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.

SKOS and BibTeX in Creating Semantic Ontology on Medical Articles

There are numerous projects that can serve as useful foundations for forming your ontology. One of such projects is Simple Knowledge Organization System (SKOS), a W3C Recommendation.
SKOS provides a standard way to represent knowledge organization systems such as thesauri, classification schemes using the RDF. Another project is BibTeX, a method of marking up bibliographic data, primarily for use in LaTeX documents, but also useful for generic bibliographic storage.

With Fluent Editor, you can utilize both projects through importing them as references, which can be useful for expressing better organization of knowledge. In this post, we will present how SKOS and BibTeX can be utilized in creating your ontology. Data used in the following ontology is based on an excerpt from a list of medical articles on PubMed Central (PMC).

Fluent Editor 2014 R4 – SWRL Built-ins, Auto-recovery Functionality, OWL2 EL++/OWL-RL Validation, and New Features in Ontology Graph.

A new Fluent Editor 2014  R4 is now available which will present you a few new powerful features. With the new Fluent Editor you will be able to utilize core SWRL built-ins, various OWL2 profiles, visualize your ontology file more effectively, and more to benefit while editing and exploring ontology files. Such new feather are as follows :

• SWRL built-ins
• Auto-recovery functionality
• OWL2-EL++ / OWL-RL validation
• New features in ontology diagram
• Various performance improvements

Ask Data Anything

Ask Data Anything is Cognitum's approach to exploring data by using a subset of natural language which articulates concepts and instances modeled in ontologies to provide a meaningful quering experience. Ask Data Anything seizes on regularities of language to provide a natural interpretation of queries being asked; its semantics are provided via R and rOntorion (alternatively  F# and Ontorion).

Technically, Ask Data Anything is capable of performing projection, sub-setting, grouping and aggregation operations, providing answers for queries involving the following information:

• What? Any of the columns of your data table are considered a quantitative field over which to perform queries,
• How? How the output is to be shown. The results of the query can be retrieved on either a table, histogram or a map,
• Where? (Optional) The "in" preposition allows to restrict the search to an specific named group of items  as happens for instance with continents which can be seeing as a group of countries,
• Of? (Optional) The "of" preposition allows to dive into the data, restricting the desired results to a certain set of types (concepts in the Fluent Editor sense) by searching the data in a certain column for instances (in Fluent Editor sense) of those types; we call this material sub-setting,
• By? (Optional) By which type (in Fluent Editor sense) you would like to group the results for aggregation purposes.
• When? (Optional) Queries can contain time constraints.

Using Active Rules on Fluent Editor

Active rules is the mechanism Fluent Editor provides for executing custom imperative code in C# upon meeting certain criteria described as SWRL rules. Considering that standard SWRL rule axioms consist of two parts, an antecedent (body) and consequent (head), the body part of active rules exactly follows the standard format of SWRL rules. The difference from standard SWRL lies on the head part, on which you can add your custom C# code as a set of execution commands. We provide some mechanism to deal with the nature of distributed environments through a set of core built-ins. Available functions to use in active rules are as follows:
 

• KnowledgeInsert(string knowledge) : Inserts knowledge into your ontology.
• KnowledgeDelete(string knowledge) : Deletes knowledge into your ontology.
• WriteMessage(string msg) : Prints msg on Active Rules Output window. 

Visualization of Ontology Contents - with Ontology Diagram and SWRL Debugger

From the latest release version, Fluent Editor includes a few new features that enhance visualization of ontology, which can help you navigate through the structure of your ontology more intuitively. Possibility of drawing a diagram of ontology is one of such features. Ontology diagrams graphically express relations between concepts and instances - also the materialized ones. 
Another new feature to be introduced is SWRL debugger. SWRL debugger shows binding of rules that took place during the reasoning process over your ontology. It is presented as a list of all the SWRL rules and bound instances. By running SWRL debugger, you can check how SWRL rules work on your ontology.

In this post, we will look through these two features further.