KNOWME KNOWledgeMapExplorer Semantic Browsing of Integrated Data using Knowledge Maps

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KNOWME KNOWledgeMapExplorer Semantic Browsing of Integrated Data using Knowledge Maps

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Knowledge Map. A domain map representing terminological knowledge about ... A process map representing knowledge of state-transitions about ... Domain ... –

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Title: KNOWME KNOWledgeMapExplorer Semantic Browsing of Integrated Data using Knowledge Maps


1
KNOW-ME (KNOWledge-Map-Explorer)Semantic
Browsing of Integrated Data using Knowledge Maps
  • Knowledge Map
  • A domain map representing terminological
    knowledge about experimental data
  • A process map representing knowledge of
    state-transitions about temporal phenomena
  • Links between them

2
KNOW-ME Features
  • Query Capabilities
  • For Concept Maps
  • find paths having nodes (N1, ..Nk) and avoiding
    nodes (N?1, ..N ?m)
  • For Process Maps (STNs)
  • transition types and parameters
  • precondition-postcondition descriptions
  • traversing level of details elaborations and
    abstractions
  • For bridges across concept maps and process maps
  • locate a concept satisfying ltcondition1gt
    associated with some process which exhibits a
    state transition satisfying ltcondition2gt

elaborate
abstract
3
KNOW-ME Architecture
WebDot Graph Layout
(dakswebdot.sdsc.edu)
JSP
Java Bean
Tomcat Servlet/JSP Engine
KNOW-ME Query Engine
KNOW-ME Web-Browser (anywhere)
(pamina2.sdsc.edu)
Oracle DB
NCMIR CCDB
ANATOM Process Maps Domain Maps
(birn.sdsc.edu)
4
KNOW-ME w/ Domain Map
5
KNOW-ME w/ Process Map
6
KNOW-ME Result Graph
7
KNOW-ME Result Data
8
Summary KNOW-ME Features
  • Semantic Browsing of Data
  • Data about a concept
  • All electromicrographs of spiny dendrites
  • Data about a process
  • All electrode recordings that show
    long-term-potentiation
  • Data that is evidence of a process
  • All electromicrographs that suggest synapse
    generation occurs during LTP

Xufei Qian, Bertram Ludäscher, Maryann E.
Martone, Amarnath GuptaSan Diego Supercomputer
Center Department of Neurosciences University
of California, San Diego
9
Some Related References Mediation of
Neuroscience Data
  • Model-Based Mediation with Domain Maps, B.
    Ludäscher, A. Gupta, M. E. Martone, 17th Intl.
    Conference on Data Engineering (ICDE),
    Heidelberg, Germany, IEEE Computer Society, April
    2001.
  • Navigating Virtual Information Sources with
    Know-ME, X. Qian, B. Ludäscher, M. E. Martone, A.
    Gupta, demonstration track, Intl. Conference on
    Extending Database Technology (EDBT), Prague,
    Czech Republic, March 2002.
  • Model-Based Information Integration in a
    Neuroscience Mediator System, B. Ludäscher, A.
    Gupta, M. E. Martone, demonstration track, 26th
    Intl. Conference on Very Large Databases (VLDB),
    Cairo, Egypt, September 2000.
  • Knowledge-Based Integration of Neuroscience Data
    Sources, A. Gupta, B. Ludäscher, M. E. Martone,
    12th Intl. Conference on Scientific and
    Statistical Database Management (SSDBM), Berlin,
    Germany, IEEE Computer Society, July 2000.
  • A Cell-Centered Database for Electron Tomographic
    Data, M. E. Martone, A. Gupta, M. Wong, X. Qian,
    G. Sosinsky, S. Lamont, B. Ludäscher , and M. H.
    Ellisman. Journal of Structural Biology, 2002. to
    appear
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