Rule Execution with SHACL

In my previous post, Using Jena and SHACL to validate RDF Data, I have looked at how RDF data can be validated using SHACL. A closely related concern to that of constraints checking, is rule execution, for which SHACL can also be used.

A SHACL Rule Example

We will again use an example from the SHACL specification. Assume we have the a file rectangles.ttl that contains the following data:

rectangle

rectangles.ttl

Assuming we want to infer that when the height and width of a rectangle are equal, the rectangle represents a square, the following SHACL rule specification can be used (which we will store in rectangleRules.ttl):

rectangleRules

rectangleRules.ttl

A Code Example using Jena

Naturally you will need to add SHACL to your Maven pom dependencies. Then the following code will execute your SHACL rules:

shaclRuleExecution

SHACL rule execution using Jena

Running the Code

Running the code will cause an inferences.ttl file to be written out to $Project/src/main/resources/. It contains the following output:

inference

inference.ttl

Note that ex:InvalidRectangle has been ignored because it does not adhere to sh:condition ex:Rectangle, since it does not have ex:height and ex:width properties. Also, ex:NonSquareRectangle is a rectangle, not a square.

Conclusion

In this post I gave a brief overview of how SHACL can be used to implement rules on RDF data. This code example is available at shacl tutorial.

Using Jena and SHACL to validate RDF Data

RDF enables users to capture data in a way that is intuitive to them. This means that data is often captured without conforming to any schema. It is often useful to know that an RDF dataset conforms to some (potential partial) schema. This is where SHACL (SHApe Constraint Language), a W3C standard, comes into play. It is a language for describing and validating RDF graphs. In this post I will give a brief overview of how to use SHACL to validate RDF data using the Jena implementation of SHACL.

A SHACL Example

We will use an example from the SHACL specification. Assume we have a file person.ttl that contains the following data:

person

Example RDF data

To validate this data we create a shape definition in personShape.ttl containing:

personShape

Person shape definition

A Code Example using Jena

To validate our RDF data using our SHACL shape we will use the Jena implementation of SHACL. Start by adding the SHACL dependency to your Maven pom.xml. Note that you do not need to add Jena as well as the SHACL pom already includes Jena.

SHACLPom

SHACL Maven dependency

In the code we will assume the person.ttl and personShape.ttl files are in $Project/src/main/resources/. The code for doing the validation is the following then:

personValidation

Java code using Jena implementation of SHACL

Running the Code

Running the code will cause a report.ttl file to be written out to $Project/src/main/resources/. We can determine that our data does not conform by checking the sh:conforms property. We have 4 violations of our ex:PersonShape:

  1. For ex:Alice the ex:ssn property does not conform to the pattern defined in the shape.
  2. ex:Bob has 2 ex:ssn properties.
  3. ex:Calvin works for a company that is not of type ex:Company.
  4. ex:Calvin has a property ex:birthDate that is not allowed by ex:PersonShape since it is close by sh:closed true.

A corrected version of our person data may look as follows:

personCorrected

Person data that conforms to our person shape

Conclusion

In this post I have given a brief overview of how SHACL can be used to validate RDF data using the SHACL implementation of Jena. This code example is available at shacl tutorial.

Why does the OWL Reasoner ignore my Constraint?

A most frustrating problem often encountered by people, with experience in relational databases when they are introduced to OWL ontologies, is that OWL ontology reasoners seem to ignore constraints. In this post I give examples of this problem, explain why they happen and I provide ways to deal with each example.

An Example

A typical example encountered in relational databases is that of modeling orders with orderlines, which can be modeled via Orders and Orderlines tables where the Orderlines table has a foreign key constraint to the Orders table. A related OWL ontology is given in Figure 1. It creates as expected Order and Orderline classes with a hasOrder object property. That individuals of Orderline are necessarily associated with one order is enforced by Orderline being a subclass of hasOrder
exactly 1 owl:Thing
.

Order

Figure 1: Order ontology

Two Problems

Two frustrating and most surprising errors given the Order ontology are: (1) if an Orderline individual is created for which no associated Order individual exists, the reasoner will not give an inconsistency, and (2) if an Orderline individual is created for which two or more Order individuals exist, the reasoner will also not give an inconsistency.

Missing Association Problem

Say we create an individual orderline123 of type Orderline, which is not associated with an individual of type Order, in this case the reasoner will not give an inconsistency. The reason for this is due to the open world assumption. Informally it means that the only inferences that the reasoner can make from an ontology is based on explicit information stated in the ontology or what can derived from explicit stated information.

When you state orderline123 is an Orderline, there is no explicit information in the ontology that states that orderline123 is not associated with an individual of Order via the hasOrder property. To make explicit that orderline123 is not in such a relation, you have to define orderline123 as in Figure 2. hasOrder max 0 owl:Thing states that it is known that orderline123 is not associated with an individual via the hasOrder property.

HasNoOrder

Figure 2: orderline123 is not in hasOrder association

Too Many Associated Individuals Problem

Assume we now change our definition of our orderline123 individual to be associated via hasOrder to two individuals of Order as shown in Figure 3. Again, most frustratingly the reasoner does not find that the ontology is inconsistent. The reason for this is that OWL does not make the unique name assumption. This means that individuals with different names can be assumed by the reasoner to represent a single individual. To force the reasoner to see order1 and order2 as necessarily different, you can state order1 is different from order2 by adding DifferentFrom:order2 to order1 (or similarly for order2).

HasTwoOrders

Figure 3: orderline123 has two orders

Constraint Checking versus Deriving Inferences

The source of the problems described here is due to the difference between the
purposes of a relational database and an OWL reasoner. The main purpose of a
relational database is to enable view and edit access of the data in such a way that the integrity of the data is maintained. A relational database will ensure that the data adheres to the constraints of its schema, but it cannot make any claims beyond what is stated by the data it contains. The main purpose of an OWL reasoner is to derive inferences from statements and facts. As an example, from the statement Class: Dog SubclassOf: Animal and the fact Individual: pluto Type: Dog it can be derived that pluto is an Animal, even though the ontology nowhere states explicitly that pluto is an Animal.

Conclusion

Many newcomers to OWL ontologies get tripped up by the difference in purpose of relational databases and OWL ontologies. In this post I explained these pitfalls and how to deal with them.

If you have an ontology modeling problem, you are welcome leaving a comment detailing the problem.