Table of Contents

CSV is possibly the most common data format in everyday use. In this article we work through the process of converting National Provider Identifier data into RDF, first with a mechanical translation that can be applied to any CSV file and then with a custom translation which supports easy querying.

The term 'Data Lake' has become a popular buzzword in 2016. Practically, organizations of all kind are accumulating large collections of heterogenous files in conventional file stores, distributed file systems such as HDFS, and object storage systems such as Amazon S3. The 'Data Lake' trend combines the ability of hyperconverged systems to do a full scan of such a document collection quickly and repeatably with innovations in data mining, artificial intelligence, knowledge representation, ontologies, and a number of fields to discover ways to repurpose data after it has been captured.

JSON, and many popular programming languages, use binary floating point numbers to represent numbers with a fractional part (and sometimes even numbers without a fractional part.) Unfortunately, binary floating point numbers don't correctly represent fractions where the denominator is not a power of two, such as US dollars divided into 100 cents. A lot is at stake when do calculations involving money, so it makes sense to use the xsd:decimal datatype for money. Although JSON does not support decimal numbers natively, this functionality can be added with JSON-LD.

In this chapter we show the reader how Jena Rules work at the individual level, how Jena Rules can be used for forwards and backward chaining and a bit of how it compares to alternatives such as Drools, Clara and SPIN.

Real semantics unifies document management, ontology management, database management, and code generation and to do all that you need a strategy for working with documents. This document describes the choice of HTML 5 document format and gives an overview of the unique way Real Semantics works with HTML 5.

Unlike some programming languages, Java does not support multiple line quotes. This makes it awkward to embed things such as SPARQL queries, RDF facts, and reasoner fact sets in Java code. Real Semantics contains a system that automatically injects objects defined in the SPARQL, Turtle and Jena rules language into Java objects, with a simple mechanism that sets the stage for keeping metadata about RDF objects used inside this system.

Being a way to write schemas with RDF vocabulary, the K Schema has a lot superficially common with RDFS. However, the K Schema is a better match for data that is already represented in a relational, object-oriented, or other common style. Level 0 of the K Schema associates a list of property and resource names with a namespace to support Java code generation as well as a basic layer of validation.

Legalentityidentifier.info is the first application of Real Semantics; growing up alongside the framework, LEI.info demonstrates our data processing, cloud computing and subjective matching capabilities.

Our mental world contains many concepts about worldly facts, and the Microsoft Concept Graph tries to duplicate them. It is a big graph of concepts, which is harnessed from billions of web pages and years' worth of search logs

RDF can be used as a general data representation that maps closely to both SQL and NoSQL databases, as well the data structures used in common programming languages suchas Java and Python. This article introduces this point of view and some mechanisms used in Real Semantics to automatically transform data between RDF and other data formats.

BCBS 239 is a standard set by the Bank for International Settlements which applies to banks which are systemtically important, either on a global or national basis. It raises the bar for IT systems and the challenge of compliance is a major concern of both IT organizations and the C-Suite. Real Semantics could be the first IT architecture designed with BCBS 239 in mind.

Documentation for software systems frequently contains snippets of code, output and other content that must be rendered in a special way. Real Semantics has facilities to transclude such snippets from multiple places in the code to make it easy to display such code without cut and pasting it so we can display actual code and actual results that are backed by automated tests.

The Ontology2 Edition of DBpedia 2015-10 is a freeze dried snapshot of DBpedia packaged together with Openlink Virtuoso and a powerful cloud server on the AWS Marketplace. This case study describes the business case for this product, how Real Semantics builds this product with the henson module, and the decisions we've made that affect what kind of virtual enviroments Real Semantics supports.

The structure of the Real Semantics system as reflected by the maven modules that comprise Real Semantics and their declared documentation and relationships.