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Kepler Meeting SMS Notes

Difference between version 21 and version 20:

Line 45 was replaced by line 45
- __Architecture__
+ __Architecture Issues__
Removed lines 47-56
- * ''Repositories''
- *# Ontology(ies)
- *# Datasets (or metadata stating how to obtain the datasets)
- *# Workflows and Workflow Components (or metadata, etc.)
- *# Semantic Annotations
-
- ** "Smart discovery and integration" needs access to each of these components:
- *** To search for a workflow component, we would search through semantic annotations. When an annotation matches, obtain the corresponding component.
- *** To organize (for browsing) all actors according to their annotations. Might iterate over actors, or similarly, for datasets.
-
Line 60 was replaced by line 50
- *** Search based on concepts-as-keywords, providing "term expansion" capabilities
+ *** Search based on individual concepts (as a keyword), providing "term expansion" capabilities
Lines 62-64 were replaced by lines 52-54
- *** Given a workflow component (an actor), find actors that can be connected to it (either as input or output) based on semantic annotations. If the annotations are "compatible" according to the ontology(ies), the component is returned.
- *** Note that this could also result in "data binding," e.g., a dataset may be a "compatible" input.
- *** Also note that semantic compatbility does not imply structural compatibility (the i/o types may not match)
+ *** Given a workflow component (an actor), find components that can be connected to it (either as input or output) based on semantic annotations. If the annotations are "compatible" according to the ontology(ies), the component is returned.
+ *** Note that this could also result in "data binding" -- a dataset may be a "compatible" input.
+ *** Also semantic compatbility does not imply structural compatibility (the i/o types may not match)
Lines 67-68 were replaced by lines 57-58
- *** Given a workflow, check that each connection (input/output) is semantically compatible.
- *** As part of analysis, annotation propagation ...
+ *** Given a workflow of connected components, check that each connection (input/output) is semantically compatible.
+ *** Analysis may take advantage of annotation propagation (this is still research)
Lines 70-74 were replaced by lines 60-65
- *** Given two components that are semantically compatible, determine a structural transformation (either another component or a transformation step) to make them structurally compatible.
- *** May be a place where SCIA can contribute, to derive structural transformations.
- *# Dataset merging/integration
- *** Search for "similar" datasets (that could be potentially "merged" or integrated)
- *** Define a dataset of interest (via an ontology-style query), find/combine datasets as integrated "view".
+ *** Given two components that are semantically compatible, determine one or more transformations (either by inserting new components or deriving a transformation step) to make them structurally compatible.
+ *** Component integration is a search problem (and still researchy)
+ *** May be a place where SCIA can contribute, to derive the structural transformation code and help users refine mappings
+ *# Dataset merging and integration
+ *** Search for "similar" datasets based on semantic annotations of current dataset
+ *** Define a dataset of interest (as a query), find/combine datasets to populate result (classic data integration).
At line 75 added 12 lines.
+ **** Still research
+ **** Integration depends on the granularity/quality of the annotations, ontologies, etc.
+
+ * ''Repositories''
+ *# Ontology(ies)
+ *# Datasets (or metadata stating how to obtain the datasets)
+ *# Workflows and Workflow Components (or metadata, etc.)
+ *# Semantic Annotations
+
+ ** "Smart discovery and integration" needs access to these components:
+ *** To search for a workflow component, we would search through semantic annotations. When an annotation matches, obtain the corresponding component.
+ *** To organize (for browsing) all actors according to their annotations. Might iterate over actors, or similarly, for datasets.

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