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‪Ajit Narayanan: A grammar engine based on visual language‬‏

Sql to Virtuoso

Mapping Relation Data to RDF with Virtuoso's RDF Views. Among its many talents, OpenLink Virtuoso Universal Server includes SPARQL support and an RDF data store tightly integrated with its relational storage engine. This article provides an overview of how to use Virtuoso to dynamically convert relational data into RDF and expose it from a Virtuoso-hosted SPARQL endpoint. The Resource Description Framework (RDF) forms a fundamental building block in the Semantic Web vision, providing a mechanism for conceptually modeling web data. Today the vast bulk of data held by companies resides in relational databases and, as a result, data that ultimately reaches the web is inherently heterogeneous at both the data schema and DBMS engine levels.

Thus a key infrastructural requirement of the Semantic Web vision is the existence of technology that facilitates the generation of RDF views of relational data. OpenLink's Virtuoso provides such a capability through its RDF Views support. What are RDF Views? Now consider RDF. Mapping Relation Data to RDF with Virtuoso's RDF Views. Semantics. Montague grammar[edit] In the late 1960s, Richard Montague proposed a system for defining semantic entries in the lexicon in terms of the lambda calculus.

Semantics

In these terms, the syntactic parse of the sentence John ate every bagel would consist of a subject (John) and a predicate (ate every bagel); Montague demonstrated that the meaning of the sentence altogether could be decomposed into the meanings of its parts and in relatively few rules of combination. The logical predicate thus obtained would be elaborated further, e.g. using truth theory models, which ultimately relate meanings to a set of Tarskiian universals, which may lie outside the logic.

The notion of such meaning atoms or primitives is basic to the language of thought hypothesis from the 1970s. Despite its elegance, Montague grammar was limited by the context-dependent variability in word sense, and led to several attempts at incorporating context, such as: GeoSPARQL. GeoSPARQL is a standard for representation and querying of geospatial linked data for the Semantic Web from the Open Geospatial Consortium (OGC).

GeoSPARQL

The definition of a small ontology based on well-understood OGC standards is intended to provide a standardized exchange basis for geospatial RDF data which can support both qualitative and quantitative spatial reasoning and querying with the SPARQL database query language. In particular, GeoSPARQL provides for: The Ordnance Survey Linked Data Platform uses OWL mappings for GeoSPARQL equivalent properties in its vocabulary.[3][4] The LinkedGeoData data set is a work of the Agile Knowledge Engineering and Semantic Web (AKSW) research group at the University of Leipzig,[5] a group mostly known for DBpedia, that uses the GeoSPARQL vocabulary to represent OpenStreetMap data. Example[edit] The following example SPARQL query could help model the question "What is within the bounding box defined by WikiMiniAtlas RCC8 use in GeoSPARQL[edit] Parliament.

AKSW/SINA. Tim Berners-Lee.

Sparql

RDF Data Stores. Data munching. Semantic web. ‪From Excel file to RDF with links to DBpedia and Europeana‬‏ ‪The Semantic Web: an introduction‬‏ ‪DBpedia: Visualising Linked Data. Graph of Members of Punk Rock Bands‬‏ ‪DBpedia semantic search with Explore & Query by Vinge Free‬‏ DBpedia. DBpedia ( from "DB" for "database" ) is a project aiming to extract structured content from the information created as part of the Wikipedia project.

DBpedia

This structured information is then made available on the World Wide Web.[1] DBpedia allows users to query relationships and properties associated with Wikipedia resources, including links to other related datasets.[2] DBpedia has been described by Tim Berners-Lee as one of the more famous parts of the decentralized Linked Data effort.[3] Background[edit] The project was started by people at the Free University of Berlin and the University of Leipzig, in collaboration with OpenLink Software,[4] and the first publicly available dataset was published in 2007. It is made available under free licences, allowing others to reuse the dataset. Dataset[edit] From this dataset, information spread across multiple pages can be extracted, for example book authorship can be put together from pages about the work, or the author.

GraphChi. Disk-based large-scale graph computation Introduction GraphChi(huahua) is a spin-off of the GraphLab(rador) project.

GraphChi

GraphChi can run very large graph computations on just a single machine, by using a novel algorithm for processing the graph from disk (SSD or hard drive). Programs for GraphChi are written in similar vertex-centric model as GraphLab. GraphChi runs vertex-centric programs asynchronously (i.e changes written to edges are immediately visible to subsequent computation), and in parallel. GraphChi brings web-scale graph computation, such as analysis of social networks, available to anyone with a modern laptop or PC.

Remarkably, in some cases GraphChi can solve bigger problems in reasonable time than many other available distributed frameworks. Getting Started. NotesAboutVirtuoso - junsbriefcase - Notes for setting up virtuoso on a Linux OS. - Notes for personal projects. Set up on Naxos running Centos: Using the default configure, the tool was installed at /usr/local/virtuoso-opensource Note: Check the version number of the following tools installed on your system: $ autoconf --version $ automake --version $ libtoolize --version $ flex --version $ bison --version $ gperf --version $ gawk --version $ m4 --version $ make --version $ openssl version Make sure that your system has at least 460MB free space Compile Before everything started, I needed to uninstall flex2.5.4 and install flex 2.5.33 manually.

NotesAboutVirtuoso - junsbriefcase - Notes for setting up virtuoso on a Linux OS. - Notes for personal projects

Running 'make' This started at 12:52 Installation make install. CSV to RDF converter from Hugh Williams on 2012-12-13 (public-lod from December 2012)