A System to Integrate Distributed Sources of Heterogeneous Scientific Information

1
A System to Integrate Distributed Sources of
Heterogeneous Scientific Information

• Amarnath Gupta, SDSC
• Bertram Ludaescher, SDSC
• Maryann E. Martone, NCMIR
• Ilya Zaslavsky SDSC
• University of California, San Diego

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A Standard Mediator Architecture (MIX --
Mediation of Information using XML)
USER-Query
XML Q/A
INTEGRATED VIEW
MIX MEDIATOR
XML Integrated View Definition
XML Q/A
XML Q/A
Wrapper
Wrapper
Wrapper
Files
Lab1
Lab2
Lab3
Data Sources
3
Integration Issues
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Integration Issues Mediating across
Multiple-Worlds

• Structural Integration
• gt common semistructured data model (XML)
• gt XML queries transformations to resolve
  schema conflicts
• Limited Query Capabilities
• gt mediator is aware of QCs exported by wrappers
  
• ...
• Semantic Integration
• most work deals with issues for one-world
  scenarios (e.g., amazon.com and bn.com)
• what if data comes from a multiple-world
  scenario (like Neuroscience), where data objects
  from different sources are not even similar, and
  only the hidden semantics (known to the domain
  expert) provides the semantic link?

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A Neuroscience Question
What is the cerebellar distribution of rat
proteins with more than 70 homology with human
NCS-1? Any structure specificity? How about other
rodents?
??? Integrated View ???
??? Integrated View Definition ???
???Mediator ???
Wrapper
Wrapper
Wrapper
Wrapper
Web
protein localization
morphometry
neurotransmission
CaBP, Expasy
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Hidden Semantics Protein Localization

• ltprotein_localizationgt
• ltneuron typepurkinje cell /gt
• ltprotein channelredgt
• ltnamegtRyRlt/gt
• .
• lt/proteingt
• ltregion h_grid_pos1 v_grid_posAgt
• ltdensitygt
• ltstructure fraction0.8gt
• ltnamegtspinelt/gt
• ltamount nameRyRgt0lt/gt
• lt/gt
• ltstructure fraction0.2gt
• ltnamegtbranchletlt/gt
• ltamount nameRyRgt30lt/gt
• lt/gt

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Hidden Semantics Morphometry

• ltneuron namepurkinje cellgt
• ltbranch level10gt
• ltshaftgt
• lt/shaftgt
• ltspine number1gt
• ltattachment x5.3 y-3.2 z8.7 /gt
• ltlengthgt12.348lt/gt
• ltmin_sectiongt1.93lt/gt
• ltmax_sectiongt4.47lt/gt
• ltsurface_areagt9.884lt/gt
• ltvolumegt7.930lt/gt
• ltheadgt
• ltwidthgt4.47lt/gt
• ltlengthgt1.79lt/gt
• lt/headgt
• lt/spinegt

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The Problem

• Multiple Worlds Integration
• compatible terms not directly joinable
• complex, indirect associations among schema
  elements
• unstated integrity constraints
• Why not just use Ontologies?
• typical ontologies associate terms along limited
  number of dimensions
• Whats needed?
• a theory under which non-identical terms can be
  semantically joined
• gt lift mediation to the level of conceptual
  models (CMs)
• gt domain knowledge, ICs become rules over CMs
• gt Model-Based Mediation

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XML-Based vs. Model-Based Mediation
XML Models
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Extended Mediator Architecture

• gt Wrappers export Conceptual Models (CMs), i.e.,
  factsrules for classes, relationships, ICs, ...
  )
• gt Mediator imports CMs (from sources, auxiliary
  knowledge bases, and domain maps (DMs)
• gt a generic conceptual model (GCM, a subset of
  F-logic), extensible via rules common target CM
  language
• gt new CMs can be plugged-in by specifying them
  in GCM F-logic rules
• gt prototype implementation in FLORA
• global-as-view approach
• compiler F-logic gt XSB-Prolog
• top-down evaluation gt virtual (demand-driven)
  views
• external interfaces (XML, RDBs, DM
  visualization,...)

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Model-Based Mediator Architecture
USER/Client
CM (Integrated View)
Domain Map DM
Integrated View Definition IVD
CM Plug-In
CM Queries Results (exchanged in XML)
Logic API (capabilities)
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Definition of Integrated Views ...

• XML-2-FL and CM-2-FL Translators

lt!ELEMENT Studies (Study)gt lt!ELEMENT Study
(study_id, animal,
experiments, experimentersgt lt!ELEMENT experiments
(experiment)gt lt!ELEMENT experiment (description,
instrument, parameters)gt
studyDBstudies gtgt study. studystudy_id gt
string animal gt animal
experiments gtgt experiment
experimenters gtgt string.

• Specification of Domain Knowledge
• Subclasses
• Rules
• Integrity Constraints
• Integrated View Definition

mushroom_spine spine
Smushroom_spine IF Sspinehead?_ neck ?_.
ic1(S)alerttype ? invalid spine object ? S
IF Sspineundef -gtgt head, neck.
protein_distribution(Protein, Organism,
Brain_region, Feature_name, Anatom, Value) IF
Iprotein_label_image proteins -gtgt Protein
organism -gt Organism

anatomical_structures -gtgt ASanatomical_structure
name-gtAnatom, NAEneuro_anatomic_entitynam
e-gtAnatom loccated_in-gtgtBrain_region, AS..seg
ments..featuresname-gtFeature_name
value-gtValue.
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... Definition of Integrated Views (Multiple
Sources)

• Creating Mediated Classes
• Reasoning with Schema

animalM?R IF Ssource, S.animal M?R
. Xtaxon?T IF X PROLAB.animalname ?N,
words(N,W1,W2_), T
TAXON.taxongenus ?W1species ?W2.
union over all classes
At Mediator
subspeciesspeciesgenus kingdomsuperkingd
om
TTR, TRTR1 IF T TAXON.taxonTaxon_Rank
?TR, Taxon_Rank1 ?TR1, Taxon_RankTaxon_Rank1.
Class creation by schema reasoning
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Model-Based Mediation with DOMAIN MAPS (DMs)

• Semantic Road Maps for situating source data
• gt navigational aid (browsing source classes at
  the conceptual level)
• gt basis for integrated views across multiple
  worlds
• gt link points (concepts) and labeled arcs
  (roles)
• gt formal semantics (in FL and/or DLs)
• Example ANATOM DM
• antatomical entities (concepts) is_a, has_a,
  overlaps, ... (roles)
• gt from syntactic equality to semantic joins

LINK(X,Y) X.zip Y.zip X.addr in Y.zip X.zip
overlaps Y.county ...
Integrated-CM(Z1,...) get X1,... from
Src1 get X2,... from Src2 LINK (Xi, Yj) Zj
CM-QL(X1,...,Y1,...)
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ANATOM Domain Map
ANATOM
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ANATOM Domain Map with Registered Data
ANATOM DATA
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Deductive Closure of has_a with tc(is_a)
ANATOM CLOSURE
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Example Query Evaluation (I)

• Example protein_distribution
• given organism, protein, brain_region
• ANATOM DM
• recursively traverse the has_a_star paths under
  brain_region collect all anatomical_entities
• Source PROLAB
• join with anatomical structures and collect the
  value of attribute image.segments.features.featur
  e.protein_amount where image.segments.features.f
  eature.protein_name protein and
  study_db.study.animal.name organism
• Mediator
• aggregate over all parents up to brain_region
• report distribution

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Interactive Queries (I)
KIND
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Example Query Evaluation (II)
"How does the parallel fiber output
(Yale/SENSELAB) relate to the distribution of
Ryanodine Receptors (UCSD/NCMIR)?"

• _at_SENSELAB X1 select output from parallel
  fiber
• _at_MEDIATOR X2 hang off X1 from Domain Map
• _at_MEDIATOR X3 subregion-closure(X2)
• _at_NCMIR X4 select PROT-data(X3,
  Ryanodine Receptors)
• _at_MEDIATOR X5 compute aggregate(X4)

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Interactive Queries (II)
KIND01
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Resulting Sub DOMAIN MAP Browser
PROTLOC
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Computed Protein Localization Data
PROTLOC
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Client-Side Result Visualization(using AxioMap
Viewer Ilya Zaslavsky)
PROTLOC-AxioMap
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Summary Outlook Federation of Brain Data
PROTLOC
Result (XML/XSLT)
Result (VML)
ANATOM