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Posted to dev@jena.apache.org by "Andy Seaborne (Jira)" <ji...@apache.org> on 2021/04/15 08:20:00 UTC
[jira] [Updated] (JENA-2089) RDFS for datasets
[ https://issues.apache.org/jira/browse/JENA-2089?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
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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