Querying Compressed XML Data

Because of increasing use of XML data on the internet, the need for an efficient method of storing and querying XML data is vital. So far, two major types of system for XML data management have been introduced: XML Enabled systems and XML native systems. The former uses relational database system for storing and querying XML data and the latter is a special XML database system which is based on XML data model. Since relational database systems are more mature than XML native systems, it seems that the use of abilities and efficiencies of relational systems is more economical. In this article, we have introduced a new relational schema named XLight for storing and processing XML data, and we have compared it with some similar methods.

As Extensible Markup Language (XML) [5] is emerging as the data format of the internet era, there are increasing needs to effciently store and query XML data. One way towards this goal is using relational database by transforming XML data into relational format. In this paper, we argue that existing transformation algorithms are not complete in the sense that they focus only on structural aspects and ignoring semantic aspects. We present the semantic knowledge that needs to be captured during the transformation to ensure a correct relational schema. Further, we show a simple algorithm that can 1) derive such semantic knowledge from the given XML Document Type Definition (DTD) and 2) preserve the knowledge by representing them in terms of semantic constraints in relational database terms. By combining the existing transformation algorithms and our constraints-preserving algorithm, one can transform XML DTD to relational schema where correct semantics and behaviors are guaranteed by the preserved constraints. Experimental results are also presented.

XML is rapidly becoming one of the most adopted standard for information representation and interchange over the Internet. With the proliferation of mobile devices of communication such as palmtop computers in recent years, there has been growing numbers of web applications that generate tremendous amount of XML data transmitted via the Internet. We therefore need to investigate an effective means to handle such ever-growing XML data in various merging activities such as aggregation, accumulation or updating, in addition to storing and querying XML data. Previously, we recognized that FDs are an important and effective means to achieve consistent XML data merging, which we restricted data consistency for leaf nodes in an XML data tree. In this paper we further extend FDs to be satisfied in an XML document by comparing subtrees in a specified context of an XML tree. Given an XML tree T and a set of FDs F defined over a set of given path expressions, called targeted functional path expressions, we tackle the problem of repairing the inconsistency with respect to F in the most concise merged format of T.

The Extensible Markup Language (XML) is emerging as the dominant data format for data exchange between applications. Many translation techniques have been devised to publish large amounts of existing conventional relational data in XML format. There also exists a need to be able to represent imprecise data in both relational databases and XML. This paper describes a fuzzy XML schema model for representing a fuzzy relational database in XML format. It also outlines a translation algorithm to include fuzzy relations and similarity matrices with their associated conventional relations. We also describe how the proposed fuzzy XML schema and the conversion process from fuzzy relational data into fuzzy XML have been integrated into VIREX, which is a prototype with powerful visual tool for transforming relational data into XML.KeywordsFuzzy XMLFuzzy Relational DatabaseSchema ConversionVisual Interface

Due to the rapid growth of XML representation for information exchange, XML databases have been widely adopted in a variety of applications. This paper presents two layers of optimisation for dealing with large XML databases: (1) OXDP (Object-Based Methodology for XML Data Partitioning) which has been developed to partition XML data efficiently and (2) OXiP (Object-Based XML Indexing for Partitions) which is an indexing and linking mechanism for partitioned data. OXDP provides optimal XML data partitioning based on an object’s semantic features which improves XML data query performance. The OXiP method tokenises all rooted label paths and preserves the pathways within each XML object partition. The semanticbased data partition ultimately enhances the notion of a frequently accessed data subset which is an advantageous feature in our proposed methods to decrease the time to answer queries. Experimentally, OXDP and OXiP can achieve an order of magnitude performance improvement for querying XML data.

Recently, ontology-based data access is more and more employed in the context of data integration. That is, to the usual data layer of an information system we superimpose a conceptual layer to be exposed to the client. In this paper, we discuss a way to query XML data over conceptual layer using Description Logics. Given a XML data file, we first map the XML DTD to a corresponding relational schema preserving the original semantics of the XML DTD, and at the meantime, we store the XML data into the relational database. After that, we create an ontology described in Description Logics with respect to the relational schema. When a Description Logic query is posted to the ontology TBox, we map it to SQL query with respect to the relational database. In this way, we can query XML data using Description Logics. The main contribution of this thesis can be seen as the following two parts: 1. We proposed a mapping from XML DTD to relational schema with constraints preserving the original XML DTD semantics. 2. We described a framework of querying XML data using Description Logics, more precisely, the DL-LiteA logic.

The ability to summarize information from many XML data sources is becoming crucial. Problems that need to be addressed are related to different representations of data and different levels of generality/specificity of data. In this paper we propose to solve these problems by creating a methodology for efficient XML schema diagram transformations in static and dynamic situations. We focus on a graphical approach for XML schema diagram transformations and XML data querying. This approach allows us to design XML processing system for diverse XML documents. In the paper we classify schema diagram changes based on adding/removing/modifying element attributes, and changing the structure of the elements.

Millau: an encoding format for efficient representation and exchange of XML over the Web

Algorithms and programming models for efficient representation of XML for Internet applications

Web service caching, i.e., caching the responses of XML web service requests, is needed for designing scalable web service architectures. Such caching of dynamic content requires maintaining the caches appropriately to re.ect dynamic updates to the back-end data source. In the database, especially relational, context, extensive research has addressed the problem of incremental view maintenance. However, only a few attempts have been made to address the cache maintenance problem for XML web service messages. We propose a middleware solution that bridges the gap between the cached web service responses and the backend dynamic data source. We assume, for generality, that the back-end source has a general XML logical data model. Since the RDBMS technology is widely used for storing and querying XML data, we show how our solution can be implemented when the XML data source is implemented on top of an RDBMS. Such implementation exploits the well-known maturity of the RDBMS technology. The middleware solution described in this paper has the following features that distinguish it from the existing technology in this area: (1) It provides declarative description of Web Services based on rich and standards-based view speci.cation language (XQuery/XPath); (2) No knowledge of the source XML schema is assumed, instead the source can be any general well-formed XML data; (3) The solution can be easily deployed on RDBMS, and (4) The size of the auxiliary data needed for the cache maintenance does not depend on the source data size, therefore, the solution is highly scalable. Experimental evaluation is conducted to assess the performance bene.ts of the proposed approach.

XML – the Extensible Markup Language has recently emerged as a standard for information representation and exchange on the internet, because of its portability, versatility and extensibility. As the large increase in the availability of such data, there is a need of an appropriate storage and an integration solution for future analysis and decision-making. Data warehouses systems provide a suitable means to organise and manage XML data for decision-making. However, XML data warehouse has some special requirements such as mixed content and irregular structure of XML data sources, which make existing traditional data warehouse approaches and techniques unsuitable. In this paper, we give an overview of current state of the art concerning how XML technologies can be combined with data warehousing systems, by the presentation of the most relevant XML warehousing approaches proposed in the literature.

This paper describes Sucxent, a novel system for the storage and querying of XML data using a relational database system (RDBMS). The relational schema proposed under Sucxent does not require the knowledge of the DTDs of the XML documents being stored. In this approach we store only the leaf nodes and their text values together with their ancestor list. Doing so will eliminate θ ( )-joins to answer XPath-expression based queries. θ-joins account for a major performance bottleneck in current approaches for storing XML data in an RDBMS. We also compare the performance of our system to two existing approaches for relational storage of XML documents, XRel and XParent, to demonstrate the effectiveness of our approach. We show that our system performs significantly better than XRel and XParent in terms of insertion, extraction and querying of XML documents.

Whenever XML is used as the data format to exchange large amounts of data or even for data streams, the verbose behavior of XML is one of the bottle necks. While compression of XML data seems to be a way out, it is essential for a variety of applications that the compression result still can be parsed, searched, transformed or modified efficiently. In order to support efficient search in compressed XML data, we have devel oped a compression technique that links two components: the first component uses the DTD to perform a structure-preserving compression of XML markup data, while the second uses a trie for the compression of text constants and attribute values.

XML (eXtensible Markup Language) documents are the main format for publishing and interchanging data on the Web. Integrity constraints are essential in data design. Functional dependencies are the most important semantic constraints. Functional dependencies satisfied by XML data have been introduced recently. Formal Concept Analysis (FCA) is a mathematical theory of concept hierarchies which is based on Lattice Theory. Data is represented as a two-dimensional context of objects and attributes. FCA discovers dependencies within the data based on the relation among objects and attributes. In this paper we take a first step towards using an FCA approach to study functional dependencies in XML databases. The novelty of our approach is the software, which analyzes an XML document, constructs the Formal Context corresponding to the flat representation of the XML data and finds the implications, which are functional dependencies in XML data.

Chapter 4 - Identifying And Avoiding SOA Performance Problems