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<h3>Understanding the Differences</h3>
<p>
-Linked Data modeling involves data going from one model to another. For example, modeling may involve converting a tabular representation of the data to a graph-based representation. Often extracts from relational databases are modeled and converted to Linked Data to more rapidly integrate datasets from different authorities or with other open source datasets. During the data modeling process, stakeholders are encouraged to describe how objects are related. The subject matter expert is recording how various objects are related, using standard vocabularies wherever possible. Best practices for using <a href="#VOCABULARIES">standard vocabularies<a/> are detailed later in this document. In Linked Data, the data schema is represented with the data itself. This mechanism of self-describing data contrasts with the relation approach which leverages external documents (e.g., data dictionaries) and diagrams (e.g., entity relationship diagrams, logical schemas).
+Linked Data modeling involves data going from one model to another. For example, modeling may involve converting a tabular representation of the data to a graph-based representation. Often extracts from relational databases are modeled and converted to Linked Data to more rapidly integrate datasets from different authorities or with other open source datasets. During the data modeling process, stakeholders are encouraged to describe how objects are related. The subject matter expert is recording how various objects are related, using standard vocabularies wherever possible. Best practices for using <a href="#VOCABULARIES">standard vocabularies<a/> are detailed later in this document. In Linked Data, the data schema is represented with the data itself. This mechanism of self-describing data contrasts with the relational approach where external documents (e.g., data dictionaries) and diagrams (e.g., entity relationship diagrams, logical schemas) describe the data.
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