Semantic Web: intro & overview             A conversation with students – Feb 21, 2012               Amit Sheth        htt...
What are two of the mostimportant software success     stories of 2012?
Apple’s Siri      IBM’s WatsonWhat are common technologies?
Just stepping back a bit
Semantic technologies in the mainstream• Microsoft purchased Powerset in 2008• Apple purchased Siri [Apr 2010]   – “Once A...
• RDFa adoption ….Search engines (esp Bing)  are about to introduce domain models and  (all) use of background knowledge/s...
A bit of history• Semantics with metadata and ontologies for heterogeneous  documents and multiple repositories of data in...
Different foci• TBL – focus on data: Data Web (“In a way, the Semantic  Web is a bit like having all the databases out the...
1     2     3     ofSemantic Web
1• Ontology: Agreement with a common  vocabulary/nomenclature, conceptual models  and domain Knowledge• Schema + Knowledge...
2• Semantic Annotation (Metadata Extraction):  Associating meaning with data, or labeling  data so it is more meaningful t...
From Syntax to Semantics   Deep semanticsShallow semantics                    Changing Focus on Interoperability in Inform...
3• Reasoning/Computation: semantics enabled  search, integration, answering complex  queries, connections and analyses (pa...
Semantic Web Stack• Web of Linked Data• Introduced by Berners Lee  et. al as next step for  Web of Documents• Allow “machi...
Characteristics of Semantic Web   Self                      Easy to   Describing                Understand     The Semanti...
Resource Description Framework                                                                Location    Company         ...
RDF: Triple Structure, IRI, Namespace                           Headquarters located in      Armonk, New York,          IB...
RDF Representation• Two types of property values in a triple   o Web resource            Headquarters located in          ...
RDF Schema                 Headquarters located in   Armonk, New     IBM                                           York, U...
RDF Schema • Propertydomain(rdfs:domain) and range(rdfs:range)     Domain           Headquarters located in      Range    ...
Ontology: A Working Definition• Ontologies are shared conceptualizations of a  domain represented in a formal language*• O...
Expressiveness Range:                                    Knowledge Representation                                  and Ont...
OWL2 Web Ontology Language• A language for modeling ontologies [OWL]• OWL2 is declarative• An OWL2 ontology (schema) consi...
OWL2 Constructs• Class Disjointness: Instance of class A cannot be  instance of class B• Complex Classes: Combining multip...
OWL2 Constructs• Property restrictions: defined over property• Existential Quantification:  o Parent =ObjectSomeValuesFrom...
SPARQL: Querying Semantic Web Data• A SPARQL query pattern composed of triples• Triples correspond to RDF triple structure...
SPARQL: Query Patterns• An example query patternPREFIX ex:<http://www.eecs600.case.edu/>SELECT?company ?location WHERE{?co...
SPARQL: Query Forms• SELECT: Returns the values bound to the variables• CONSTRUCT: Returns an RDF graph• DESCRIBE: Returns...
a little bit about ontologies
Many Ontologies Available Today                                   Open Biomedical Ontologieshttp://bioportal.bioontology.o...
From simple ontologies
Drug Ontology Hierarchy                                    (showing is-a relationships)                                   ...
to complex ontologies
N-Glycosylation metabolic        pathway                                                      GNT-I                       ...
A little bit about semanticmetadata extractions and         annotations
Extractionfor Metadata Creation                                       Nexis           Digital Videos                      ...
Automatic Semantic Metadata  Extraction/Annotation
Semantics & Semantic Web     in 1999-2002
Sample applications• Early Semantic Search, use baby steps of  today’s engines• Enterprise applications – healthcare & lif...
Taalee Semantic/Faceted Search & Browsing(1999-2001)    BLENDED BROWSING & QUERYING INTERFACE                             ...
Semantic Search/Browsing/Directory (2001-….)                                        Links to news on companies that       ...
Semantic Search/Browsing/Directory (2001-….)                  System recognizes ENTITY & CATEGORY                         ...
Semantic Search/Browsing/Directory (2001-….)                                    Users can explore                         ...
Equity Research Dashboard with                Blended Semantic Querying and Browsing Automatic  3rd party                 ...
Extracting Semantic Metadata from Semistructured and Structured Sources (1999 – 2002)Semagix Freedom for buildingontology-...
Ontology Creation and Maintenance Steps  1. Ontology Model Creation (Description)              2. Knowledge Agent Creation...
Semantic Associations - Connecting the Dots                                                                               ...
Global Investment Bank                                    Law                        Public     World Wide     BLOGS,     ...
Fast forward to 2005-2006
Semantic Web+Clinical Practice Informatics =Active Semantic Electronic Medical Record (ASEMR)  Operationally deployed in J...
ASEMR: SW application in useIn daily use at Athens Heart Center  – 28 person staff     • Interventional Cardiologists     ...
Information Overload in Clinical                Practice• New drugs added to market  – Adds interactions with current drug...
Active Semantic Document (ASD)A document (typically in XML) with the following features:• Semantic annotations   – Linking...
Active Semantic Patient Record• An application of ASD• Three Ontologies  – Practice     Information about practice such as...
Active Semantic Electronic Medical Record AppIn Use Today at Athens Heart Center For Clinical Decision Support since Janua...
Demo of ASEMR and other      applications       http://knoesis.org/showcasehttp://archive.knoesis.org/library/demos/
Benefits of ASEMR• Error prevention (drug interactions, allergy)  – Patient care  – insurance• Decision Support (formulary...
Using large data sets for StructuredData on the web:Linked Open Data – samples from2005 to 2010
Linked Open Data  Publish Open Data Sets in RDF  By 2010, 203 data data sets  25 billion TriplesImage: http://richard.cyga...
You publish the raw data…                 Semantic Web Adoption and Application
… and others can use it             Semantic Web Adoption and Application
Using the LOD to build Web site: BBC                   Semantic Web Adoption and Application
Using the LOD to build Web site:             BBC                     Semantic Web Adoption and Application
GoodRelations Ontology - RDFa                   Semantic Web Adoption and Application
GoodRelations Ontology - RDFa                   Semantic Web Adoption and Application
GoodRelations Ontology - RDFa                   Semantic Web Adoption and Application
Fast forward to 2010-2011
Schema.orgShared       Amazing things can happenVocabulary                  Will give some on-line examples
Twitris: Semantic Social Web Mash-up                  Select date                                    Select topic   N-gram...
Web (and associated for Human Experience is                                Computing                                      ...
2D-3D & Immersive                          Visualization, Human                                  Impacting                ...
Semantics as core enabler,  enhancer @ Kno.e.sis
Take Home Message (Cont.)Semantics play a key role in refering"meaning" behind the data. Requiresprogress from keywords ->...
Take Home Message (Cont.)Wide variety of semantic models andKBs(vocabularies, social dictionaries, community created semi-...
Interested in more?Kno.e.sis Wiki for the following and more:•   Computing for Human Experience•   Continuous Semantics to...
Future: Computing for Human Experience                         http://knoesis.org       Kno.e.sis – Ohio Center of Excelle...
Upcoming SlideShare
Loading in...5
×

Semantic Web: introduction & overview

10,685

Published on

A lecture/conversation focusing on the first 12 years of Semantic Web - delivered on February 21, 2012.

See http://j.mp/SWIntro for more details. More detailed course material is at http://knoesis.org/courses/web3/

Published in: Education
2 Comments
19 Likes
Statistics
Notes
  • Suddenly Semantic Search is hot. While some well-known companies are incorporating semantics in their search now, semantic search (and semantic browsing, advertisement/targeting, etc) is not new (at conceptual, research or commercial levels). Here are just some links [apologies for self-citations as they are available to me- may want to search to find other efforts]:

    A 2000 talk on commercial semantic search, browsing, etc: http://www.slideshare.net/apsheth/semantic-web-info-brokering-opportunities-commercialization-and-challenges

    A 2000 interview on Semantic Search: http://knoesis.org/amit/Taalee-Seamtic-Search-Engine-Interview.pdf

    A 2000/2001 patent (System and method for creating a semantic web and its applications in browsing, searching, profiling, personalization and advertising) : http://www.google.com/patents/US6311194

    A 2002 paper: http://knoesis.org/library/resource.php?id=810

    A 2003 keynote : 'Semantic Web in Action: Ontology-driven information search, integration and analysis' :
    http://www.slideshare.net/apsheth/semantic-web-in-action-ontologydriven-information-search-integration-and-analysis

    A 2005 'exchange' on thoughts on one way of adding semantics to search by a Google director and my response (and this is broadly how GKG is exploited now, incorporating entities /things, relationships):
    http://amitsheth.blogspot.com/2007/05/semantic-web-different-perspective-on.html
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • This slide deck was used for a short course taught in early 2012 on-line for international students at universities in India. More recently, We have a low cost book that carries this subject matter further: 'Semantics Empowered Web 3.0: Managing Enterprise, Social, Sensor, and Cloud-based Data and Services for Advanced Applications' http://www.amazon.com/Semantics-Empowered-Web-3-0-Applications/dp/1608457168/ Furthermore, all materials (Slides, Video, assignments) used in the class that uses this book is available free: http://knoesis.org/courses/web3. For instructors wishing to teach this course, contact me at amit@knoesis.org for assistance.
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
No Downloads
Views
Total Views
10,685
On Slideshare
0
From Embeds
0
Number of Embeds
6
Actions
Shares
0
Downloads
316
Comments
2
Likes
19
Embeds 0
No embeds

No notes for slide
  • RDF: Triple structure
  • Review types of heterogeneity. Why we need to reconcile data heterogeneityUniform Resource Locator: A network location and used as an identifier for resources on the Web. URL is a specific type of URI. URI can be used to refer to anythingIRI: In addition to ASCII character set, contains Universal Character Set (from RFC 3987)
  • RDF uses XML Schema datatypes
  • Allows creation of an abstract representation of domain
  • Allows creation of an abstract representation of domain
  • Review types of heterogeneity. Why we need to reconcile data heterogeneity
  • Review types of heterogeneity. Why we need to reconcile data heterogeneity
  • Review types of heterogeneity. Why we need to reconcile data heterogeneity
  • Taalee (subsequently Voquette and Semagix) was founded in 1999 as an Audio/Video Web Search Company (focus on A/V mainly for scalability and market focus reasons, servicename: MediaAnywhere). Domain models/ontologies were created in major areas (many more than what you can find on Bing in 2011) and automatically populated to build knowledge bases (populated ontologies or WorldModel) from a variety of structured and semistructured sources, and periodically kept up to date. This was than used for semantic annotation/metadata extraction to drive semantic search, browsing, etc applications over data crawled from Web sites.
  • The important thing is that the system knew that Robert Duval is a movie actor, is a different person that David Duval who is a golfer and a sportsperson, and had understanding of a variety of relationships Robert Duval participates in – such as
  • Obtained from Ivan’s slide
  • Obtained from Ivan’s slide
  • Obtained from Ivan’s slide
  • Obtained from Ivan’s slide
  • Obtained from Ivan’s slide
  • Let me give a technological introduction to what our center is about: we all face a fire hose of data-- Pubmed adds 2000 to 4000 citations per day, it is usual to add about 5 gig from a single run of a scientific experiment -- and just imagine how much data created by all the cameras and 40 billion mobile sensors in the world! But even with all the search and browsing tools we have, we face huge information glut. How do we make sense from the data? Just as humans apply their knowledge and experience to understand what they see– we apply domain model or knowledge to attach meaningful labels to these data. Then we can apply computational techniques to visualize, provide situational awareness, discovery nuggets of knowledge of information and insight. For example, from all that biomedical data, what a scientist may be looking for is– how can we treat Migraine? What has Magnesium to do with Migraine? Why does Magnesium deficiency cause Migraine? What is the process by which Magnesium affects Migraine?
  • Kno.e.sis has 15 faculty in Computer Science, life sciences and health care, cognitive science and business. It has about 50 PhD students and post docs– about 2/3 of these in Computer Science. Its faculty members have 40 labs, and occupies a majority of 50K sqft Joshi Research Center. Its students are highly successful– eg tenure track faculty @ Case Western Reserve Univ or Researcher at IBM Almaden. It has received recent funding from funding from Microsoft Research. IBM Research, HP Labs, Google, and small companies (Janya, EZdi,…) and collaborates with many more (Yahoo! Labs, NLM, …).
  • Transcript of "Semantic Web: introduction & overview"

    1. 1. Semantic Web: intro & overview A conversation with students – Feb 21, 2012 Amit Sheth http://knoesis.org/amitKno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing Wright State University, Dayton, OH, USA 1
    2. 2. What are two of the mostimportant software success stories of 2012?
    3. 3. Apple’s Siri IBM’s WatsonWhat are common technologies?
    4. 4. Just stepping back a bit
    5. 5. Semantic technologies in the mainstream• Microsoft purchased Powerset in 2008• Apple purchased Siri [Apr 2010] – “Once Again The Back Story Is About Semantic Web”• Google buys Metaweb [June 2010]...” Google Snaps Up Metaweb in Semantic Web Play” – Now see: “Google Knowledge Graph Could Change Search Forever”• FacebookOpenGraph, Twitter annotation …”another example of semantic web going mainstream” “Google, Twitter and Facebook build the semantic web” 5
    6. 6. • RDFa adoption ….Search engines (esp Bing) are about to introduce domain models and (all) use of background knowledge/structured databases with large entity bases• Bing, Yahoo! and Google announced schema.org
    7. 7. A bit of history• Semantics with metadata and ontologies for heterogeneous documents and multiple repositories of data including the Web was discussed in 1990s (semantic information brokering, faceted search, InfoHarness, SIMS, Ariadne, OBSERVER, SHOE, MREF, InfoQuilt, …). Also DAML and OIL.• Tim Berners-Lee used “Semantic Web” in his 1999 book• I had founded a company Taalee in 1999, gave a keynote on Semantic Web & commercialization in 2000 and filed for a patent in 2000 (awarded 2001).• Well known TBL, Hendler, Lassila paper in Scientific American took AI-ish approach (agents,…) to Semantic Web• First 5 years saw too much of AI/DL, but more practical/applied work has dominated recently
    8. 8. Different foci• TBL – focus on data: Data Web (“In a way, the Semantic Web is a bit like having all the databases out there as one big database.”)• Others focus on reasoning and intelligent processing
    9. 9. 1 2 3 ofSemantic Web
    10. 10. 1• Ontology: Agreement with a common vocabulary/nomenclature, conceptual models and domain Knowledge• Schema + Knowledge base• Agreement is what enables interoperability• Formal description - Machine processability is what leads to automation
    11. 11. 2• Semantic Annotation (Metadata Extraction): Associating meaning with data, or labeling data so it is more meaningful to the system and people.• Can be manual, semi-automatic (automatic with human verification), automatic.
    12. 12. From Syntax to Semantics Deep semanticsShallow semantics Changing Focus on Interoperability in Information Systems: From System, Syntax, Structure to Semantics
    13. 13. 3• Reasoning/Computation: semantics enabled search, integration, answering complex queries, connections and analyses (paths, sub graphs), pattern finding, mining, hypothesis validation, discovery, visualization
    14. 14. Semantic Web Stack• Web of Linked Data• Introduced by Berners Lee et. al as next step for Web of Documents• Allow “machine understanding” of data,• Create “common” models of domains using formal language - ontologies Semantic Web Layer Cake Layer cake image source: http://www.w3.org; see W3C SW publications
    15. 15. Characteristics of Semantic Web Self Easy to Describing Understand The Semantic Web:Machine &Issued by XML, RDF & Ontologya Trusted HumanAuthority Readable Can be Convertible Secured Adapted from William Ruh (CISCO) 15
    16. 16. Resource Description Framework Location Company Armonk, New York, United States IBM Zurich, Switzerland• Resource Description Framework – Recommended by W3C for metadata modeling [RDF]• A standard common modeling framework – usable by humans and machine understandable RDF/OWL slides From: Semantic Web in Health Informatics (thanks: Satya)
    17. 17. RDF: Triple Structure, IRI, Namespace Headquarters located in Armonk, New York, IBM United States• RDF Triple o Subject: The resource that the triple is about o Predicate: The property of the subject that is described by the triple o Object:The value of the property• Web Addressable Resource:Uniform Resource Locator (URL), Uniform Resource Identifier(URI), Internationalized Resource Identifier (IRI)• Qualified Namespace:http://www.w3.org/2001/XMLSchema# asxsd: o xsd: string instead of http://www.w3.org/2001/XMLSchema#string
    18. 18. RDF Representation• Two types of property values in a triple o Web resource Headquarters located in IBM Armonk, New York, o Typed literal United States Has total employees IBM “430,000” ^^xsd:integer • The graph model of RDF:node-arc-node is the primary representation model • Secondary notations: Triple notation o companyExample:IBM companyExample:has-Total- Employee “430,000”^^xsd:integer .
    19. 19. RDF Schema Headquarters located in Armonk, New IBM York, United States Headquarters located in Redwood Oracle Shores, California, United States Headquarters located in Company Geographical Location• RDF Schema: Vocabulary for describing groups of resources [RDFS]
    20. 20. RDF Schema • Propertydomain(rdfs:domain) and range(rdfs:range) Domain Headquarters located in Range Company Geographical Location • Class Hierarchy/Taxonomy:rdfs:subClassOf SubClass rdfs:subClassOf (Parent) ClassComputer Technology CompanyCompanyBanking CompanyInsurance Company
    21. 21. Ontology: A Working Definition• Ontologies are shared conceptualizations of a domain represented in a formal language*• Ontologies: o Common representation model - facilitate interoperability, integration across different projects, and enforce consistent use of terminology o Closely reflect domain-specific details (domain semantics) essential to answer end user o Support reasoning to discover implicit knowledge* Paraphrased from Gruber, 1993
    22. 22. Expressiveness Range: Knowledge Representation and Ontologies KEGG TAMBIS BioPAX Thesauri “narrower Disjointness, term” Formal Frames Inverse, relation is-a (properties) part of…Catalog/ID DB Schema UMLS RDF RDFS DAML CYC Wordnet OO OWL IEEE SUO Informal Formal Value General Terms/ is-a instance Restriction Logical glossary constraints GO SWETO GlycO EcoCycSimple Pharma ExpressiveTaxonomies Ontologies Ontology Dimensions After McGuinness and Finin
    23. 23. OWL2 Web Ontology Language• A language for modeling ontologies [OWL]• OWL2 is declarative• An OWL2 ontology (schema) consists of: o Entities:Company, Person o Axioms:Company employs Person o Expressions:A Person Employed by a Company = CompanyEmployee• Reasoning: Draw a conclusion given certain constraints are satisfied o RDF(S) Entailment o OWL2 Entailment
    24. 24. OWL2 Constructs• Class Disjointness: Instance of class A cannot be instance of class B• Complex Classes: Combining multiple classes with set theory operators: o Union:Parent =ObjectUnionOf(:Mother :Father) o Logical negation:UnemployedPerson = ObjectIntersectionOf(:EmployedPerson) o Intersection:Mother =ObjectIntersectionOf(:Parent :Woman)
    25. 25. OWL2 Constructs• Property restrictions: defined over property• Existential Quantification: o Parent =ObjectSomeValuesFrom(:hasChild :Person) o To capture incomplete knowledge• Universal Quantification: o US President = objectAllValuesFrom(:hasBirthPlace United States)• Cardinality Restriction
    26. 26. SPARQL: Querying Semantic Web Data• A SPARQL query pattern composed of triples• Triples correspond to RDF triple structure, but have variable at: o Subject: ?companyex:hasHeadquaterLocationex:NewYork. o Predicate: ex:IBM?whatislocatedinex:NewYork. o Object: ex:IBMex:hasHeadquaterLocation?location.• Result of SPARQL query is list of values – valuescan replace variable in query pattern
    27. 27. SPARQL: Query Patterns• An example query patternPREFIX ex:<http://www.eecs600.case.edu/>SELECT?company ?location WHERE{?company ex:hasHeadquaterLocation?location.}• Query Result company location Multiple Matches IBM NewYork Oracle RedwoodCity MicorosoftCorporation Bellevue
    28. 28. SPARQL: Query Forms• SELECT: Returns the values bound to the variables• CONSTRUCT: Returns an RDF graph• DESCRIBE: Returns a description (RDF graph) of a resource (e.g. IBM) o The contents of RDF graph is determined by SPARQL query processor• ASK: Returns a Boolean o True o False
    29. 29. a little bit about ontologies
    30. 30. Many Ontologies Available Today Open Biomedical Ontologieshttp://bioportal.bioontology.org/ , http://obo.sourceforge.net/
    31. 31. From simple ontologies
    32. 32. Drug Ontology Hierarchy (showing is-a relationships) formulary_ non_drug_ interaction_ property formulary reactant property indication indication_ property owl:thingmonograph property _ix_class prescription interaction_ _drug_ with_non_ brandname_ prescription brand_name drug_reactantprescription individual _drug interaction _drug_ property brandname_ brandname_ composite prescription interaction_ undeclared _drug_ with_mono interaction_ generic graph_ix_cl with_prescri cpnum_ generic_ ass ption_drug group composite generic_ individual
    33. 33. to complex ontologies
    34. 34. N-Glycosylation metabolic pathway GNT-I attaches GlcNAc at position 2N-glycan_beta_GlcNAc_9 N-acetyl-glucosaminyl_transferase_V N-glycan_alpha_man_4 GNT-V attaches GlcNAc at position 6 UDP-N-acetyl-D-glucosamine + alpha-D-Mannosyl-1,3-(R1)-beta-D-mannosyl-R2 <=> UDP + N-Acetyl-$beta-D-glucosaminyl-1,2-alpha-D-mannosyl-1,3-(R1)-beta-D-mannosyl-$R2 UDP-N-acetyl-D-glucosamine + G00020 <=> UDP + G00021
    35. 35. A little bit about semanticmetadata extractions and annotations
    36. 36. Extractionfor Metadata Creation Nexis Digital Videos UPI AP ... ... Feeds/ Data Stores Documents WWW, Enterprise Digital Maps Repositories ... Digital Images Digital Audios Create/extract as much (semantics) metadata automatically as possible;Use ontlogies to improve and enhance EXTRACTORS extraction METADATA
    37. 37. Automatic Semantic Metadata Extraction/Annotation
    38. 38. Semantics & Semantic Web in 1999-2002
    39. 39. Sample applications• Early Semantic Search, use baby steps of today’s engines• Enterprise applications – healthcare & life sciences, financial, security• Driving the innovation with new types of data: sensor (Semantic Sensor Web), social (Semantic Social Web), semantic IoT/WoT
    40. 40. Taalee Semantic/Faceted Search & Browsing(1999-2001) BLENDED BROWSING & QUERYING INTERFACE Targeted e-shopping/e-commerce ATTRIBUTE & KEYWORD QUERYING assets accessSEMANTIC BROWSING uniform view of worldwide distributed assets of similar type
    41. 41. Semantic Search/Browsing/Directory (2001-….) Links to news on companies that compete against Commerce One Crucial news on Commerce One’s competitors (Ariba) can Links to news on companieseasily and be accessed Commerce One competes against automatically (To view news on Ariba, click on the link Search for company for Ariba) ‘Commerce One’
    42. 42. Semantic Search/Browsing/Directory (2001-….) System recognizes ENTITY & CATEGORY Relevant portion of the Directory is automatically presented.
    43. 43. Semantic Search/Browsing/Directory (2001-….) Users can explore Semantically related Information.
    44. 44. Equity Research Dashboard with Blended Semantic Querying and Browsing Automatic 3rd party Focused content relevantintegration content organized by topic (semantic categorization) Related relevant content not explicitly asked for (semantic associations) Automatic Content Aggregation from multiple Competitive content providers research and feeds inferredautomatically
    45. 45. Extracting Semantic Metadata from Semistructured and Structured Sources (1999 – 2002)Semagix Freedom for buildingontology-driven information system Managing Semantic Content on the Web
    46. 46. Ontology Creation and Maintenance Steps 1. Ontology Model Creation (Description) 2. Knowledge Agent Creation Ontology Semantic Query Server 4. Querying the Ontology 3. Automatic aggregation of Knowledge © Semagix, Inc.
    47. 47. Semantic Associations - Connecting the Dots Ahmed Yaseer: • Appears on Watchlist ‘FBI’ Watch list Organization • Works for Company ‘WorldCom’ Hamas FBI Watchlist • Member of a banned member of organization organization’ appears on Watchlist Ahmed Yaseer works for Company WorldCom Company 2004 SEMAGIX 47
    48. 48. Global Investment Bank Law Public World Wide BLOGS, Watch Lists Enforcement Regulators Records Web content RSS Semi-structured Government Data Un-structure text, Semi-structured DataEstablishingNew Account User will be able to navigate the ontology using a number of different interfaces Scores the entity based on the content and entity relationships Fraud Prevention application used in financial services – Related KYC application is deployed at Majority of Global Banks
    49. 49. Fast forward to 2005-2006
    50. 50. Semantic Web+Clinical Practice Informatics =Active Semantic Electronic Medical Record (ASEMR) Operationally deployed in January 2006, in use (as of 2012)
    51. 51. ASEMR: SW application in useIn daily use at Athens Heart Center – 28 person staff • Interventional Cardiologists • Electrophysiology Cardiologists – Deployed since January 2006 – 40-60 patients seen daily – 3000+ active patients – Serves a population of 250,000 people
    52. 52. Information Overload in Clinical Practice• New drugs added to market – Adds interactions with current drugs – Changes possible procedures to treat an illness• Insurance Coverages Change – Insurance may pay for drug X but not drug Y even though drug X and Y are equivalent – Patient may need a certain diagnosis before some expensive test are run• Physicians need a system to keep track of ever changing landscape
    53. 53. Active Semantic Document (ASD)A document (typically in XML) with the following features:• Semantic annotations – Linking entities found in a document to ontology – Linking terms to a specialized lexicon [TR]• Actionable information – Rules over semantic annotations – Violated rules can modify the appearance of the document (Show an alert)
    54. 54. Active Semantic Patient Record• An application of ASD• Three Ontologies – Practice Information about practice such as patient/physician data – Drug Information about drugs, interaction, formularies, etc. – ICD/CPT Describes the relationships between CPT and ICD codes• Medical Records in XML created from database
    55. 55. Active Semantic Electronic Medical Record AppIn Use Today at Athens Heart Center For Clinical Decision Support since January 2006Amit P. Sheth, S. Agrawal,JonathanLathem, Nicole Oldham, H. Wingate, P. Yadav, and K. Gallagher, Active SemanticElectronic Medical Record, Proc. of the 5th International Semantic Web Conference, 2006
    56. 56. Demo of ASEMR and other applications http://knoesis.org/showcasehttp://archive.knoesis.org/library/demos/
    57. 57. Benefits of ASEMR• Error prevention (drug interactions, allergy) – Patient care – insurance• Decision Support (formulary, billing) – Patient satisfaction – Reimbursement• Efficiency/time – Real-time chart completion – “semantic” and automated linking with billing
    58. 58. Using large data sets for StructuredData on the web:Linked Open Data – samples from2005 to 2010
    59. 59. Linked Open Data Publish Open Data Sets in RDF By 2010, 203 data data sets 25 billion TriplesImage: http://richard.cyganiak.de/2007/10/lod/
    60. 60. You publish the raw data… Semantic Web Adoption and Application
    61. 61. … and others can use it Semantic Web Adoption and Application
    62. 62. Using the LOD to build Web site: BBC Semantic Web Adoption and Application
    63. 63. Using the LOD to build Web site: BBC Semantic Web Adoption and Application
    64. 64. GoodRelations Ontology - RDFa Semantic Web Adoption and Application
    65. 65. GoodRelations Ontology - RDFa Semantic Web Adoption and Application
    66. 66. GoodRelations Ontology - RDFa Semantic Web Adoption and Application
    67. 67. Fast forward to 2010-2011
    68. 68. Schema.orgShared Amazing things can happenVocabulary Will give some on-line examples
    69. 69. Twitris: Semantic Social Web Mash-up Select date Select topic N-gram summaries Topic tree Sentiment Spatial Marker Tweet trafficImages & Videos Analysis Related tweets Reference news Wikipedia articles TWITRIS
    70. 70. Web (and associated for Human Experience is Computing computing) Enhanced Experience, Tech assimilated in life evolving/using semantics to leverage text Web as an oracle assistant / partner - “ask the Web”: Situations, 2007 + data + services Events - Powerset Objects Web ofpeople, Sensor Web - social networks, user-createdcasualcontent - 40 billionsensors, 500M+ FB users, 1B tweets/wk Patterns Web of resources - data, service, data, mashups Keywords - 4 billionmobilecomputing Web of databases1997 - dynamically generated pages - web query interfaces Web of pages - text, manually created links - extensive navigation
    71. 71. 2D-3D & Immersive Visualization, Human Impacting affects Computer Interfaces bottom line MigraineOntologies/Dom Magnesium ain Models/ inhibit isa Stress Knowledge Patient Calcium Channel Blockers Knowledge discovery SEMANTICS, MEANING PROCESSING Semantic Search/ Browsing/Personalization/ Patterns / Inference / Reasoning Analysis, Knowledge Meta data / Discovery, Semantic Visualization, Annotations Situational Awareness Search and Metadata Extraction/Semantic Annotations browsing Big data Structured text (Scientific Experimental Public domain publications / Clinical Trial Data knowledge white papers) Results (PubMed) 71
    72. 72. Semantics as core enabler, enhancer @ Kno.e.sis
    73. 73. Take Home Message (Cont.)Semantics play a key role in refering"meaning" behind the data. Requiresprogress from keywords ->entities ->relationships ->events, from raw data tohuman-centric abstractions.
    74. 74. Take Home Message (Cont.)Wide variety of semantic models andKBs(vocabularies, social dictionaries, community created semi-structured knowledge, domain-specific datasets,ontologies)empower semantic solutions. This canlead to Semantic Scalability – scalability that ismeaningful to human activities and decisionmaking.
    75. 75. Interested in more?Kno.e.sis Wiki for the following and more:• Computing for Human Experience• Continuous Semantics to Analyze Real-Time Data• Semantic Modeling for Cloud Computing• Citizen Sensing, Social Signals, and Enriching Human Experience• Semantics-Empowered Social Computing• Semantic Sensor Web• Traveling the Semantic Web through Space, Theme and Time• Relationship Web: Blazing Semantic Trails between Web Resources• SA-REST: Semantically Interoperable and Easier-to-Use Services and Mashups• Semantically Annotating a Web ServiceTutorials: Semantic Web:Technologies and Applications for the Real-World (WWW2007)Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications (WWW2011)Partial Funding: NSF (Semantic Discovery: IIS: 071441, Spatio Temporal Thematic: IIS-0842129), AFRL and DAGSI (Semantic Sensor Web), Microsoft Research (Semantic Search) and IBM Research (Analysis of Social Media Content),and HP Researh (Knowledge Extraction from Community-Generated Content).
    76. 76. Future: Computing for Human Experience http://knoesis.org Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing Wright State University, Dayton, Ohio, USA Vision Paper: Computing for Human Experience:http://wiki.knoesis.org/index.php/Computing_For_Human_Experience 76
    1. A particular slide catching your eye?

      Clipping is a handy way to collect important slides you want to go back to later.

    ×