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

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”

A standards-related web-based information system

This late breaking proposal introduces the prototype of a web-based information system dealing with standards in the field of annotation

ORE User Guide - Resource Map Implementation in JSON-LD 0.9

Open Archives Initiative Object Reuse and Exchange (OAI-ORE) defines standards for the description and exchange of aggregations of Web resources. OAI-ORE introduces the notion of a Resource Map, an RDF Graph which describes the Aggregation, the aggregated Resources of which it is composed, and the relationships between them (and/or the relationships between these and other resources). Since a Resource Map is an RDF Graph, it can be serialized using any RDF syntax. This document outlines the use of one such syntax for the serialization of Resource Maps: JSON-LD. This document is intended for implementers who have an understanding of ORE concepts and are responsible for the development of applications which generate or process Resource Maps using JSON-LD.This document is available at http://www.openarchives.org/ore/0.9/jsonl

RDF(S) Interoperability Results for Semantic Web Technologies

Interoperability among different development tools is not a straightforward task since ontology editors rely on specific internal knowledge models which are translated into common formats such as RDF(S). This paper addresses the urgent need for interoperability by providing an exhaustive set of benchmark suites for evaluating RDF(S) import, export and interoperability. It also demonstrates, in an extensive field study, the state of-the-art of interoperability among six Semantic Web tools. From this field study we have compiled a comprehensive set of practices that may serve as recommendations for Semantic Web tool developers and ontology engineers

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

The Resource Description Framework and its Schema

International audienceRDF is a framework to publish statements on the web about anything. It allows anyone to describe resources, in particular Web resources, such as the author, creation date, subject, and copyright of an image. Any information portal or data-based web site can be interested in using the graph model of RDF to open its silos of data about persons, documents, events, products, services, places etc. RDF reuses the web approach to identify resources (URI) and to allow one to explicitly represent any relationship between two resources. Such statements can come from any source on the web and be merged with other statements supporting worldwide data integration. Using and reusing URIs, anyone can say anything about any topic, anyone can add to it, and so on. Additionally, using RDFS, one can define domain-specific classes and properties to describe these resources and organize them in hierarchies. These schemas are also published and exchanged in RDF. RDF not only provides a graph model to publish and link data on the web, it also provides the foundational shared data model on which other capabilities are built: querying (SPARQL is built on top of RDF), embedding (RDFa and GRDDL rely on the RDF model), and reasoning (RDFS and OWL are defined on top of RDF). Semantic web is a web to link data and share the semantics of their schemas. RDF provides a recommendation to publish and link data. RDFS provides a recommendation to share the semantics of their schemas. The couple RDF & RDFS is also reused in several other activities of the W3C

Efficient Pattern Matching in Python

Pattern matching is a powerful tool for symbolic computations. Applications include term rewriting systems, as well as the manipulation of symbolic expressions, abstract syntax trees, and XML and JSON data. It also allows for an intuitive description of algorithms in the form of rewrite rules. We present the open source Python module MatchPy, which offers functionality and expressiveness similar to the pattern matching in Mathematica. In particular, it includes syntactic pattern matching, as well as matching for commutative and/or associative functions, sequence variables, and matching with constraints. MatchPy uses new and improved algorithms to efficiently find matches for large pattern sets by exploiting similarities between patterns. The performance of MatchPy is investigated on several real-world problems