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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
SW Today ,[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Differnent approaches in developing ontologies:  schema vs populated; community efforts vs reusing knowledge sources Types of Ontologies   (or things close to ontology)
Open Biomedical Ontologies Open Biomedical Ontologies, http://obo.sourceforge.net/
Example Life Science Ontologies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Manual Annotation   (Example PubMed abstract) Abstract Classification/Annotation
Semantic Annotation/Metadata Extraction + Enhancement [Hammond, Sheth, Kochut 2002]
Automatic Semantic Annotation © Semagix, Inc. Limited tagging (mostly syntactic) COMTEX Tagging Content ‘ Enhancement’ Rich Semantic  Metatagging Value-added Semagix Semantic Tagging ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Spatio-temporal-thematic semantics http://lsdis.cs.uga.edu/library/download/ACM-GIS_06_Perry.pdf
Scene Description Tree Retrieve Scene Description Track “ NSF Playoff” Node Enhanced  XML  Description MPEG-2/4/7 Enhanced  Digital Cable Video MPEG Encoder MPEG Decoder Node = AVO Object Voqutte/Taalee Semantic Engine ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Object Content Information (OCI) Metadata-rich Value-added Node Create Scene Description Tree  GREAT USER EXPERIENCE Embedding Metadata in  multimedia, a/v or sensor data  Channel sales through Video Server Vendors,  Video App Servers, and Broadcasters License metadata decoder and  semantic applications to  device makers “ NSF Playoff”
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.
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
WSDL-S  <?xml version=&quot;1.0&quot; encoding=&quot;UTF-8&quot;?> <definitions    ………………. xmlns:rosetta = &quot; http://lsdis.cs.uga.edu/projects/meteor-s/wsdl-s/pips.owl “   > <interface name = &quot;BatterySupplierInterface&quot;    description = &quot;Computer PowerSupply Battery Buy Quote Order Status &quot;  domain=&quot;naics:Computer and Electronic Product Manufacturing&quot; > <operation name = &quot;getQuote&quot;  pattern = &quot;mep:in-out&quot;    action  =  &quot; rosetta:#RequestQuote &quot;  > <input messageLabel = ”qRequest” element=&quot; rosetta :#QuoteRequest &quot; /> <output messageLabel = ”quote” elemen =&quot; rosetta :#QuoteConfirmation &quot; /> < pre condition  =  qRequested.Quantity  > 10000 &quot; /> </operation> </interface> </definitions>  Function from Rosetta Net Ontology Data from Rosetta Net Ontology Pre Condition on input data
Relationship Extraction  Disease or Syndrome causes affects causes complicates Fish Oils Raynaud’s Disease ??????? instance_of instance_of UMLS MeSH PubMed 9284  documents  4733   documents Biologically  active substance Lipid affects 5  documents
About the data used ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],T147—effect  T147—induce  T147—etiology  T147—cause  T147—effecting  T147—induced
Method – Parse Sentences in PubMed SS-Tagger (University of Tokyo) SS-Parser (University of Tokyo) (TOP (S (NP (NP (DT An) (JJ excessive) (ADJP (JJ endogenous) (CC or) (JJ exogenous) ) (NN stimulation) ) (PP (IN by) (NP (NN estrogen) ) ) ) (VP (VBZ induces) (NP (NP (JJ adenomatous) (NN hyperplasia) ) (PP (IN of) (NP (DT the) (NN endometrium) ) ) ) ) ) )
Method – Identify entities and Relationships in Parse Tree [Ramakrishnan, Kochut, Sheth 2006] Modifiers Modified entities Composite Entities
Limitations of Current N/W Design ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Limitations (Contd.) ,[object Object],[object Object],[object Object],[object Object],[object Object]
What Can Semantics Do For N/Ws ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Content Based Networking ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CISCO AON Diagram: CISCO AON (www.cisco.com) Think of modern router as a blade server.
Semantic Aware Networking Semantic Enabled Network Systems, NSF Proposal, Sheth, A., Ramaswamy, L.,  et. al.
Semantic Network Auditing Figure: Semantics-enabled Accountable Systems, LSDIS Lab, SAIC, Cisco
Medical Domain Example ,[object Object],[object Object]
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.
[object Object],[object Object],[object Object],[object Object],Profiles (Subscriptions) ,[object Object],[object Object],causes Disease Angiotension Receptor Blocker
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
Ontology Work at the Network Level ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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
Conclusions ,[object Object],[object Object],[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
For more information ,[object Object],[object Object]

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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
  • 2.
  • 3.
  • 4. Open Biomedical Ontologies Open Biomedical Ontologies, http://obo.sourceforge.net/
  • 5.
  • 6. Manual Annotation (Example PubMed abstract) Abstract Classification/Annotation
  • 7. Semantic Annotation/Metadata Extraction + Enhancement [Hammond, Sheth, Kochut 2002]
  • 8.
  • 10.
  • 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=&quot;1.0&quot; encoding=&quot;UTF-8&quot;?> <definitions ………………. xmlns:rosetta = &quot; http://lsdis.cs.uga.edu/projects/meteor-s/wsdl-s/pips.owl “ > <interface name = &quot;BatterySupplierInterface&quot; description = &quot;Computer PowerSupply Battery Buy Quote Order Status &quot; domain=&quot;naics:Computer and Electronic Product Manufacturing&quot; > <operation name = &quot;getQuote&quot; pattern = &quot;mep:in-out&quot; action = &quot; rosetta:#RequestQuote &quot; > <input messageLabel = ”qRequest” element=&quot; rosetta :#QuoteRequest &quot; /> <output messageLabel = ”quote” elemen =&quot; rosetta :#QuoteConfirmation &quot; /> < pre condition = qRequested.Quantity > 10000 &quot; /> </operation> </interface> </definitions> Function from Rosetta Net Ontology Data from Rosetta Net Ontology Pre Condition on input data
  • 14. Relationship Extraction Disease or Syndrome causes affects causes complicates Fish Oils Raynaud’s Disease ??????? instance_of instance_of UMLS MeSH PubMed 9284 documents 4733 documents Biologically active substance Lipid affects 5 documents
  • 15.
  • 16. Method – Parse Sentences in PubMed SS-Tagger (University of Tokyo) SS-Parser (University of Tokyo) (TOP (S (NP (NP (DT An) (JJ excessive) (ADJP (JJ endogenous) (CC or) (JJ exogenous) ) (NN stimulation) ) (PP (IN by) (NP (NN estrogen) ) ) ) (VP (VBZ induces) (NP (NP (JJ adenomatous) (NN hyperplasia) ) (PP (IN of) (NP (DT the) (NN endometrium) ) ) ) ) ) )
  • 17. Method – Identify entities and Relationships in Parse Tree [Ramakrishnan, Kochut, Sheth 2006] Modifiers Modified entities Composite Entities
  • 18.
  • 19.
  • 20.
  • 21.
  • 22. CISCO AON Diagram: CISCO AON (www.cisco.com) Think of modern router as a blade server.
  • 23. Semantic Aware Networking Semantic Enabled Network Systems, NSF Proposal, Sheth, A., Ramaswamy, L., et. al.
  • 24. Semantic Network Auditing Figure: Semantics-enabled Accountable Systems, LSDIS Lab, SAIC, Cisco
  • 25.
  • 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.
  • 27.
  • 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
  • 29.
  • 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
  • 31.
  • 32.
  • 33.

Notas del editor

  1. 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