Using RDF Data Cube Vocabulary to model sales data with Fluent Editor - Example.

RDF Data Cube Vocabulary is a way to represent data in popular format with link data paradigms. Linked data is an approach to publishing data on a web and this vocabulary makes it possible. There are numerous benefits to linked data. The individual observations, and groups of observations, become (web) addressable. This allows publishers ad third parties to annotate and link to this data. For example a report can reference the specific figures it is based on allowing for fine grained provenance trace-back. Representing any data set with these benefits is now possible with Controlled Natural Language in Fluent Editor and it has never been so easy.

Example of energy industry ontology with external references in Fluent Editor

Modern energy sector is a wide area of industry, that concerns numerous aspects, like energy efficiency in different regions, renewable energy sources, energy companies' specializations and many others. Due to the variety of information, it is often difficult to get comprehensive answers to questions about specific fields. Semantic Technology allows to manage this knowledge in a simple and flexible way. It provides versatile description of reality, that is understand and can be adjusted to give complete, comprehensive information in chosen areas. This article presents simple ontology written in Fluent Editor, describing energy industry. It contains information about energy companies, regions and ecological aspects of their activities. You can download this sample ontology through the following link: EnergeoOnt.encnl

Using SWRL built-ins in CNL ontology

The Semantic Web Rule Language (SWRL) is an expressive OWL-based rule language. SWRL extends OWL syntax which allows users to write rules with more powerful deductive reasoning capabilities than OWL alone. SWRL built-ins are one of SWRL’s powerful features, which are predicates to be used to manipulate data values in SWRL rules.

From the latest version, Fluent Editor supports a number of core SWRL built-ins defined in SWRL Built-in Submission. In this post, we will introduce two examples of applying some of SWRL core built-ins to your CNL ontology.

Reasoning about ontologies - fast vs. complete answers

In this article you will gain more intuition about: - how to query your ontology - the difference between reasoner and materialized graph - what is materialization mode OWL-DL and materialization mode OWL-RL+ - when you can use faster OWL RL+ reasoning mode safely You will see two example ontologies: - about books (using data types, cardinality restriction, data type restrictions) - about political preferences (SWRL rules, defining concepts by enumeration) You can reproduce the steps by downloading the ontologies: - my_books.encnl - political_parties.encnl and opening it with FluentEditor on your computer.

About reasoners and materialized graph

With recent FluentEditor releases the user has three tools to query the ontology:

• reasoner of choice (in this example Hermit reasoner is used)
• materialized graph (we can use either OWL-DL or OWL-RL+ materialization mode)
• SPARQL queries