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Publication of factual information on the Semantic Web often requires additional explanations to communicate more precisely what it means and/or how it may be used. Rules provide a way to document how the published factual information should be interpreted and/or used, in a precise, unambiguous and, possibly, machine-processible way.

One such case is the publication of a new Semantic Web vocabulary, the goal being to specify (proof-theoretic) semantics for some of the vocabulary elements with a low barrier to entry. The publisher may be any organization that wants to publish a reusable vocabulary.

For instance, the IDM laboratory wants to publish an ontology of the anatomy of the brain cortex and a vocabulary to describe facts about items on brain images, such as can be provided by computer-assisted or automated image analysis tools. Hospital, medical practices and medical imagery laboratories want to use the ontology and vocabulary to improve and streamline their communication.

To communicate the semantics of the properties defined as part of the ontology and of the vocabulary in a clear, precise and unambiguous way, IDM publishes a set of rules to capture relationships between ontology and/or vocabulary properties, e.g.:

Two MaterialAnatomicalEntities (MAE) enving a shared boundary are connected: 
      isMAEBoundedBy(?x1,?x3) Λ isMAEBoundedBy(?x2,?x3) Λ MAE(?x1) Λ MAE(?x2) Λ GyriConnection(?x3)

Two MAE entities having a shared connection are connected:
       connectsMAE(?x3,?x1,?x2) Λ MAE(?x1) Λ MAE(?x2) Λ GyriConnection(?x3)

One MRI laboratory uses an automated image analysis tool to extract facts about brain images and wants to use the ontology and the vocabulary to describe items on the images. The rules are retrieved in the RIF and translated into the rule language specific to the engine used by he application. They are executed to label automatically the brain cortex structures - sulci and gyri - in brain images, based the facts extracted by the image analysis.

On the one hand, the rules are used to communicate semantics for some of the elements of the published ontology in a clear, precise and unambiguous way. On the other hand, they are used to specify how factual information about elements in brain images, such as can be provided by automated image analysis tools, can be used to identify and label anatomical entities in the images.

Other examples, of particular interest of formal standard bodies, include the RDFS and SKOS specifications: inference rules are part of SKOS Core. Where appropriate, inference rules are expressed using the Jena 2 rule syntax, or as RDF statements using the OWL vocabulary. They are described in prose when this is not possible or when the expression would be too cumbersome to be a useful communication tool. A RIF provides implementation neutrality whereby the publisher can convey rule-based expression of semantics in implementation-neutral form, leaving the consumer free to choose whatever implementation approach is appropriate.

Yet other cases involve instance data only. Here the role of rules is only to publish how the data should be used or interpreted. For example, a FOAF user might publish a rule set along with their FOAF record describing which of their phone numbers should be used at which time in the day depending on the day in the week, and so on.