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Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)
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Inauguration Function - Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)

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Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis) …

Ohio Center of Excellence in Knowledge-Enabled Computing at Wright State (Kno.e.sis)

Center overview: http://bit.ly/coe-k
Invitation: http://bit.ly/COE-invite

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  • Let me start by offering my appreciation for our Chancellor Dr. Fingerhut’s visionary leadership in establishing the Ohio Center of Excellence program that identifies Centers and program that generate world-class research and help draw talent and investment to the state. I would be remiss if I did not call out tremendous leadership that our President Dr. Hopkins and his entire leadership team has shown in regards to identifying and promoting these centers– my tanks to Dr. Angle, Dr. Bantle. Dr. Jang, and Dr. Sudkamp– thanks for your early and steadfast support for Kno.e.sis.
  • In the 16th Century, Francis Bacon—an Englishphilosopher, statesman, scientist, lawyer, jurist and author established deductive methodologies for scientific enquiry… and he said something that is more true than ever– Knowledge is Power
  • A study of OECD countries over a decade showed that as much as 75% of the economic growth and most new jobs was due to knowledge-intensive services- and the importance of these services was not only limited only high-tech or IT areas, but pervaded all sectors of economy
  • 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?
  • So what is Kno.e.sis about– it is about stepping away from the concerns of storing and searching data, to that of improving human experience, human effectiveness, human performance, human productivity.
  • Our 15 faculty from 4 colleges are already engaged in multiple jointly funded grants, pending proposals, serving on interdisciplinary programs like Biomedical Sciences PhD program and on committees of students of colleagues.
  • One of the hallmarks of the knowledge enabled computinginfrasturucture is Enabling machines to understand the data that they are processing. At the core of this vision also shared by the Semantic Web is having a formal representation of a domain or what we call ‘domain knowledge’ –the entities involved in a domain and how are they related to each other..Where do we get some domain knowledge from – one could look to domain experts to categorize world knowledge in that domain, borrow from legacy systems or in many cases tap into the knowledge that is already present in documents ..
  • One of our projects in this space looks into scalable harvesting of community knowledge that exists about a domain in collaborative sources such as Wikipedia and scientific corpus to construct formal models of a domain
  • Here is an example of a Human performance n cognition Ontology developed by us using this technique and which is being used by human effectiveness directorate at the AFRLSeveral part of this work were conducted in collaboration with Hewlett Packard research labs who currently conduct beta testing of a commercial version called Taxonom.com
  • One application of building domain models is knowledge discovery or deriving informational nuggets present in data sources by using facts that you already know about a domain
  • One of our efforts in this direction uses existing domain models such as the UMLS or those built from wikipedia to guide browsing of concepts in documents and use the browse trails to formulate hypotheses to discover knowledge that we did not know previously existed in the data.
  • This work that envisions our information space as a web of relationships to connect diferent document or web resources represents in many ways the beginnings of the realization of the expansive memex vision and trailblazing that Dr Vanevar Bush outlined in 1945… As he was speaking to how our human brain navigates the information space… using an association of thoughts that link one item to the next
  • Several tools that we built in this space are available online and also shared as an open source project with the community
  • A second area where we extensively employ domain knowledge is in interpreting various forms of sensor data in order to achieve meaningful situational awareness..Today there are more than 40 billion mobile sensors on the groundAnd nearly 4 million people carrying mobile phones taking pictruesWith so many sensors around there is a lot of information available at hand surrounding any eventHow do u know that they all relate to the same event and lend an understanding for how event evolves?
  • The knowledge enabled techniques we develop enable a fusion of Sensor data – lending understanding from the stages of identifying sensors, to gathering processing and using this data for situational awareness and sense makingSome of our work in this space is being supported by the sensor directorate at the AFRL next door.
  • The last representative work we’d like to share with you is our work on making sense of social data, like those from Twitter and facebookaround news worthy events that are of interest to a populace.The goal is to offer an understanding of what people are talking about and paying attention to
  • What the social perceptions behind the data might be, the multiple narratives
  • Twitris is our effort in this direction to help users keep up with observations made around news-worthy events.. Before I hand over the microphone to Dr. Mike Raymer, I’d like to leave you with a short demo of the deployed web application.
  • No where is it more important to enable the path from data to understanding than in the medical and life sciences!The barriers to interdisciplinary collaboration are high – natural scientists and computer scientists speak different languages.More new words in their first biology class than an entire year of a foreign language.We have demonstrated success in breaking down those barriers.Cross-disciplinary scientists (we make it our job) & cross disciplinary students.
  • No where is it more important to enable the path from data to understanding than in the medical and life sciences!The barriers to interdisciplinary collaboration are high – natural scientists and computer scientists speak different languages.More new words in their first biology class than an entire year of a foreign language.We have demonstrated success in breaking down those barriers.Cross-disciplinary scientists (we make it our job) & cross disciplinary students.
  • No where is it more important to enable the path from data to understanding than in the medical and life sciences!The barriers to interdisciplinary collaboration are high – natural scientists and computer scientists speak different languages.More new words in their first biology class than an entire year of a foreign language.We have demonstrated success in breaking down those barriers.Cross-disciplinary scientists (we make it our job) & cross disciplinary students.
  • Example – AFRL problem – collaboration with Dr. Nick Reo, School of MedicineDr. Reo – Nuclear Magnetic ResonanceProblem – highly complex data sets – many noisy results from each experiment
  • Example – AFRL problem – collaboration with Dr. Nick Reo, School of MedicineDr. Reo – Nuclear Magnetic ResonanceProblem – highly complex data sets – many noisy results from each experiment
  • No where is it more important to enable the path from data to understanding than in the medical and life sciences!The barriers to interdisciplinary collaboration are high – natural scientists and computer scientists speak different languages.More new words in their first biology class than an entire year of a foreign language.We have demonstrated success in breaking down those barriers.Cross-disciplinary scientists (we make it our job) & cross disciplinary students.
  • Transcript

    • 1. SCHEDULE
      • 8:30am-8:55am CONTINENTAL BREAKFAST
      • 2. 9:00am-10:15am INAUGURATION CEREMONY(Endeavor Room, Student Union)
      - Chancellor of University System of Ohio, Eric Fingerhut
      • President of Wright State University, Dr. David R. Hopkins
      • 3. Techincal Introduction of Knoesis (Dr.AmitSheth– Director, and the team)
      • 4. 10:15am-11:15am CAREER PANEL (Endeavor Room, Student Union)
      • 5. Professor Ahmed Elmagarmid, Purdue University
      • 6. Dr. Daniel Gruhl, IBM, Research
      • 7. Dr. PankajMehra, HP Labs
      • 8. Dr. Daniel Serfati, Aptima
      • 9. Dr. Harry Silver, LexisNexis
      • 10. 11:15am-12:00pm POSTERS/DEMOS
      • 11. Twitris, Cuebee, Scooner, Sensor Web etc
      • 12. 2:00pm-3:00pm Technical Talk I
      - Semantic Supercomputing
      • Dan Gruhl, Room 365, Joshi Center
    • Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
      Amit Sheth, Director
    • 13. Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
      scientiapotentiaest
      Knowledge is Power
      Francis Bacon, 1597
      …established and popularized deductive methodologies for scientific inquiry
      3
    • 14. Ohio Center of Excellence
      Knowledge-Enabled Computing (Kno.e.sis)
      Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
      Our society has progressed from
      Agriculture
      Industrial
      Service
      Knowledge



      … we live in a Knowledge Society
      4
    • 15. Knowledge Economy
      As the economies have transformed ….
      … new era … where the principal component of
      value creation, productivity and economic growth is
      knowledge. Florida & Kenny 91
      5
    • 16. Knowledge Economy
      Thousands
      knowledge-intensive services are leading the all sector in job creation, R&D spending, average wages and growth.
      6
    • 17. Knowledge Economy
      Exploitation of Knowledge for improving human experience/effectiveness, social and economic gains
      Computer + Human Knowledge (knowledge discovery, insight)
      Computer + Collective Action Collective Intelligence (Knowledge)
      Computer (IR,ML,NLP) + Knowledge = (better extraction, next gen search) learning, insight
      Humanknowledge + Computer Representation = Situated Cognition
      Computer + Human + Knowledge(better) Interaction, (improved) Human Experience, (higher) Productivity
      7
    • 18. Knowledge Services
      Creation and exploitation of Knowledge for improving human experience/effectiveness, social and economic gains
      Computer + Human Knowledge (knowledge discovery, insight)
      Computer + Collective Action  Collective Intelligence
      Computer (IR,ML,NLP) + Knowledge = (better) learning (extraction, search…)
      Humanknowledge+ Computer Representation = Situated Cognition
      Computer + Human + Knowledge
      (better) Interaction, (improved) Human Experience, (higher) Productivity
      8
    • 19. affects
      Migraine
      Magnesium
      Stress
      isa
      inhibit
      Knowledge discovery
      Patient
      Calcium Channel
      Blockers
      2D-3D & Immersive Visualization, Human Computer Interfaces
      Impacting bottom line
      Domain Models/Knowledge
      Structured text (Scientific publications / white papers)
      Biomedical Knowledge Discovery,
      Knowledge
      Management & Visualization
      SEMANTICS, MEANING PROCESSING
      Patterns / Inference / Reasoning
      Meta data / Semantic Annotations
      Search and browsing
      Metadata Extraction/Semantic Annotations
      Massive amounts of data
      Clinical Trial Data
      Experimental
      Results
      Public domain knowledge (PubMed)
      9
    • 20. Kno.e.sis’ leadership in semantic processing will contribute to basic theory about computation and cognitive systems, and address pressing practical problems associated with productive thinking in the face of an explosion of data.
      Kno.e.sis intends to lead a march from information age to meaning age.
      Kno.e.sis Vision
      10
    • 21. Why Kno.e.sis?
      • We have exciting vision built on cutting edge research and technology
      • 22. We incorporate synergy to carry out exceptional vision
      • 23. We are world class – and recognized as such
      • 24. Our track record shows we can succeed
      • 25. We target the growth aspect of economy and regional/state needs
      11
    • 26. Globally Competitive Careers and Economic Development
      Dayton Region Companies
      WPAFB Directorates
      Human Effectiveness
      Sensor
      Woolpert
      REI Tech, Aptima
      Tech^Edge
      SAIC
      LexisNexis
      Knowledge Workers, Products, Services and Applications
      Human Sciences
      & Health Care
      Advanced Data Management
      Defense/Aerospace R & D
      Application to Regional Industry Cluster
      daytaOhio – a WCI
      Kno.e.sis+Faculty Strengths
      • Visualization and Data Mgt Infrastructure
      • 27. Consulting and Technology Transfer
      • 28. Cognitive Science & Human Factors
      • 29. Data Analysis/Mining/Visualization
      • 30. Info. & Knowledge Mgmt
      • 31. Web 3.0 (Semantics, Services, Sensors)
      • 32. Virtual Worlds, Social Computing
      • 33. High Performance/Cloud Computing
      • 34. Bioinformatics/Biomedicine, Healthcare
      Academic Research and Infrastructure
      12
    • 35. 13
    • 36. Significant Infrastructure
      Whole-Body Laser
      Range Scanner
      VERITAS
      stereoscopic 3D
      visualization
      NMR
      AVL
      14
    • 37. Exceptional
      Regional Collaboration
      • At least 6 active projects with AFRL/WPAFB
      • 38. Human Effectiveness Directorate
      • 39. Sensors Directorate
      15
    • 40. Exceptional
      National Collaboration
      • Univ. of Georgia, Stanford, Purdue, OSU, Ohio U., Indiana U. UC-Irvine, Michigan State U., Army, W3C
      • 41. Microsoft, IBM, HP, Google
      16
    • 42. Exceptional
      International Collaboration
      • U. Manchester, TU-Copenhagen, TU-Delft, DERI (Ireland), Max-Planck Institute, U. Melbourne, U Queensland, NICTA-Australia,CSIRO, DA-IICT (India)
      17
    • 43. Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
      Knowledge & Next Generation of the Web
      Web has become the core infrastructure for the knowledge economy
      Web 1.0: Web of Documents and Media
      Web 2.0: Web of People
      Web 3.0: Web of Meaning
      MeenaNagarajan
      Advanced Data Management
    • 44. KNOWLEDGE EXTRACTION
      “Human Cognition” AND Psychology AND Neuroscience?
      19
    • 45. Harvesting Community Knowledge & Scientific Corpus
      “Human Cognition” AND Psychology AND Neuroscience
      20
    • 46. Human Performance &
      Cognition Ontology
      “Human Cognition” AND Psychology AND Neuroscience
      21
    • 47. INSIGHTS &KNOWLEDGE DISCOVERY
    • 48. DataExploration on the Web
      Utilizes semantic information from domain models to guide user interaction
      • “PTEN protein could inhibit cell invasion even in the presence of ... epidermal growth factor receptor (EGFR)” [PMID: 15986432]
      • 49. “EGF and hypoxia induce CXCR4 in non-small cell lung cancer...” [PMID:15802268]
      Record navigation trail:
      • EGFR  induces  CXCR4
      23
    • 50. The Memex Vision
      [Vannevar Bush]
      Of now the human brain navigates an information space …
      “It operates by association. With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts, in accordance with some intricate web of trails carried by the cells of the brain.”
      24
    • 51. Cuebee and Scooner
      Shared as open source, with demos online.
      25
    • 52. Ohio Center of Excellence
      Knowledge-Enabled Computing
      SEMANTIC SENSOR WEB
      26
    • 53.
      Semantic Sensor Web
      Utilizes semantic technologies for situational awareness
      Data Storage
      (Raw Data, XML, RDF)
      Semantic Analysis and Query
      Feature Extraction and Entity Detection
      Semantic
      Annotation
      Sensor Data Collection
      Ontologies
      • Space Ontology
      • 54. Time Ontology
      • 55. Situation Theory Ontology
      • 56. Domain Ontology
      27
    • 57. Ohio Center of Excellence
      Knowledge-Enabled Computing (Kno.e.sis)
      SEMANTIC SOCIAL WEB
    • 58. Everyone Wants to talk …and be heard!
      Hundreds and thousands of tweets, facebook posts, blogs about a single event, multiple narratives, strong opinions, breaking news..
      29
    • 59. TWITRIS : Twitter+Tetris
      Our attempt to help you keep up with citizen observations on Twitter
      WHAT are people saying, WHEN, from WHERE
      Puts citizen reports in context for you by overlaying it with news, wikipedia articles!
      30
    • 60. 31
    • 61. Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
      Biomedical & Health Sciences
      From data to understanding
      Mike Raymer
      Many biomedical collaborations: Nick Reo, Toxicology; Tim Cope, Neuroscience;
      Jerry Alter, Protein Science; Oleg Paliey, Microbiolgy and health
      Many health care collaborations: Kate Cauley, Center for Healthy Communities; UC-Irvine – Emergency health, Sonia Michail, obesity & intestinal health; Bradley Jacobs, human health
      Human Sciences
      & Health Care
    • 62. Biomedical & Health Sciences
      From data to understanding
      33
    • 63. Computation & Life Science
      Publication/Funding Trends
      Perez-Iratxeta, C. et al. Brief Bioinform 2007 8:88-95; doi:10.1093/bib/bbl035
      34
    • 64. Biomedical & Health Sciences
      From data to understanding
      35
    • 73. Cross-disciplinary workHow we do it
      • Determine whether exposure has occurred
      • 74. Including low-dose exposure
      • 75. Predict downstream outcome
      • 76. Organ/system toxicity vs. recovery
      • 77. Using easily deployable tests
      • 78. Blood, urine, etc.
      36
    • 79. Cross-disciplinary workHow we do it - 2
      37
    • 80. Nationwide Health
      CDC
      VA
      IHS
      DoD
      SSA
      State and Local Gov
      Health Bank orPHR Support Organization
      Community Health Centers
      Community #1
      Labs
      As part of Nationwide Health Information Network effort, Center for Healthy Communities (CHC) will use its HIExTM system, supported through Wright State HealthLink and medical providers to electronically transmit data from their certified EHRs to the Social Security Administration (SSA). This will improved quality of care through analysis of large data sets documenting treatments and outcomes. Knoesis will be in the forefront creating the systems intelligence to better understand this complex, integrated information both at the individual provider level and in the realm of population health. CHC received ~1M contact from SSA.
      IntegratedDelivery System
      Pharmacies
      Community #2
      38
    • 81. Biomedical & Health Sciences
      From data to understanding
      Data
      Information
      Understanding
      39
    • 82. Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
      Cognitive Science & applications to Human Effectiveness
      John Flach
      Defense/Aerospace R & D
    • 83. Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
    • 84. Brightest Idea Award:National Center for Technology Innovation
      42
    • 85. VERITAS Robert Gilkey
      43
    • 86. Cognitive Systems Engineering
      44
    • 87. Cognitive Systems Engineering
      45
    • 88. GRAPHICAL INTERFACESKevin Bennett
      46
    • 89. Total Energy Path Display
      47
    • 90. Pasteur’s QuadrantDonald Stokes (1997)
      48
    • 91. Putting Humans Into Control
      Samuel Pierpont Langley
      49
    • 92. Regional Impact
      Collaboration by daytaOhio and the Dayton Development Coalition to Leverage Kno.e.sis
      Terry Rapoch – President/CEO daytaOhio
      Jim Leftwich – CEO Dayton Development Coalition
      50
    • 93. Regional Development Model
      Defense/Aerospace R & D
      Knoesis
      Advanced Data Management
      Human Sciences
      & Health Care
      51
    • 94. Collaboration Objectives
      • Complement the knoesis Center in two ways that are consistent with daytaOhio’s vision and regional role
      • 95. Expanding the scope of R&D into knowledge services
      • 96. Identifying opportunities to commercialize the knowledge services developed by Kno.e.sis
      • 97. Enhance the impact of Kno.e.sis on regional economic development
      • 98. Attracting more research funding and talent
      • 99. Providing commercial channel for knoesis innovations
      • 100. Supporting knowledge base start ups
      • 101. Bringing new products and service to existing businesses
      52
    • 102. Process
      • Continue to develop initial opportunities with LexisNexis
      • 103. Catalog knoesis Intellectual Property available for commercialization
      • 104. Qualify additional partners in the region working with Dayton Development Coalition
      • 105. Expand role of Knoesis in regional opportunities cyberspace and human effectiveness
      53
    • 106. Partners
      AFRL/HPW-RHCB/WSU
      SAIC
      • Sensor web
      Kettering/Siemens
      • Image knowledge extraction
      LexisNexis
      • Ontology, semantics browsers
      Ohio IT Alliance/Point Energy Solutions
      • Knowledge extraction
      • 107. Researchand development
      • 108. Evaluation of systems and process using Virtual Reality
      • 109. Integration of sensors into immersive visualizations
      • 110. Medical – post processing of images into immersive environments
      • 111. Commercial direction
      • 112. Integration, knowledge services IP
      • 113. Data center energy
      54
    • 114. Advisory Board
      55
    • 115. Board of Advisor’s View
      Prof. Ahmed Elmagarmid
      Cyber Center – Discovery Park
      Purdue University
      Ohio Center of Excellence on
      Knowledge-Enabled Computing (Kno.e.sis)
    • 116. Faculty
      • Over 2,000 citations per faculty, around 1,000 refereed publications – comparable to any excellent group; granted 74 PhDs, $50 million in cumulative funding
      • 117. Prof. Sheth among the most cited Computer Science authors in the world today(top 30 based on h-index)
      • 118. Prof. Bennett & Flach’s paper declared as one of most influential papers published in over 50 years in Journal of Human Factors; Prof. Raymer’s paper was cited in a US Supreme Court decision
      • 119. Kno.e.sis has attracted top-notch faculty
      • 120. High quality funding: NIH, NSF, AFRL…..innovation grants: Microsoft Research, Google, IBM Research, HP labs
      • 121. Entrepreneurship experience – launched several companies
      57
    • 122. Funding (7 faculty)
      58
    • 123. Funding
      Starting with current active funds of $8-10 million (supporting research of 15 faculty and 45+ funded grad students & postdocs)
      Kno.e.sis anticipates growing to $13 million in 5 years and $19.5 million in 10 years (25 faculty plus 75 researchers)
      59
    • 124. World Class Students
      • Meena Nagarajan gave a keynote at an international workshop– unheard of for a PhD student
      • 125. Satya, Cory, Karthikorganized international workshops
      • 126. Six of the senior PhD students: 84 papers, 43 program committees, contributed to winning NIH and NSF grants.
      • 127. LyubomirZagorchev, a recent alumni invited to give a talk at Harvard.
      • 128. Students interned at & collaborated with the very best places: Microsoft Research, Yahoo! Research, IBM Research, HP Labs, NLM, …and filed for 6 patents in 2 years
      60
    • 129. Opportunities
      and Challenges
      Noteworthy
      • Possibly the largest or second largest academic research group in the US in Semantic Web (key enabler of Web 3.0)
      • 130. World class faculty and students
      • 131. Regional, National and International Collaborations and Leadership (eg W3C)
      • 132. Recognition of the opportunity from the University leadership
      Adequate but will need to grow to support growth
      • Infrastructure (computing, space)
      • 133. Managing director, Professional Grant Writers/pre-award/post award teams
      • 134. Faculty lines – allocate new lines where there is excellence
      61
    • 135. Metrics
      How we propose to benchmark/evaluate the progress?
      • Recognition & Visibility (be #1, 2, or 3 in US)
      • 136. Funding (200% of averages in respective unit; over average of COE’s at tier 1 institutions)
      • 137. Student Achievements (15 to 20% above national &regional averages for salaries, placement in top 20% of high value jobs)
      • 138. Faculty Achievements (publications at 200% of respective units)
      • 139. Collaborations
      • 140. Economic Impact
      62
    • 141. 63
      Students
      Faculty
      Infrastructure
      &
      Commitment
      Funding
    • 142. Kno.e.sis - information age to meaning age
      Career panel next …
      64
    • 143. PanelWhat are exciting and emerging areas for careers? And how to prepare yourself for one?
      Prof. Ahmed Elmagarmid, Purdue University
      Dr. Daniel Gruhl, IBM, Research
      Dr. PankajMehra, HP Labs
      Dr. Daniel Serfati, Aptima
      Dr. Harry Silver, LexisNexis
    • 144. Demos andPostersnow

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