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”

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

Using semantics in XML query processing

Ph.DDOCTOR OF PHILOSOPH

AMaχoS—Abstract Machine for Xcerpt

Web query languages promise convenient and efficient access to Web data such as XML, RDF, or Topic Maps. Xcerpt is one such Web query language with strong emphasis on novel high-level constructs for effective and convenient query authoring, particularly tailored to versatile access to data in different Web formats such as XML or RDF. However, so far it lacks an efficient implementation to supplement the convenient language features. AMaχoS is an abstract machine implementation for Xcerpt that aims at efficiency and ease of deployment. It strictly separates compilation and execution of queries: Queries are compiled once to abstract machine code that consists in (1) a code segment with instructions for evaluating each rule and (2) a hint segment that provides the abstract machine with optimization hints derived by the query compilation. This article summarizes the motivation and principles behind AMaχoS and discusses how its current architecture realizes these principles

A survey on tree matching and XML retrieval

International audienceWith the increasing number of available XML documents, numerous approaches for retrieval have been proposed in the literature. They usually use the tree representation of documents and queries to process them, whether in an implicit or explicit way. Although retrieving XML documents can be considered as a tree matching problem between the query tree and the document trees, only a few approaches take advantage of the algorithms and methods proposed by the graph theory. In this paper, we aim at studying the theoretical approaches proposed in the literature for tree matching and at seeing how these approaches have been adapted to XML querying and retrieval, from both an exact and an approximate matching perspective. This study will allow us to highlight theoretical aspects of graph theory that have not been yet explored in XML retrieval

A node partitioning strategy for optimising the performance of XML queries

For ease of communication between heterogeneous systems, the eXtensible Markup Language (XML) has been widely adopted as a data storage format. However, XML query processing presents issues both in terms of query performance and updatability. Thus, many are choosing to shred XML data into relational databases in order to benet from its mature technology. The problem with this approach is that (often complex and time consuming) data transformation processes are required to transform XML data to relational tables and vice versa. Additionally, many of the benets of XML data can be lost during these processes. In this dissertation, we present a process that partitions nodes within an XML document into disjoint subsets. Briefly, as there are fewer partitions than there are nodes, a more efficient join operation can be performed between partitions, thus reducing the number of inefficient node comparisons. The number and size of partitions varies depending on the structure and layout in the XML document, and the number of partitions impacts query performance. Therefore, we also provide a partition classication process, which signicantly reduces the number of partitions because each partition class represents many equivalent partitions within the XML document. In this dissertation, we will demonstrate that our approach outperforms similar approaches for a large subset of XML queries by eliminating complex join operations (where possible) during the query process

IDEAS-1997-2021-Final-Programs

This document records the final program for each of the 26 meetings of the International Database and Engineering Application Symposium from 1997 through 2021. These meetings were organized in various locations on three continents. Most of the papers published during these years are in the digital libraries of IEEE(1997-2007) or ACM(2008-2021)

A Survey on Mapping Semi-Structured Data and Graph Data to Relational Data

The data produced by various services should be stored and managed in an appropriate format for gaining valuable knowledge conveniently. This leads to the emergence of various data models, including relational, semi-structured, and graph models, and so on. Considering the fact that the mature relational databases established on relational data models are still predominant in today's market, it has fueled interest in storing and processing semi-structured data and graph data in relational databases so that mature and powerful relational databases' capabilities can all be applied to these various data. In this survey, we review existing methods on mapping semi-structured data and graph data into relational tables, analyze their major features, and give a detailed classification of those methods. We also summarize the merits and demerits of each method, introduce open research challenges, and present future research directions. With this comprehensive investigation of existing methods and open problems, we hope this survey can motivate new mapping approaches through drawing lessons from eachmodel's mapping strategies, aswell as a newresearch topic - mapping multi-model data into relational tables.Peer reviewe