Transcript Document

Semantic Business
Management
November 5, 2009
Paul Haley
Automata, Inc.
[email protected]
(412) 716-6420
Forecasting beyond rules for…
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Model-driven architecture
Service-oriented architecture
Complex event processing
Business process modeling
Business activity monitoring
Predictive analytics
Business intelligence
Corporate performance management
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The ontology is the model
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Business rule realities
• Derived from artificial intelligence
• Primarily based on production rules
• Substantially limited to forward chaining
– Backward chaining avoids combinatoric deduction
• Goals rarely explicit; no automatic sub-goaling
– Lacking deductive capability, authors bear the burden
• No ability to solve problems or optimize solutions
– No search to achieve goals or evaluate alternatives
• Not enough AI or operations research
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Business needs more AI
• Natural logic:
– Only full page color ads may run on the last page of the Times.
• Some business rules to enforce constraints:
– If an ad that is not full page is to be run on the last page of the
Times then refuse the run.
– If an ad that is not color is to be run on the last page of the Times
then refuse the run.
• Business rules for user interfaces:
– If asking for the size of an ad that is to be run on the last page of
the Times then the only choice should be full page.
– If asking for the type of an ad that is to be run on the last page of
the Times then full page should not be a choice.
• More general business rules (without if):
– Ads run on the last page of the Times must be full page.
– Ads run on the last page of the Times must be color.
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Semantic technology: the next step
• Semantics – focus on meaning (not structure)
• Resource Description Format (RDF)
– Graphs are the universal data structure
– Metadata is just more data in the graph
– World-wide identification of nodes, links
• More powerful, logical deduction
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Description logic (e.g., OWL-DL)
Logic programming (e.g., Prolog)
Predicate calculus (i.e., first-order logic)
HiLog (higher-order syntax for FOL)
• More powerful ontology (OWL)
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Incremental steps forward
• Production Rule Representation
– no functional advance
– may be adequate for some interchange
• Two very quick slides on:
– Semantics of Business Vocabulary & Rules
– World-wide web Rule Interchange Format
• Then back to the big picture
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OMG SBVR
• Semantics
– Business Rules
– Vocabulary
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logical aspects are a huge step forward
but no ontology – no meanings
and no runtime options
needs more linguistic competence
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W3C RIF
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Think of RIF as first-order logic in XML
a “dumb” version covers production rules
SBVR and RIF overlap on logic
SBVR textual, RIF formal syntax
Weak vocabulary in SBVR, none in RIF
Weak ontology in SBVR, strong in W3C
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Forecasting beyond rules for…
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Model-driven architecture
Service-oriented architecture
Complex event processing
Business process modeling
Business activity monitoring
Predictive analytics
Business intelligence
Corporate performance management
Copyright © 2009, Automata, Inc.
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BI, BPM & CEP realities
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Flowchart metaphor dominates
Events are second class citizens
Asynchronous activity is awkward
State within the business is poorly defined
Policies enforced only at certain points
Policy-based decisions are context free
Governance is not part of the process
Business transformation is like coding
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BAM, PA, BI, and CPM realities
• Activities have to be modeled (again?)
– How long does it take or how much does it cost X to do Y?
• Decisions have to be represented.
– How else can we audit or learn from what we have done?
• Predictive analytics doesn’t know what to look for
– will remain a skilled art until the meaning of data is clear
• Business intelligence is doesn’t know what matters
– will display the intelligence of analyst, not its own, until…
• Corporate performance management has no intelligence
– will remain insight-free BI until the goals and objectives of business are clear
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Ontology needed for
• BPMN
– events and processes
• BMM
– goals and objectives
• With ontology of rules, the process, and motivation:
– Predictive analytics can automate intelligent investigation
• understanding data produces better variables
• understanding data produces better hypotheses
• understanding objectives produces better KPIs
– BI produces more pertinent dashboards and reports
– CPM becomes more insightful and pertinent
• PA & BI identify variance that is relevant
• Sharing ontology across the business stack is key
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Events are primitive
• Events occur.
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They happen.
They are temporal.
Processes are a kind of event.
Actions are processes.
• It’s all about the verbs.
– Tense is context for BPM & CEP
– De-verbal nouns are not just “objects”!
• See the blog for all the details
• An SOA request is an action, process, and event.
• Semantic SOA is coming
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Service-oriented architecture
• Why was it in the abstract?
• An SOA request
– is an action
– is a process
– is an event
• Semantic SOA is coming
– the externalization of IT will continue
• so are intelligent web agents
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The ontology is the model
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and the process definition
the rest is the logic
including requirements and policies
and other rules
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