Structured Dynamics' Semantic Technologies Product Stack
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Structured Dynamics provides 'ontology-driven applications'. Our product stack is geared to enable the semantic enterprise. The products are premised on preserving and leveraging existing information assets in an incremental, low-risk way. SD's products span from converters to authoring environments to Web services middleware and to eventual ontologies and user interfaces and applications.
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Structured Dynamics' Semantic Technologies Product Stack
- 1. May (updated) 2010 Product Stack
- 5. Layers and Current Products
- 7. Fit of Current Products within Layers
- 18. scones
- 21. Creating New Entity Dictionaries
- 23. irON – i nstance r ecord and O bject N otation
- 27. structWSF
- 29. RDF and Data Federation Model
- 31. A Collaborative, Distributed Network
- 32. Flexible User Access Permissions
- 34. Ontologies Layer
- 37. Migrating Structure to the Ontology Layer
- 38. Ontologies Layer
- 39. irON
- 42. Notable Ontologies and Vocabularies
- 43. Management Layer
- 47. conStruct SCS
- 50. Re-cap
Editor's Notes
- At present, though constantly increasing, Zitgist's existing conversion services recognizes nearly 100 various formats GRDDL (Gleaning Resource Descriptions from Dialects of Languages) is a W3C markup format for getting RDF data out of XML and XHTML documents using explicitly associated transformation algorithms, typically represented in XSLT GRDDL accomodates a wide variety of dialects (see one listing) and can be combined with arbitrary transformation mechanisms (though currently mostly based on XSLTs).
- At present, though constantly increasing, Zitgist's existing conversion services recognizes nearly 100 various formats GRDDL (Gleaning Resource Descriptions from Dialects of Languages) is a W3C markup format for getting RDF data out of XML and XHTML documents using explicitly associated transformation algorithms, typically represented in XSLT GRDDL accomodates a wide variety of dialects (see one listing) and can be combined with arbitrary transformation mechanisms (though currently mostly based on XSLTs).
- More here also, use the candidate properties content to get the extract to the SC context (??? more about the “aboutness”) contextual UMBEL metadata on the fly