XLight, An Efficient Relational Schema to Store and Query XML Data

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.

The exploitation of large volume of XML (eXtensible Markup Language) data with a limited storage space implies the development of a special and reliable treatment to compress data and query them. This work studies and treats these processes in order to combine them via a mediator while facilitating querying compressed XML data without recourse to the decompression process. We propose a new technique to compress, re-index and query XML data while improving XMill and B+Tree algorithms. We show the reliability and the speed up of the proposed querying system towards response time and answers' exactitude.

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.

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.

As XML data storage and interchange become ubiquitous, analysts and data engineers increasingly need tools to model their data and map it to XML schemas and to reverse engineer XML documents and schemas in support of evolution and integration activities. For effective data management, model transformations require guarantees of properties of interest including guarantees of information and constraintpreservation, redundancy-free and compactness guarantees, and assurances about readability and maintainability. In this paper, we make foundational observations about XML data management, including conceptual modeling for XML data, transformations to and from XML Schema and XML data models, and transformation guarantees concerning properties of interest, and we provide resolutions for conceptual mismatches between XML data management and more traditional data management. Our implemented prototype tools show that these observations and insights can provide a strong foundation for XML data engineering.

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.

Digital broadcasting is a novel paradigm for the next generation broadcasting. It can offer a new opportunity for interactive services such as content-based browsing, non-linear navigation, usage of user preference, and history, etc. On the other hand, one of the important factors for this new broadcasting environment is the interoperability among providers and consumers since the environment is distributed. Therefore a standard metadata for digital broadcasting is required and TV-Anytime metadata is one of the metadata standards for digital broadcasting. It is defined using XML schema, so its instances are XML data. In order to fulfill interoperability, a standard query language is also required and XQuery, which is a forthcoming standard query language for XML data, is a natural choice. In this paper we propose an efficient XML data management system that supports TV-Anytime metadata, especially using XQuery as a query language. Since the volume of metadata would be very large in real situation, our system considers a relational database system as storage. We implement a prototype system and test performance for various typical queries by comparing our system with other general-purpose systems.KeywordsPath ExpressionXPath ExpressionRelational Database SystemDigital BroadcastingMetadata GeneratorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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.

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.

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.

With the advent of IoT, storing, indexing and querying XML data efficiently is critical. To minimize the cost of querying XML data, researchers have proposed many indexing techniques. Nearly all the techniques, partition the XML data into a number of data-streams. To evaluate a query, existing twig pattern matching algorithms process a subset of the data-streams simultaneously. Processing many data-streams simultaneously results in some or all of the following four problems, namely, the accessing of many data nodes which don’t appear in the final solution of a given query, the generation of duplicate results, the generation of huge number of intermediate results, and the cost of merging the generated intermediate results. To the best of our knowledge, all the existing twig pattern matching algorithms suffer from some or all of the above mentioned problems. This paper proposes a new twig pattern matching algorithm called MatchQTP which processes one data-stream at a time and avoids all the above mentioned four problems. It also proposes a new indexing technique called RLP-Index and a new XML node labeling scheme called RLP-Scheme, both of which are used by MatchQTP. Unlike the existing indexing techniques, RLP-Index stores a subset of the data nodes. The rest of the data nodes can be generated efficiently. This minimizes storage space utilization and query processing time and makes RLP-Index the first of its kind. Many experiments were conducted to study the performance of MatchQTP. The results show that MatchQTP is very efficient and highly scalable. It was also compared with four algorithms, three of which are used frequently in the literature to compare the performance of new algorithms and the fourth algorithm is the state-of-the-art algorithm. MatchQTP significantly and consistently outperformed all of them

With the rapidly increasing popularity of XML as a data format, there is a large demand for efficient techniques in storing and querying XML documents. However XML is by nature verbose, due to repeatedly used tags that describe data. For this reason the storage requirements of XML can be excessive and lead to increased costs for data manipulation. Therefore, it seems natural to use compression techniques to increase the efficiency of storing and querying XML data. In this paper, we propose a new approach called SCQX for Storing, Compressing and Querying XML documents. This approach compresses the structure of an XML document based on exploiting repetitive consecutive tags in the structure, and then SCQX stores the compressed XML structure and the data separately in a robust storage structure that includes a set of access support structures to guarantee fast query performance. Moreover, SCQX supports querying of the compressed XML structure directly and efficiently without requiring decompression. An experimental evaluation on sets of XML data shows the effectiveness of our approach.

The paper addresses the problem of using semantic annotations in XML documents for better querying XML data. We assume that the annotations refer to an ontology defined in OWL (Web Ontology Language). The intention is then to combine syntactic querying techniques on XML documents with OWL ontology reasoning to filter out semantically irrelevant answers. The solution presented in this paper is an extension of the declarative rule-based XML query and transformation language Xcerpt. The extension allows to interface an ontology reasoner from Xcerpt rules. This makes it possible to use Xcerpt to filter extracted XML data using ontological information. Additionally it allows to retrieve ontological information by sending semantic queries to a reasoner. The prototype implementation uses DIG (Description Logic interface) for communication with the OWL reasoner RacerPro where the ontology queries are answered.

XML data is likely to be widely used as a data exchange format but users also need to store and query XML data. The purpose of this panel is to explore whether and how to best provide this functionality.

Up until now, you have learned how to work with your own XML data. This includes reading, writing, validating, serializing, and querying XML data. Microsoft has used XML extensively in the .NET Framework. This use of XML comes in different flavors, such as XAML markup of note, server control markup of ASP.NET, and configuration system of the .NET Framework. Understanding the use of XML in the .NET Framework is therefore essential for any .NET developer.