Reusing Dublin Core Ontology - ontology

I'm new in ontology and i'm using protege to create my own. I have imported the Dublin core ontology (http://purl.org/dc/elements/1.1) into my own ontology using protege but only annotations were included. Upon reading the documentation of Dublin core there were classes and properties defined. how will i include these classes and properties in my ontology with the use of protege?

I think your problem is that you don't look inside the files. Dublin Core has many files. The one that you are referring to (elements) only contains annotations. You need to find the appropriate file. The DC terms contains some properties and classes. You need to read the documentation and then import the file with the modelling elements that you require.

Related

how to import data (instances) into an existing ontology in protoge

Can anyone tell me the steps that are required to populate an Ontology?
I have created a domain-specific Ontology (TBox = Terminological knowledge) which consists of defined classes and relations.
On the other hand, I have an IFC file (The Industry Foundation Classes) which has the instances.
I have converted the IFC file to IFC OWL and have understood that I need to map the classes into the newly created ontology.
However, I don't understand how I can get the instances of the associated classes and relations into my created ontology.
You have created two ontology files, one with the tbox and one with the abox. Usually, in this scenario the abox would use an owl:imports annotation to refer to the tbox, and would not, itself, need class declarations - it would use the IRIs for the classes already declared in the tbox. In protégé, creating an imports is straightforward.
A common issue is incorrect IRIs: if you've created your abox without initially importing the tbox, it's possible the classes you used do not match the tbox classes (e.g., the abox classes use the abox IRI as their base IRI instead of the tbox).

Creating knowledge graphs in Neo4j

1.Can Neo4j store RDF directly? we understand it can import RDF and export RDF but how is the data stored internally.
We also understand in Neo4j we can create property graphs and make it as a KG using APOC procedures and algorithms available,is that the case or are we missing anything?
2. We would like to understand, how an entity will be tagged against an ontology in Neo4j KG implementation.
You can import RDF data into Neo4j, however it will not be exactly in that format. Using Neosemantics, the triples will be converted into a property graph.
Neosematics can reconvert the property graph data back into triples should that be required.

default ontologies loaded into Graphdb

I am interested in finding out what are the ontologies preloaded into Graphdb by default. This will help me identify what ontologies (.ttl files) do I need to add along with my ontology as part of the package, especially in the situations when there is no Internet connection.
I know that some ontologies such as rdfs and owl are preloaded into GraphDb. but I could not find any list on preloaded ontologies.
Please keep in mind that OWL does not differentiate very clearly ontology from instance triples. Also GraphDB introduces another term "axiomatic triple" (i.e. statement that cannot be deleted with a normal user transaction) used to separate the ontology statements from the normal RDF.
There are 3 ways of loading ontologies as axiomatic triples in GraphDB:
Ruleset - will import all statements from the beginning of a PIE file as axiomatic statements. Check here for additional information.
Add imports initialisation parameter - this will safe a configuration predicate in the SYSTEM's repository See the configuration parameter
Add a special predicate in the beginning of an RDF file - the system transaction will add all following statements as ontology. Check here.
Another approach is to add every file in a different named graph. This will allow you to see which graphs are currently stored in the repository.

Difference between Direct Mapping and R2RML

I've tried to figure out what's differences between the two rdb2rdf mapping languages Direct Mapping and R2RML are.
I understand that booth languages generate RDF files that stand for a virtual RDF graph - which can be accessed via SPARQL.
So what's the point in having two W3C languages/standards doing the same!?
The two standards don't do the same.
Direct Mapping is a default, convention-based algorithm to convert relational data into RDF graphs. It defines how tables, primary keys, relationships, etc. are converted.
On the other hand R2RML is a language, with which you can create your own mappings, including Direct Mapping. As examples it gives you various ways to construct URLs, map tables to RDF classes or map custom SQL SELECT statements instead of tables.
R2RML defines a relaxed variant of the Direct Mapping intended as a default mapping for further customization.
So, R2RML actually includes a definition of Direct Mapping. Implementing tools can generate mappings from existing database, which can be further adjusted.
RDB to RDF mapping tools like D2RQ and SPIDER use a language to provide online mapping from a relational database to RDF, which means data are converted to RDF on the fly. Data can be converted directly without any user customization or users should specify the columns and the mapping predicates accordingly. The former is called directed mapping which is usually used for simple RDB databases, but for a relational database with complex structure, R2RML language is used for mapping.

How to add instances in ontology from CSV file

I tried to add instances in ontology using WebProtege. But the problem is that data is not assigned as data/object property instead it is in the 'type' the heading under the 'Description'. Is there any other quick way to add indvisuals from CSV file.
Steps:
Using Jena to read the ontology into Model X
Write small java code that will read each row of CSV file and convert it according the ontology vocabulary in the form of RDF statement.
RDF Statements can then be stored into the same Model X.
So at the end you will have both your ontology and data instances in the same model X. Then print your model X into some file with extension of saved file as "RDF/XML".
If using the Protégé Ontology editor environment you can use the plugin called "Cellfie" A Protégé Desktop plugin for mapping spreadsheets to OWL ontologies. The plugin is available in the menu item "Tools > Create axioms from Excel workbook..."

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