Amit Sheth, "Driving Deep Semantics in Middleware and Networks: What, why and how?," Keynote talk at Semantic Sensor Networks Workshop at the 5th International Semantic Web Conference (ISWC-2006), November 6, 2006, Athens, Georgia, USA.
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Driving Deep Semantics in Middleware and Networks: What, why and how?
1. Driving Deep Semantics in Middleware and Networks: What, why and how? Amit Sheth Keynote @ Semantic Sensor Networks Workshop @ ISWC2006 November 06, 2006, Athens GA Thanks: Doug Brewer, Lakshmish Ramaswamy
11. Metadata for Automatic Content Enrichment Interactive Television This segment has embedded or referenced metadata that is used by personalization application to show only the stocks that user is interested in. This screen is customizable with interactivity feature using metadata such as whether there is a new Conference Call video on CSCO. Part of the screen can be automatically customized to show conference call specific information– including transcript, participation, etc. all of which are relevant metadata Conference Call itself can have embedded metadata to support personalization and interactivity.
12. WSDL-S Metamodel Action Attribute for Functional Annotation Pre and Post Conditions Pre and Post Conditions Can use XML, OWL or UML types Extension Adaptation schemaMapping
13. WSDL-S <?xml version="1.0" encoding="UTF-8"?> <definitions ………………. xmlns:rosetta = " http://lsdis.cs.uga.edu/projects/meteor-s/wsdl-s/pips.owl “ > <interface name = "BatterySupplierInterface" description = "Computer PowerSupply Battery Buy Quote Order Status " domain="naics:Computer and Electronic Product Manufacturing" > <operation name = "getQuote" pattern = "mep:in-out" action = " rosetta:#RequestQuote " > <input messageLabel = ”qRequest” element=" rosetta :#QuoteRequest " /> <output messageLabel = ”quote” elemen =" rosetta :#QuoteConfirmation " /> < pre condition = qRequested.Quantity > 10000 " /> </operation> </interface> </definitions> Function from Rosetta Net Ontology Data from Rosetta Net Ontology Pre Condition on input data
26. Data Sources Elsevier iConsult Health Information through SOAP Web Services PubMed 300 Documents Published Online each day NCBI Genome, Protein DBs Updated Daily with new Sequences Heterogenous Datasources need for integration and getting the right information to those who need it.
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28. Extracting the Relationship Diabetes mellitus adversely affects the outcomes in patients with myocardial infarction (MI), due in part to the exacerbation of left ventricular (LV) remodeling. Although angiotensin II type 1 receptor blocker (ARB) has been demonstrated to be effective in the treatment of heart failure, information about the potential benefits of ARB on advanced LV failure associated with diabetes is lacking. To induce diabetes, male mice were injected intraperitoneally with streptozotocin (200 mg/kg). At 2 weeks, anterior MI was created by ligating the left coronary artery. These animals received treatment with olmesartan (0.1 mg/kg/day; n = 50) or vehicle (n = 51) for 4 weeks. Diabetes worsened the survival and exaggerated echocardiographic LV dilatation and dysfunction in MI. Treatment of diabetic MI mice with olmesartan significantly improved the survival rate (42% versus 27%, P < 0.05) without affecting blood glucose, arterial blood pressure, or infarct size. It also attenuated LV dysfunction in diabetic MI. Likewise, olmesartan attenuated myocyte hypertrophy, interstitial fibrosis, and the number of apoptotic cells in the noninfarcted LV from diabetic MI. Post-MI LV remodeling and failure in diabetes were ameliorated by ARB, providing further evidence that angiotensin II plays a pivotal role in the exacerbated heart failure after diabetic MI. Angiotensin II type 1 receptor blocker attenuates exacerbated left ventricular remodeling and failure in diabetes-associated myocardial infarction., Matsusaka H, et. al. ARB causes heart failure
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30. Ontology Network Ontology: A Framework for Schema-Driven Relationship Discovery from Unstructured Text, Ramakrishnan, et. al., ISWC 2006, LNCS 4273, pp. 583-596 causes produces ARB causes heart failure PubMed NCBI Elsevier
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Editor's Notes
CENTRAL ROLE OF ONTOLOGIES Ontology represents agreement, represents common terminology/nomenclature Ontology is populated with extensive domain knowledge or known facts/assertions Key enabler of semantic metadata extraction from all forms of content: unstructured text (and 150 file formats) semi-structured (HTML, XML) and structured data Ontology is in turn the center price that enables resolution of semantic heterogeneity semantic integration semantically correlating/associating objects and documents Large number of ontologies have been developed and many are in use