| Line 10 was replaced by line 10 |
| - * The goal is to "tag" (annotate) data and workflows (and their components) using ontology terms |
| + * The goal is to "tag" (annotate) data and workflows (and their components/actors) using ontology terms |
| Line 29 was replaced by line 29 |
| - *** ''Workflows and components'': A workflow, a workflow component, or some portion (parameters, ports, substructures of a port type, etc.). |
| + *** ''Workflows and components'': A workflow, a workflow actor, or some portion (parameters, ports, substructures of a port type, etc.). |
| Line 32 was replaced by line 32 |
| - *** Can be as simple as an LSID, e.g., that identifies an entire component or dataset |
| + *** Can be as simple as an LSID, e.g., that identifies an actor or dataset |
| Line 49 was replaced by line 49 |
| - *** Categorize workflows, components, datasets according to their position in the ontology concept hierarchy. |
| + *** Categorize workflows, actors, datasets according to their position in the ontology concept hierarchy. |
| Lines 51-52 were replaced by lines 51-52 |
| - *# Find "compatible" workflow components |
| - *** 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. |
| + *# Find "compatible" workflow actors |
| + *** Given a workflow 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 actor is returned. |
| Line 54 was replaced by line 54 |
| - *** Note that semantic compatbility does not imply structural compatibility (the i/o types may not match) |
| + *** Note that semantic compatibility does not imply structural compatibility (the i/o types may not match; see below) |
| Line 57 was replaced by line 57 |
| - *** Given a workflow of connected components, check that each connection (input/output) is semantically compatible. |
| + *** Given a workflow of connected actors, check that each connection (input/output) is semantically compatible. |
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| - *# Workflow-component structural integration |
| - *** 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 |
| + *# Workflow actor structural integration |
| + *** Given two actors that are semantically compatible, determine one or more transformations (either by inserting new actors or deriving transformation "code") to make them structurally compatible. |
| + **** In general, actor integration is a planning-style search problem (and still research) |
| + **** May be a place where SCIA can contribute, to derive the structural transformation code and help users refine mappings |
| Lines 65-67 were replaced by lines 65-68 |
| - *** Define a dataset of interest (as a query), find/combine datasets to populate result (classic data integration). |
| - **** Perhaps a place for SCIA to contribute? |
| - **** Still research |
| + *** Given two datasets, merge them (data fusion) into a single dataset based on their semantic annotations + metadata |
| + *** Define a dataset of interest (as a query---the classic approach---or as a target, annotated schema), then find/integrate datasets to populate result (classic data integration). |
| + **** Perhaps places for SCIA to contribute? |
| + **** In general, still research |
| Line 73 was replaced by line 74 |
| - *# Workflows and Workflow Components (or metadata, etc.) |
| + *# Workflows and Actors (or metadata, etc.) |
| Line 80 was replaced by lines 81-153 |
| - * ''Tools'' |
| + * ''Required Tools'' |
| + *# Ontology Editors/Browsers |
| + *** The KR group in SEEK |
| + *# Semantic Annotation Editors/Browsers |
| + *** For creating, editing, registering annotations |
| + *** KR and SMS group in SEEK |
| + *# Ontology-based query rewriting/answering |
| + *** Classification based on ontology (Jena, Racer, etc.) |
| + *** Efficiently using rewriting to find components |
| + *** Testing semantic compatibility |
| + *** Annotation propogation (research) |
| + *# Actor integration reasoning |
| + *** Structural transformation algorithms (SCIA? CLIO? Schema Mapping?) |
| + *** Search a la planners |
| + *# Data merging and integration reasoning |
| + *** Algorithms and rules for fusing together data |
| + *** Structural transformation algorithms (see above)) |
| + *** Basic conversions like count/area = density |
| + *# Explanation viewers/systems |
| + *** To explain why an answer was obtained |
| + *** Closely tied to ontology editors/browsers |
| + |
| + |
| + * ''"Smart" Actor Search in Kepler'' |
| + ** A very simple keyword-based search we (Chad and I) implemented within Kepler. |
| + *** Integrated with the actor 'quick search' frame |
| + *** Allows dynamic actor classification (for browsing) |
| + *** Allows runtime annotation and re-classification of actors |
| + *** Term expansion for individual concept queries |
| + ** Required a number of new features in Kepler: |
| + **# ID mechanism for actors |
| + **# Repositories: Fakes out component repository (as a ptolemy xml config file), annotation repository (xml file), ontology repository (simple is-a hierarchy, no rels) |
| + **# Provides a very naive, hand-coded, local ID service (like for LSIDs) |
| + |
| + |
| + |
| + __What's needed for KEPLER__ |
| + |
| + * Ontologies and Ontology Tools |
| + ** Need more example ontologies. |
| + ** There also aren't tools within Kepler for creating, browsing, or editing ontologies (coupling tools within Kepeler? import OWL files?, etc). |
| + |
| + * Annotations |
| + ** Need to formalize/finalize the annotation language |
| + ** Annotation interface for Kepler |
| + ** Also, may want: |
| + *** GUI design |
| + *** A uniform way to access/browse a component/dataset and its attributes, such as ports and their input/output types. |
| + *** Perhaps SCIA can help with specifying annotations? |
| + |
| + * Basic Kepler GUI Hooks |
| + ** Like for toolbar, menus, etc. |
| + ** Checking semantic compatibility (can steal unit resolver?). |
| + ** Explanation of results (like for searching, etc.) |
| + ** Joined development with Ptolemy group for customizable menus, etc. |
| + ** Use a personal ontology. Swap out default ontologies. |
| + |
| + * Algorithms |
| + ** Need to understand the integration/merging algorithms better (working on examples/test cases currently ...) |
| + ** Could today write the other types of search algorithms (compatible actors/datasets) |
| + |
| + * Repositories |
| + ** Basically none of the repositories exist (except perhaps for Data, not sure) |
| + ** I think the Kepler Obj. Manager can help with this, what we need from it is: |
| + *** Ability to register components, data sets, ontologies, and annotations with the obj. manager |
| + *** Ability to access all LSIDs of a certain type, e.g., components, data sets, ontologies, annotations |
| + *** Ability to retrieve the object for an LSID |
| + *** Some form of ''annotation indexing'' (this is similar to metadata indexing perhaps) |
| + **** A search can be executed directly against an in-memory annotation file (e.g., obtained dynamically from all registered objects) |
| + **** In contrast to asking the obj mngr for all lsids that are annotations, and for each retrieving the annotation file, etc. |
| + *** For efficiency, probably want multiple access paths via lsids, e.g., get all the workflow components and for each, retrieve it's annotation (if there are a lot more annotations than just for components); or build an annotation index based on these lsids, etc. |
| + **** The types of indexing needed should be driven by development/testing |
| + **** We may consider an obj. mngr. architecture that can easily support "extensible" indexing strategies (e.g., through listeners, etc.) |
| Removed line 82 |
| - *** Ontology Editors/Browsers |
| Removed line 84 |
| - *** Semantic Annotation Editor |
| Removed line 86 |
| - *** Ontology-based query rewriting/answering |
| Removed lines 89-144 |
| - * "Smart" Actor Search in Kepler |
| - |
| - A very simple keyword-based search implementation within Kepler. |
| - |
| - Fakes out: workflow component LSIDs, an actor repository (as a |
| - ptolemy xml config file), annotation repository (xml file), LSID |
| - service. |
| - |
| - The "ontology" is a simple hierarchy. No rels, etc. |
| - |
| - |
| - |
| - * What's Needed for KEPLER |
| - |
| - ** Ontologies |
| - |
| - There basically aren't any. |
| - |
| - There also aren't any tools. No tools within Kepler. |
| - |
| - |
| - ** Repositories ... |
| - |
| - The Obj. Mngr. can help! We don't have repositories for |
| - workflows/components, ontologies, annotations, or datasets in |
| - KEPLER. |
| - |
| - For annotations, need a searchable "index" of annotations and ids |
| - (for components, datasets, etc.), and a mechanism to "retrieve" |
| - those items. |
| - |
| - For performance, I wonder though if the "index" should be in |
| - memory. |
| - |
| - |
| - ** Semantic Annotation Editor |
| - |
| - This doesn't exist either ... lots of ways/approaches here. |
| - |
| - Need GUI design for this. |
| - |
| - Also, need a good way to access/browse a component/dataset and its |
| - attributes, such as is ports and their input/output types. |
| - |
| - Similar with datasets |
| - |
| - The challenges are making this tool easy to use, and accessible |
| - within Kepler. |
| - |
| - |
| - ** Basic Kepler Interfaces / GUI Design |
| - |
| - Like for searching, checking semantic compatibility (can steal |
| - unit resolver), explanation of semantics (like for searching, etc.) |
| - |
| - |
