Three perspectives to GlobIS

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(No Transcript)
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Three perspectives to GlobIS
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Evolving targets and approaches in
integrating data and information (a personal
perspective)
Infocosm
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• Data recognized as corporate resource
  leverage it!
• Data predominantly in structured databases,
  different data models, transitioning from
  network and hierarchical to relational DBMSs
• Heterogeneity (system, modeling and schematic)
  as well as need to support autonomy posed
  main challenges major issues were data
  access and connectivity
• Information integration through Federated
  architecture
• Support for corporate IS applications as the
  primary objective, update often required,
  data integrity important

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Generation I
(heterogeneity in FDBMSs)
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Generation I
(Federated Database Systems Schema Architecture)

• Dimensions for interoperability and
  integration distribution, autonomy and
  heterogeneity

• Model Heterogeneity Common/Canonical
  Data Model Schema Translation
• Information sharing while preserving
  autonomy

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Generation I
(characterization of schematic conflicts in
multidatabase systems)
Sheth Kashyap, Kim Seo
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Generation I
(observations and lessons learnt)

• tightly coupled vs loosely coupled debate
  we were not able to develop global schema
  based systems
• good common data model debate we were
  not able to pick the best data model
• can we have a metadata standard for a domain?
• only for a limited purpose
• must learn to live with multiple data types,
  multiple metadata models/standards, and
  multiple ontologies

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• Significant improvements in computing and
  connectivity (standardization of protocol,
  public network, Internet/Web) remote data access
  as given
• Increasing diversity in data formats, with
  focus on variety of textual data and
  semi-structured documents
• Many more data sources, heterogeneous
  information sources, but not necessarily
  better understanding of data
• Use of data beyond traditional business
  applications mining warehousing,
  marketing, e-commerce
• Web search engines for keyword based querying
  against HTML pages attribute-based querying
  available in a few search systems
• Use of metadata for information access early
  work on ontology support distribution
  applied to metadata in some cases
• Mediator architecture for information
  management

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Generation II
(limited types of metadata, extractors, mappers,
wrappers)
Find Marketing Manager positions in a company
that is within 15 miles of San Francisco and
whose stock price has been growing at a rate of
at least 25 per year over the last three
years Junglee, SIGMOD Record, Dec. 1997
EXTRACTORS
METADATA
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Generation II
(a metadata classification the informartion
pyramid)

• METADATA STANDARDS
• General Purpose
• Dublin Core, MCF
• Domain/industry specific
• Geographic (FGDC, UDK, ),
• Library (MARC,)

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VisualHarness an example
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Whats next (after comprehensive use of metadata)?
Query processing and information requests
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GIS Data Representation Example
multiple heterogeneous metadata models with
different tag names for the same data in the same
GIS domain
Kansas State
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• Increasing information overload and broader
  variety of information content (video
  content, audio clips etc) with increasing amount
  of visual information, scientific/engineering
  data
• Continued standardization related to Web for
  representational and metadata issues (MCF,
  RDF, XML)
• Changes in Web architecture distributed
  computing (CORBA, Java)
• Users demand simplicity, but complexities
  continue to rise
• Web is no longer just another information
  source, but decision support through data
  mining and information discovery, information
  fusion, information dissemination, knowledge
  creation and management, information management
  complemented by cooperation between the
  information system and humans
• Information Brokering Architecture proposed for
  information management

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Information Brokering An Enabler for the
Infocosm
INFORMATION/DATA OVERLOAD
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Information Brokering Three Dimensions
Objective Reduce the problem of knowing
structure and semantics of data in the
hugenumber of information sources on a global
scale to understanding andnavigating a
significantly smaller number of domain ontologies
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What else can Information Brokering do?
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Concepts, tools and techniques to support
semantics
semanticproximity
context
inter-ontologicalrelations
media-independentinformation correlations
ontologies(esp. domain-specific)
profiles
domain-specific metadata
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Tools to support semantics

• Context, context, context
• Media-independent information correlations
• Multiple ontologies
• Semantic Proximity (relationships between
  concepts within and across ontologies) using
  domain, context, modeling/abstraction/representati
  on, state
• Characterizing Loss of Information incurred due
  to differences in vocabulary

BIG challenge identifying relationship
or similarity between objects of different media,
developed and managed by different persons and
systems
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Information Brokering over Heterogeneous Digital
Data A Metadata-based Approach

• Systems Heterogeneity information system
  heterogeneity (DBMSs, concurrency control)
  platform Heterogeneity (operating systems,
  hardware)
• Syntactic Heterogeneity different formats
  and storage for digital media machine readable
  aspects of data representation
• Structural Heterogeneity heterogeneity in
  data model constructs schematic/representati
  onal heterogeneity
• Semantic Heterogeneity
  terminological/vocabulary heterogeneity
  contextual heterogeneity

• Information Resource Discovery
• which/where are the relevant information
  sources ?
• Modeling of information Content
• increasing number of modeling
  possibilities
• Querying of Information Content
• Information Focusing
• Information Correlation
• combinatorial combinations of
  combining/subsetting information

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Heterogeneity...
is a Babel Tower!!