This is a parent page of the current use cases. The intention of describing these use cases is to identify the project scope and define the design requirements that will guide the system architecture and its implementation. All developers and users are invited to share their notes and thoughts.

Semantic

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1. A user to annotate resources using ontological terms through the semantic tagging plugin (Data from Leslie that has different spatial characteristics) 
2. Raw tags could be converted to standard tags (From SEAD or DataOne)
3. A user can create a new term in the semantic wiki and this term will pass through the semantic enrichment process (template based on SKOS)
4. standard names can be linked in a network (e.g. Temperature)

annotation and resource alignment 

Scenario:

•  A user added a new dataset to clowder.
• Data can be annotated using the Semantic Annotation Service (SAS), which proivdes spatial, temporal,  standard names, and encapsulated annotation, scientific provenance, and statistical features annotation of the data 
• A user can choose the Semantic Annotation Service (SAS) to annotate his data
• Then he uses a model and 

Applications

Main Success Scenario

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Linked Standard Names and knowledge integration

Scenario:

Applications:

Main Success Scenario:

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Knowledge discovery

Scenario:

Applications:

Main Success Scenario:

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1. How to create a semantically enabled models 
2. How to couple models and check and fix the semantics of their exchanged elements using Graph database. In this case, we need to avoid linear workflows
3. A model from CSDMS can find data in SEAD based on the semantic search (Leslie to provide data and the model). this case includes select, filter, and run. In this case the a raw data can be added to Medici II and tagged with semantic tags, then discovered from CSDMS. 

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