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https://issues.apache.org/jira/browse/JENA-2089?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Andy Seaborne updated JENA-2089:
--------------------------------
    Description: 
This is not a replacement for any of the Jena inference and rules system.

"RDFS for datasets" is dataset and graph wrappers that take a vocabulary, build 
internal datastructures during setup, then apply the RDFS entailments to data, 
for both "match" ({{find}}) and "stream" (materialization) access to the data.
 * RDFS for datasets
 * Scale
 * Data interferences

{{ :x rdf:type ?type}} will returns the types of {{:x}}, deductions from 
{{rdfs:range}} or {{rdfs:domain}}, along with supertypes.

{{rdf:type}} will behave like {{rdf:type/rdfs:SubClassOf*}}.

Coverage: {{subClassOf}}, {{subPropertyOf}}, {{range}} and {{domain}}

It is fixed:
 * The RDFS vocabulary is not visible in the data and any vocabulary use in the 
data is not acted on.
 * The application can not subproperty the RDFS vocabulary (no subproperties of 
{{rdfs:subPropertyOf}}, {{rdfs:subClassOf}}, {{rdfs:range}}, {{rdfs:domain}} or 
{{rdf:type}}.
 * Vocabulary is static, not dynamically editable.
 * Inference in a dataset is "per graph", with the same vocabulary for all 
graphs in a dataset
 * The data can be updated
 * It is backwards chaining for scale.
 * There will be an equivalent Jena inference ruleset and test run both and 
compare the outcomes.

A "data+vocabulary" mode may be provided for graphs (i.e. data and vocabulary 
in the same graph), but not datasets which are split data and vocabulary only. 
Such a combined mode is not necessarily efficient - the focus of the work is 
split data and vocabulary.

The Dataset support will need JENA-2088.

In the future, incorporating directly into TDB1 or TDB2 evaluation, working 
with in {{NodeIds}}, should be possible.

  was:
This is not a replacement for any of the Jena inference and rules system.

"RDFS for datasets" is dataset and graph wrappers that take a vocabulary, build 
internal datastructures during setup, then apply the RDFS entailments to data, 
for both "match" ({{find}}) and "stream" (materialization) access to the data.

 * RDFS for datasets
 * Scale
 * Data interferences

{{ :x rdf:type ?type}} will returns the types of {{:x}}, deductions from 
{{rdfs:range}} or {{rdfs:domain}}, along with supertypes.

{{rdf:type}} will behave like {{rdf:type/rdfs:SubClassOf*}}.

Coverage: {{subClassOf}}, {{subPropertyOf}}, {{range}} and {{domain}}

It is fixed:
 * The RDFS vocabulary is not visible in the data and any vocabulary use in the 
data is not acted on.
 * The application can not subproperty the RDFS vocabulary (no subproperties of 
{{rdfs:subPropertyOf}}, {{rdfs:subClassOf}}, {{rdfs:range}}, {{rdfs:domain}} or 
{{rdf:type}}.
 * Vocabulary is static, not dynamically editable.
 * Inference in a dataset is "per graph", with the same vocabulary for all 
graphs in a dataset
 * The data can be updated
 * It is backwards chaining for scale.
 * There will be an equivalent Jena inference ruleset and test run both and 
compare the outcomes.

A "data+vocabulary" mode may be provided for graphs (i.e. data and vocabulary 
in the same graph), but not datasets which are split data and vocabulary only. 
Such a combined mode is not necessarily efficient - the focus of the work is 
split data and vocabulary.

The Dataset support will need JENA-2088.

In the future, incorporating directly into TDB1 or TDB2 evaluation, working 
with in {{NodeIds}}, should be possible.


> RDFS for datasets
> -----------------
>
>                 Key: JENA-2089
>                 URL: https://issues.apache.org/jira/browse/JENA-2089
>             Project: Apache Jena
>          Issue Type: New Feature
>    Affects Versions: Jena 4.0.0
>            Reporter: Andy Seaborne
>            Assignee: Andy Seaborne
>            Priority: Major
>
> This is not a replacement for any of the Jena inference and rules system.
> "RDFS for datasets" is dataset and graph wrappers that take a vocabulary, 
> build internal datastructures during setup, then apply the RDFS entailments 
> to data, for both "match" ({{find}}) and "stream" (materialization) access to 
> the data.
>  * RDFS for datasets
>  * Scale
>  * Data interferences
> {{ :x rdf:type ?type}} will returns the types of {{:x}}, deductions from 
> {{rdfs:range}} or {{rdfs:domain}}, along with supertypes.
> {{rdf:type}} will behave like {{rdf:type/rdfs:SubClassOf*}}.
> Coverage: {{subClassOf}}, {{subPropertyOf}}, {{range}} and {{domain}}
> It is fixed:
>  * The RDFS vocabulary is not visible in the data and any vocabulary use in 
> the data is not acted on.
>  * The application can not subproperty the RDFS vocabulary (no subproperties 
> of {{rdfs:subPropertyOf}}, {{rdfs:subClassOf}}, {{rdfs:range}}, 
> {{rdfs:domain}} or {{rdf:type}}.
>  * Vocabulary is static, not dynamically editable.
>  * Inference in a dataset is "per graph", with the same vocabulary for all 
> graphs in a dataset
>  * The data can be updated
>  * It is backwards chaining for scale.
>  * There will be an equivalent Jena inference ruleset and test run both and 
> compare the outcomes.
> A "data+vocabulary" mode may be provided for graphs (i.e. data and vocabulary 
> in the same graph), but not datasets which are split data and vocabulary 
> only. Such a combined mode is not necessarily efficient - the focus of the 
> work is split data and vocabulary.
> The Dataset support will need JENA-2088.
> In the future, incorporating directly into TDB1 or TDB2 evaluation, working 
> with in {{NodeIds}}, should be possible.



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