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Using British Royal Family Data Snippets — to demonstrate SPARQL Query Language-based Reasoning & Inference

Kingsley Uyi Idehen
OpenLink Virtuoso Weblog
Published in
7 min readMay 4, 2016

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Brevity is a function of sophisticated use of language (systematic use of signs, syntax, and semantics for encoding information [data in some context]).

In this post I demonstrate how a few RDF Language sentences about the British Royal Family can enable a SPARQL-compliant RDBMS, equipped with deductive capabilities, to produce inferred query results by way of reasoning & inference against the semantics (nature) of the predicates used in those same few sentences.

http://cdn.playbuzz.com/cdn/03c85b38-12b0-4ccb-836f-e308516b383e/ea3dbf94-a959-4130-8710-86c3641c6b09_560_420.jpg

Courtesy of RDF Language based nanotation, in this case using Turtle Notation, I am able to use this blog post as a structured data source for this exercise — that is, a demonstration of SPARQL Query Language-based reasoning and inference over snippets of data about the British Royal Family.

{
  ## Collection of RDF Language Statements (using 
  ## Turtle Notation) that describe various 
  ## Relationship Types (or Relations) that connect 
  ## various members of the British Royal Family.  
  ## These statements have been created using terms 
  ## from the Relationship Vocabulary at 
  ## http://purl.org/vocab/relationship/
  ## and Described in this URIBurner Document  @prefix rel: <http://purl.org/vocab/relationship/> .  <http://dbpedia.org/resource/Prince_William_of_Wales>
    rel:siblingOf 
    <http://dbpedia.org/resource/Prince_Harry_of_Wales> 
    .
  <http://dbpedia.org/resource/Elizabeth_Bowes-Lyon> 
    rel:ancestorOf
    <http://dbpedia.org/resource/Elizabeth_II_of_the_United_Kingdom> 
    .
  <http://dbpedia.org/resource/Elizabeth_II_of_the_United_Kingdom>
    rel:ancestorOf 
    <http://dbpedia.org/resource/Charles,_Prince_of_Wales> 
    .
  <http://dbpedia.org/resource/Charles,_Prince_of_Wales>
    rel:ancestorOf
    <http://dbpedia.org/resource/Prince_William_of_Wales> ,
    <http://dbpedia.org/resource/Prince_Harry_of_Wales> 
  .
}

Here’s how the data above is interpreted and presented to me by OSDS — the OpenLink Structured Data Sniffer:

Loading the Raw Data

Now that I have my raw data (here in the form of a Turtle-based collection of sentences/statements), I can load it into my SPARQL 1.1-compliant Virtuoso RDBMS using a variety of methods; for instance, I could use the URI that Identifies this document (this blog post) in the FROM clause of a SPARQL query:

DEFINE get:soft "replace" 
SELECT DISTINCT * 
FROM <{URI-Of-This-Document}>
WHERE {?s ?p ?o}

Setting Up Inference Rules
As suggested earlier, I am using terms from the relationship vocabulary to drive this exercise, of which terms I will make Virtuoso aware by performing a few additional steps.

First, I need to get the Relationship Vocabulary — a collection of RDF Language sentences that define a variety of relationship types — loaded into the Virtuoso instance behind our URIBurner service. There are two easy ways to do this:

  1. Use SPARQL with a Virtuoso Pragma (get:soft “replace” or get:soft “add”) that invokes its Sponger Middleware Layer, and the FROM <http://purl.org/vocab/relationship/> clause to retrieve the vocabulary data file, as in—
DEFINE get:soft "replace" 
SELECT * 
FROM <http://vocab.org/relationship/rel-vocab-20100607.rdf> 
WHERE { ?s ?p ?o }

— followed by —

COPY <http://vocab.org/relationship/rel-vocab-20100607.rdf> 
  TO <http://purl.org/vocab/relationship/>

2. Or via a SPARQL 1.1 LOAD command—

DEFINE get:soft "no-sponge"
LOAD <http://vocab.org/relationship/rel-vocab-20100607.rdf> 
  INTO <http://purl.org/vocab/relationship/>

In each case, the Sponger Middleware negotiates the content-format of the vocabulary (which may also be referred to as an ontology, a schema, or a data-dictionary) when retrieving this data from the originating server, en route to local RDF document storage.

You can use this SPARQL query to check whether the ontology has been successfully loaded —

SELECT * 
FROM <http://purl.org/vocab/relationship/>
WHERE { ?s ?p ?o }

Inference Rule Creation
Inference rules are created in the SQL realm of Virtuoso, by associating a uniquely identified Rule with a Vocabulary or Ontology that describes the existence and nature (semantics) of various entity relationship types. Here’s an example of such an association using a SQL command (calling the rdfs_rule_set(); stored procedure) that you can execute using any of Virtuoso’s data access interfaces (command-line iSQL, ODBC, JDBC, HTML-based iSQL, etc.) —

rdfs_rule_set
  ( 'urn:relationships:ontology:inference:rules' , 
    'http://purl.org/vocab/relationship/'
  ) ;

You can then verify the Rule’s Existence with this SQL query —

SELECT * FROM sys_rdf_schema ;

Querying for Inferred Data about the British Royal Family

Each of the following SPARQL query examples includes four elements:

  1. the Query Definition
  2. a Live Link to the Query Results (Solution)
  3. a Live Link to Edit the Query
  4. the implicit option to replace <urn:royals:demo> with <{url-of-this-post}> in the FROM clause of each example

Query 1 — Descendants of Elizabeth Bowes-Lyon (Queen Mother), without Reasoning & Inference

PREFIX rel: <http://purl.org/vocab/relationship/>
SELECT *
FROM <urn:royals:demo>
WHERE
   { <http://dbpedia.org/resource/Elizabeth_Bowes-Lyon>
        rel:ancestorOf   ?o
   }
  • Live Link to the Query Results. This solution is empty, because the Inference Rules were not invoked, and the data did not include any statements explicitly using the rel:ancestorOf property.
  • Live Link to the Query Editor

Query 2 — Descendants of Elizabeth Bowes-Lyon (Queen Mother) using Reasoning & Inference pragma

## Demonstrates effects of the Transitive nature 
## of the rel:ancestorOf relation which is what 
## enables the system to construct an inferred 
## list of descendantsDEFINE input:inference 
  ‘urn:relationships:ontology:inference:rules’PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE
{
   <http://dbpedia.org/resource/Elizabeth_Bowes-Lyon>
        rel:ancestorOf   ?o
}

Query 3 — Descendants of Elizabeth Bowes-Lyon (Queen Mother), using
SPARQL 1.1 Property Paths feature

In this case, the inference & reasoning effect is crafted into the query, rather than being declared. Note: the unary operator “+” indicates a property path of one or more occurrences of the relation in question (rel:ancestorOf) connects the relation subject (the Queen Mother) to one or more objects (descendants, in this case).

PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE
{
  <http://dbpedia.org/resource/Elizabeth_Bowes-Lyon>
    rel:ancestorOf+   ?o
}

Query 4 — Prince Harry’s Sibling using Reasoning & Inference Pragma

You can comment out (using one or more leading “#” characters) the Inference rule pragma (the DEFINE lines) to disable the Reasoning & Inference effects (i.e., generation of inferred data).

## Demonstrates the effects of Symmetric relation 
## semantics; i.e., the query solution is unchanged 
## whether Prince Harry is the Subject or Object of 
## the rel:siblingOf relationsDEFINE input:inference 
  'urn:relationships:ontology:inference:rules'PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE
{
  <http://dbpedia.org/resource/Prince_Harry_of_Wales>
     rel:siblingOf   ?o
}

Query 5 — Relationship Symmetry using SPARQL 1.1 Property Paths

Here, the unary operator “+” indicates a property path comprised of one or more occurrences of the relation (rel:siblingOf) connecting the relation subject (Harry) to one or more siblings; while unary operator “^” indicates a property path of one or more occurrences of the relation (rel:siblingOf) connecting the relation object (Harry) to one or more siblings; and the binary operator “|” provides the OR condition between “+” and “^”.

PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE
{
   <http://dbpedia.org/resource/Prince_Harry_of_Wales>
      ( rel:siblingOf+|^rel:siblingOf )   ?o
}

Query 6 — Queen Elizabeth II Ancestry with Reasoning and Inference

## Demonstrates effects of the Transitive nature 
## of the rel:descendantOf relation, which is what 
## enables the system to construct an inferred list 
## of ancestors. This also demonstrates the Inverse 
## nature of the rel:descendentOf as it relates to 
## rel:ancestorOf, since rel:descendentOf isn't 
## used in any of the sentences used to describe 
## the Royal Family.DEFINE input:inference 
  'urn:relationships:ontology:inference:rules'PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE
{
  <http://dbpedia.org/resource/Elizabeth_II_of_the_United_Kingdom>
      rel:descendantOf   ?o
}

Query 7 — Queen Elizabeth II Ancestry with Reasoning and Inference using SPARQL 1.1 Property Paths

PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE 
   {
      <http://dbpedia.org/resource/Elizabeth_II_of_the_United_Kingdom>
         rel:descendantOf+|^rel:ancestorOf  ?o
   }

Query 8 — Descendants of Queen Elizabeth II, using Reasoning & Inference Pragma

## Demonstrates the effects of the Transitive nature 
## of the rel:ancestorOf relation, which is what 
## enables the system to construct an inferred list 
## of descendantsDEFINE input:inference 
  'urn:relationships:ontology:inference:rules'PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE 
   {
      <http://dbpedia.org/resource/Elizabeth_II_of_the_United_Kingdom>
         rel:ancestorOf   ?o
   }

Query 9 —Descendants of Queen Elizabeth II, using SPARQL 1.1 Property Paths to leverage the Transitive nature of rel:ancestorOf

PREFIX rel: <http://purl.org/vocab/relationship/>SELECT *
FROM <urn:royals:demo>
WHERE 
   {
      <http://dbpedia.org/resource/Elizabeth_II_of_the_United_Kingdom>
      rel:ancestorOf+|^rel:descendentOf   ?o
   }

Conclusion

The concept of a Deductive Database isn’t new; what’s different today is the existence of the open standards (URIs, HTTP, RDF Language, OWL Ontology, and SPARQL) that enable the implementation and delivery of this functionality in a standard form, as exemplified by OpenLink Virtuoso, our SPARQL compliant RDBMS that also includes scalable reasoning and inference functionality.

The ability to create, share, and consume semantically-rich data snippets is a critical requirement for a new generation of smart agents that will increasingly shape our experiences with “Big Data”, “Semantically-enhanced World Wide Web” (a/k/a “Semantic Web”), and the burgeoning “Internet of Things.”

Related

Sparql
Semantic Web
Linked Data
AI
Rdf

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Kingsley Uyi Idehen
OpenLink Virtuoso Weblog

Written by Kingsley Uyi Idehen

3.4K Followers

CEO, OpenLink Software —High-Performance Data Centric Technology Providers.

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