering methodology represents a systematic way of decomposing a high-level need into a set of well defined requirements and accompanying designs to satisfy these requirements. Many such processes are described and compared in Stakeholde...

show abstract

“…In this work we apply a set of QVT [2] relations to the development of a secure DW. Various approaches for the conceptual design of the DW repository have been proposed in [4,5,6,7]. These proposals are twofold; on the one hand they try to represent the main MD properties at the conceptual level by abstracting away details of the target database platform where the DW will be implemented.…”

Section: Introductionmentioning

confidence: 99%

Transforming Conceptual Model into Logical Model for Temporal Data Warehouse Security: A Case Study

Salah¹,

Marie²,

El-Fangary³

et al. 2012

IJACSA

View full text Add to dashboard Cite

Abstract-Extraction-transformation-loading (ETL) processes are responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. Data warehouse often store historical information which is extracted from multiple, heterogeneous, autonomous and distributed data sources, thereby, the survival of the organizations depends on the correct management, security and confidentiality of the information. In this paper, we are using the Model Driven Architecture (MDA) approach to represent logical model requirements for secure Temporal Data Warehouses (TDW). We use the Platform-Independent Model (PIM) which does not include information about specific platforms and technologies. Nowadays, the most crucial issue in MDA is the transformation between a PIM and Platform Specific Models PSM. Thus, OMG defines use the Query/View/Transformation (QVT) language, an approach for expressing these MDA transformations. This paper proposes a set of rules to transform PIM model for secure temporal data warehouse (TDW) to PSM model, we apply the QVT language to the development of a secure data warehouse by means of a case study.

show abstract

A Framework for the Classification and Description of Multidimensional Data Models

Cited by 42 publications

References 10 publications

BioStar models of clinical and genomic data for biomedical data warehouse design

BioStar models of clinical and genomic data for biomedical data warehouse design

A Data Warehouse to Support Condition Based Maintenance (CBM)

Transforming Conceptual Model into Logical Model for Temporal Data Warehouse Security: A Case Study

Contact Info

Product

Resources

About