Use natural language processing to guess a concept mapping
Use Case Number |
Init1hm3.pm27.1 |
---|---|
Brief Description |
It can be challenging to identify the correct semantic annotation of data elements in the metadata repository when the user performing the concept annotation is not intimately familiar with the ontology. Natural language processing could be used to digest a data element description and map it to a concept more correctly than a simple text search. |
Actor(s) for this particular use case |
Metadata Specialist |
Pre-condition |
A common data element is available for annotating. |
Post condition |
The common data element has been annotated with one or more semantic concepts. |
Steps to take |
|
Alternate Flow |
None. |
Priority |
High. |
Associated Links |
|
Fit criterion/Acceptance Criterion |
The NLP algorithm must be more accurate than simple text matching. |
Train a natural language processor using existing semantic annotations
Use Case Number |
Init1hm3.pm27.2 |
---|---|
Brief Description |
A large number of semantic annotations exist within information models in caBIG. These mappings of semantic concepts to data elements with textual descriptions could be used to train the natural language processor algorithm. |
Actor(s) for this particular use case |
Metadata Specialist |
Pre-condition |
The semantic annotations of all caBIG information models are available. |
Post condition |
A natural language processor algorithm is trained. |
Steps to take |
|
Alternate Flow |
None. |
Priority |
Low. |
Associated Links |
|
Fit criterion/Acceptance Criterion |
None. |