Comparative Analysis of Five XML Query Languages

XML is becoming the most relevant new standard for data representation and exchange on the WWW. Novel languages for extracting and restructuring the XML content have been proposed, some in the tradition of database query languages (i.e. SQL, OQL), others more closely inspired by XML. No standard for XML query language has yet been decided, but the discussion is ongoing within the World Wide Web Consortium and within many academic institutions and Internet-related major companies. We present a comparison of five, representative query languages for XML, highlighting their common features and differences.Comment: TeX v3.1415, 17 pages, 6 figures, to be published in ACM Sigmod Record, March 200

Non-hierarchical Structures: How to Model and Index Overlaps?

Overlap is a common phenomenon seen when structural components of a digital object are neither disjoint nor nested inside each other. Overlapping components resist reduction to a structural hierarchy, and tree-based indexing and query processing techniques cannot be used for them. Our solution to this data modeling problem is TGSA (Tree-like Graph for Structural Annotations), a novel extension of the XML data model for non-hierarchical structures. We introduce an algorithm for constructing TGSA from annotated documents; the algorithm can efficiently process non-hierarchical structures and is associated with formal proofs, ensuring that transformation of the document to the data model is valid. To enable high performance query analysis in large data repositories, we further introduce an extension of XML pre-post indexing for non-hierarchical structures, which can process both reachability and overlapping relationships.Comment: The paper has been accepted at the Balisage 2014 conferenc

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Visual exploration and retrieval of XML document collections with the generic system X2

This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically. After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed

Survey over Existing Query and Transformation Languages

A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas

Development of Use Cases, Part I

For determining requirements and constructs appropriate for a Web query language, or in fact any language, use cases are of essence. The W3C has published two sets of use cases for XML and RDF query languages. In this article, solutions for these use cases are presented using Xcerpt. a novel Web and Semantic Web query language that combines access to standard Web data such as XML documents with access to Semantic Web metadata such as RDF resource descriptions with reasoning abilities and rules familiar from logicprogramming. To the best knowledge of the authors, this is the first in depth study of how to solve use cases for accessing XML and RDF in a single language: Integrated access to data and metadata has been recognized by industry and academia as one of the key challenges in data processing for the next decade. This article is a contribution towards addressing this challenge by demonstrating along practical and recognized use cases the usefulness of reasoning abilities, rules, and semistructured query languages for accessing both data (XML) and metadata (RDF)

Content-Aware DataGuides for Indexing Large Collections of XML Documents

XML is well-suited for modelling structured data with textual content. However, most indexing approaches perform structure and content matching independently, combining the retrieved path and keyword occurrences in a third step. This paper shows that retrieval in XML documents can be accelerated significantly by processing text and structure simultaneously during all retrieval phases. To this end, the Content-Aware DataGuide (CADG) enhances the wellknown DataGuide with (1) simultaneous keyword and path matching and (2) a precomputed content/structure join. Extensive experiments prove the CADG to be 50-90% faster than the DataGuide for various sorts of query and document, including difficult cases such as poorly structured queries and recursive document paths. A new query classification scheme identifies precise query characteristics with a predominant influence on the performance of the individual indices. The experiments show that the CADG is applicable to many real-world applications, in particular large collections of heterogeneously structured XML documents