Laura Irina Rusu

A Methodology for Building XML Data Warehouses

Developing a data warehouse for XML documents involves two major processes: one of creating it, by processing XML raw documents into a specified data warehouse repository; and the other of querying it, by applying techniques to better answer users’ queries. This paper focuses on the first part; that is identifying a systematic approach for building a data warehouse of XML documents, specifically for transferring data from an underlying XML database into a defined XML data warehouse. The proposed methodology on building XML data warehouses covers processes including data cleaning and integration, summarization, intermediate XML documents, and updating/linking existing documents and creating fact tables. In this paper, we also present a case study on how to put this methodology into practice. We utilise the XQuery technology in all of the above processes.

On Building XML Data Warehouses

Developing a data warehouse for XML documents involves two major processes: one of creating it, by processing XML raw documents into a specified data warehouse repository; and the other of querying it, by applying techniques to better answer user’s queries. The proposed methodology in our paper on building XML data warehouses covers processes such as data cleaning and integration, summarization, intermediate XML documents, and updating/linking existing documents and creating fact tables.

Maintaining versions of dynamic XML documents

The ability to store information contained in XML documents for future references becomes a very important issue as the number of applications which use and exchange data in XML format is growing continuously. Moreover, the contents of XML documents are dynamic and they change across time. However, storing all document versions in an XML data warehouse would introduce a high level of redundancy. Nevertheless the ability to store XML documents together with their different versions across time is often required. Our paper proposes a novel approach for storing changes of dynamic XML documents in time with less overhead so earlier versions can be easily queried. We show how our proposed consolidated delta is built, with steps and rules of the algorithm involved and we demonstrate the efficiency of the versioning approach in terms of storage and retrieval using some test data.

Partitioning methods for multi-version XML data warehouses

Due to an explosive increase of XML documents, it is imperative to manage XML data in an XML data warehouse. XML warehousing imposes challenges, which are not found in the relational data warehouses. In this paper, we firstly present a framework to build an XML data warehouse schema. For the purpose of scalability due to the increase of data volume, we propose a number of partitioning techniques for multi-version XML data warehouses, including document based partitioning, schema based partitioning, and cascaded (mixed) partitioning model. Finally, we formulate cost models to evaluate various types of queries for an XML data warehouse.

Storage techniques for multi-versioned XML documents

Following the increased popularity of using XML documents for information exchange between applications and representing semi-structured data, the issue of warehousing collections of XML documents has become strongly imperative. The focus of this paper is on the storage of dynamic (multiversioned) XML documents. In this paper we present four different storage methods for dynamic XML documents, and evaluate each of them using two performance indicators, namely I/O loading and versioning costs.

Warehousing dynamic XML documents

Due to the increased popularity of using XML documents in exchanging information between diverse types of applications or in representing semi-structured data, the issue of warehousing large collections of XML documents has become strongly imperative. Furthermore, an efficient XML warehouse needs to be able to answer various user queries about its content or about the history of the warehoused documents. In this paper, we propose a methodology for warehousing dynamic XML documents, which allows a low degree of redundancy of the warehoused data, while preserving critical information.

Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments

Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments discusses developments in data mining and warehousing as well as techniques for successful implementation. Contributions investigate theoretical queries along with real-world applications, providing a useful foundation for academicians and practitioners to research new techniques and methodologies.

Intelligent Dynamic XML Documents Clustering

Clustering as an intelligent technique for mining XML documents has been utilised as an excellent way of grouping the documents by their content or structure. A main step in many distance based XML clustering algorithms is to calculate pair-wise distances between documents; naturally, a time-efficient technique requests the pair-wise distances to be determined in a timely manner. In case of dynamic XML documents, the amount of changes between versions cannot be predicted. Therefore, in case of clustered dynamic XML documents, if changes were little or if they affected only some of the clustered documents, recalculating pair-wise distances every time would be highly redundant. In this paper we propose a time-efficient technique to reassess pair- wise distances between clustered dynamic XML documents which change in time, without performing redundant calculations but considering the previously known distances and the set of changes which might have affected the documents versions.

Moving towards a collaborative decision support system for aeronautical data

The recent effort in global information standardization within the aviation industry has triggered an increased need for aviation data to be readily available, accurate and easy for stakeholders to use. Aviation management systems are generally based on old proprietary disparate systems, so there is a growing need for a system which could act as a collaborative decision support system, where the same right data can be provided at the right time to the right users. This system would not only eliminate the need to manually retrieve required information from multiple systems and reduce the possibility of human error, it would also allow the discovery of any hidden knowledge, a task otherwise not possible from separate systems. This paper presents our proposed approach to build an integrated system for data-intensive collaborative decision support. Each stage in the proposed framework is explained, including a section on the performance evaluation of the proposed system.

A Right-Time Refresh for XML Data Warehouses

The new era of business intelligence and web data warehousing has brought in new research and development issues, whereby it is imperative to have an efficient refresh process for the information in the XML warehouses. Existing strict real-time or static timestamp-based refresh mechanisms are not always efficient. In this paper, we propose to build a waiting queue to make the XML warehouse refresh processes discrete, based on (i ) Level of Criticality (LoC), (ii ) Impact on Reports (IoR), and (iii ) Frequency of Appearance (FoA). Our experimental results have shown the effectiveness of our proposed method.