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The AI, Database, Programming Languages, and Software Engineering communities have overlapping interests in modeling concepts, tools, and techniques.
AI Database PL SE
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Concepts
Tools
Techniques
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• Topics
– Type systems, data models, knowledge representation
– Modeling
• Workshops
– 1980 Pingree Park: Data Abstraction, Databases, and Conceptual Modeling
– 1981 New Hampshire: Integrating AI and Database Technologies
– 1982 Islamorada: <somethin’ good>
• Results
– Lots of noise, little persistent impact
– Communication failure between AI/DB/PL
– Conceptual modeling raised modestly: database community only
– Types and modeling too low ?
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• AI, Database, Programming Language an Software Engineering communities can contribute to the Next Generation Information
System?
• ICIS Vision
– Intelligent
– Cooperative
– Information Systems
• Collaboration, the essential ICIS requirement, raises the level of requirements such as interoperation
– Engineering
– Data
– Process
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• Areas of Focus
– Development
– Core technologies
– Cooperation
• Workshops
– 1991 Niagara Falls: ICIS Development
– 1991 Como, Italy: Core ICIS Technologies
– 1992 Dagstuhl: Distributed Cooperation in Integrated Information
Systems
• Results
– Hard to retro-fit ideas from different areas
– Failure to communicate: CSCW too far out
– Database progress
• Middleware, interoperability, …
• Deeper understanding of the problem space
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• Most terminology
• Interoperability and Evolution Are Critical and Hard (technically & otherwise)
• Key Core Technology For Future Systems
– Object Orientation
– Active Databases
– Multi-paradigm Execution Model
– Transaction services (orthogonal?)
• Little Impact of Conceptual and Application Modelling
• Higher Level Concepts, Tools, Techniques For ICISs ("In The Large")
• Little Understanding Of Application Requirements
• Semantic Interoperability: Always An Open Problem
• Object/System Mapping via Type System Mapping
• No or Little Global Anything (e.g., schemas, memory)
• Autonomy: Good and Realistic
• Message passing best communications paradigm for autonomy
• DB Interoperability & Loose Coupling via Gateways
• Heterogeneity : languages, paradigms, systems, ...
• More Flexible : Constraints, Negotiation, Transactions, ...
• Interoperability requires gateways (only alternative, global memory is bad)
• Events, Activities, Active DBs are very useful/necessary
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• Conceptual Modelling Will (Never) Be Useful
• Terms & Understanding
– Intelligence and Cooperation
– Database Management (seen by two different groups)
• Managing large amount of shared, persistent data
• Managing a model of knowledge of the world convenient for users
• Systems Considered: two extremes
– Revolution: New Stuff Only, Single Paradigm
– Evolution: Existing and new systems/technologies/etc., multi-paradigm
• Level and Nature of Interfaces to core technology (e.g., active
DBs)
• Level of Interaction between component ICISs
• "Intelligence" folks seen as space cadets by systems people!
• Rules: Languages, processing, architectures.
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• Focus on
– Agreements
– Big Picture
• Embrace Web Reality
– Understand the Web
• Radical differences
– Work web-like
• Radically change our behavior
• Advance database / Information Systems capabilities
– Develop a prototypical architecture
– Identify problems / challenges / opportunities
– Apply / evolve data management / Information System capabilities
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Agreement is required between two or more individuals share information.
An ontology can provide a basis for such an agreement on the elements of a schema.
Every individual has an ontology. Most often it is implicit.
When disagreements arises and the ontologies are made explicit (e.g., green and blue)
It turns out that the disagreements are due to differences in the implicit ontologies.
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Coordination
• Collaborative customer service
• Complex sales
• Distributed marketing
Transactions
Value
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2002
Information
2008
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• (Semantic) Web Underway
– I2 “ontologies” => semantic web legacy
• Behavioral change required
– Understand the web
– Web behavior
• Collaborate on the web
– Apply / evolve data management knowledge to new requirements
• Search
• Loose coupling
• Modeling
• Ontology
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