1,599 research outputs found

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

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    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”

    Querying Schemas With Access Restrictions

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    We study verification of systems whose transitions consist of accesses to a Web-based data-source. An access is a lookup on a relation within a relational database, fixing values for a set of positions in the relation. For example, a transition can represent access to a Web form, where the user is restricted to filling in values for a particular set of fields. We look at verifying properties of a schema describing the possible accesses of such a system. We present a language where one can describe the properties of an access path, and also specify additional restrictions on accesses that are enforced by the schema. Our main property language, AccLTL, is based on a first-order extension of linear-time temporal logic, interpreting access paths as sequences of relational structures. We also present a lower-level automaton model, Aautomata, which AccLTL specifications can compile into. We show that AccLTL and A-automata can express static analysis problems related to "querying with limited access patterns" that have been studied in the database literature in the past, such as whether an access is relevant to answering a query, and whether two queries are equivalent in the accessible data they can return. We prove decidability and complexity results for several restrictions and variants of AccLTL, and explain which properties of paths can be expressed in each restriction.Comment: VLDB201

    Identification of Design Principles

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    This report identifies those design principles for a (possibly new) query and transformation language for the Web supporting inference that are considered essential. Based upon these design principles an initial strawman is selected. Scenarios for querying the Semantic Web illustrate the design principles and their reflection in the initial strawman, i.e., a first draft of the query language to be designed and implemented by the REWERSE working group I4

    Effective and Efficient Data Access in the Versatile Web Query Language Xcerpt

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    Access to Web data has become an integral part of many applications and services. In the past, such data has usually been accessed through human-tailoredHTMLinterfaces.Nowadays, rich client interfaces in desktop applications or, increasingly, in browser-based clients ease data access and allow more complex client processing based on XML or RDF data retrieved throughWeb service interfaces. Convenient specifications of the data processing on the client and flexible, expressive service interfaces for data access become essential in this context.Web query languages such as XQuery, XSLT, SPARQL, or Xcerpt have been tailored specifically for such a setting: declarative and efficient access and processing ofWeb data. Xcerpt stands apart among these languages by its versatility, i.e., its ability to access not just oneWeb format but many. In this demonstration, two aspects of Xcerpt are illustrated in detail: The first part of the demonstration focuses on Xcerpt’s pattern matching constructs and rules to enable effective and versatile data access. It uses a concrete practical use case from bibliography management to illustrate these language features. Xcerpt’s visual companion language visXcerpt is used to provide an intuitive interface to both data and queries. The second part of the demonstration shows recent advancements in Xcerpt’s implementation focusing on experimental evaluation of recent complexity results and optimization techniques, as well as scalability over a number of usage scenarios and input sizes

    State-of-the-art on evolution and reactivity

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    This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

    Knowledge Rich Natural Language Queries over Structured Biological Databases

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    Increasingly, keyword, natural language and NoSQL queries are being used for information retrieval from traditional as well as non-traditional databases such as web, document, image, GIS, legal, and health databases. While their popularity are undeniable for obvious reasons, their engineering is far from simple. In most part, semantics and intent preserving mapping of a well understood natural language query expressed over a structured database schema to a structured query language is still a difficult task, and research to tame the complexity is intense. In this paper, we propose a multi-level knowledge-based middleware to facilitate such mappings that separate the conceptual level from the physical level. We augment these multi-level abstractions with a concept reasoner and a query strategy engine to dynamically link arbitrary natural language querying to well defined structured queries. We demonstrate the feasibility of our approach by presenting a Datalog based prototype system, called BioSmart, that can compute responses to arbitrary natural language queries over arbitrary databases once a syntactic classification of the natural language query is made

    Modular Web Queries — From Rules to Stores

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    Even with all the progress in Semantic technology, accessing Web data remains a challenging issue with new Web query languages and approaches appearing regularly. Yet most of these languages, including W3C approaches such as XQuery and SPARQL, do little to cope with the explosion of the data size and schemata diversity and richness on the Web. In this paper we propose a straightforward step toward the improvement of this situation that is simple to realize and yet effective: Advanced module systems that make partitioning of (a) the evaluation and (b) the conceptual design of complex Web queries possible. They provide the query programmer with a powerful, but easy to use high-level abstraction for packaging, encapsulating, and reusing conceptually related parts (in our case, rules) of a Web query. The proposed module system combines ease of use thanks to a simple core concept, the partitioning of rules and their consequences in flexible “stores”, with ease of deployment thanks to a reduction semantics. We focus on extending the rule-based Semantic Web query language Xcerpt with such a module system though the same approach can be applied to other (rule-based) languages as well
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