4. Quelques applications et outils RDF. Semantic Enterprise Composite Offering. From MIKE2.0 Methodology Introduction The Semantic Enterprise Solution Offering provides a layer for the enterprise to establish coherence, consistency, and interoperability across its information assets. Applicable information assets may range fully from structured to unstructured (text and document) sources. The methodology of this Offering is: inherently incrementallayered onto existing capabilities and resourcesflexible to accommodate expansions in scope, new learning, and changes the continuum As an implementation proceeds and extends across the enterprise, there are exciting prospects to shift the locus of knowledge management and tools from vendors and the IT function to practicing knowledge workers. Executive Summary The Semantic Enterprise Offering provides an incremental approach to bring interoperability and common understandings with respect to enterprise information.
These can be applied to the issues related information interoperability. Solution Offering Purpose. Structured Dynamics. Exporter ses données en RDF. Plus d’info sur son compte pearltrees ? RDF Schemas Directory.
APIs. RelFinder - Interactive Relationship Discovery in RDF Datasets. Generating RDF from data.gov - Data-gov Wiki. From Data-gov Wiki Overview Many of the datasets in data.gov are available as tables (spreadsheets). This makes it easy to translate the datasets into RDF by generating a triple for each table cell where the row id is the subject, the column name is the predicate, and the cell content is the object.
Our work adopted the following principles: In the first principle, we minimize our translation by (i) preserving the functional structure of the original tables and (ii) skipping additional understanding of the cell content. In the second principle, we keep the translated RDF friendly to Web users. RDF/XML was chosen because it makes the translated RDF readable by RDF parsers as well as XML parsers, and queryable by SPARQL as well as by Xquery. Our third principle was approached by using a semantic wiki to host user contributed extensions.
To find more details, please go to The Problem Here is an example Properties include: linking files.
Build Your Own NYT Linked Data Application. Now that we’ve published nearly 10,000 of our tags as Linked Open Data, you’re probably wondering what kind of cool applications you can build with this data. To help you get started (and since linked data applications are a little different from your average Web application), we thought we’d provide a sample application and detailed information about how we built it. Our sample application, “Who Went Where,” lets you explore recent Times coverage of the alumni of a specified college or university.
The Who Went Where application (click for larger image) You can find the application here and beautified source code here. Before we dive into the source, let’s take a high-level look at the application’s control (which is fairly straightforward). Wait! Linked Data: The idea behind linked data is super simple. DBpedia: Have you ever noticed those handy little info boxes on certain Wikipedia articles? Step-by-Step to Your Own NYT Linked Data Application Step 1: Initializing the Auto-Complete Field.