Astrophysical Data Mining: A Review of Multidimensional Indexing and Data Warehousing Techniques

Title: Astrophysical Data Mining: A Review of Multidimensional Indexing and Data Warehousing Techniques

Abstract: This study reviews the use of data mining techniques in astrophysics, focusing on multidimensional indexing and data warehousing. It highlights the challenges posed by the heterogeneity, high dimensionality, and multiplicity of astronomical data, and proposes data warehousing as a solution. The article discusses the star schema, dimensions, hierarchies, and measures, which form the characteristic structure of a data warehouse. It also emphasizes the importance of metadata in providing information about the data's origin and context.

Main Research Question: How can data mining techniques be effectively applied to manage and analyze the vast and complex data sets in astrophysics?

Methodology: The study reviews existing literature and research on data mining, multidimensional indexing, and data warehousing. It examines how these techniques can be applied to astrophysical data and discusses their benefits and challenges.

Results: The review found that data warehousing can be an effective solution for managing and analyzing astronomical data. The star schema, dimensions, hierarchies, and measures can help organize and query the data, making it easier for researchers to access and analyze the information.

Implications: The use of data warehousing and data mining techniques in astrophysics can lead to more efficient and effective data management and analysis. It can help researchers extract valuable information from large and complex data sets, leading to new discoveries and advancements in the field. However, further research is needed to develop and refine these techniques for specific astrophysical applications.

Link to Article: https://arxiv.org/abs/0402016v1 Authors: arXiv ID: 0402016v1