Semantic Business Management – Business Rules Forum 2009

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20 Νοε 2013 (πριν από 3 χρόνια και 10 μήνες)

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Semantic Business
Management

November 5, 2009


Paul Haley

Automata, Inc.

paul@haleyAI.com

(412) 716
-
6420

Copyright © 2009, Automata, Inc.

Forecasting beyond rules for…


Model
-
driven architecture


Service
-
oriented architecture


Complex event processing


Business process modeling


Business activity monitoring


Predictive analytics


Business intelligence


Corporate performance management


2

The ontology is the model

Copyright © 2009, Automata, Inc.

3

Copyright © 2009, Automata, Inc.

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




4

Copyright © 2009, Automata, Inc.

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.







5

Copyright © 2009, Automata, Inc.

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


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)



6

Incremental steps forward

Copyright © 2009, Automata, Inc.

7


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

OMG SBVR

Copyright © 2009, Automata, Inc.

8


Semantics


Business Rules


Vocabulary


logical aspects are a huge step forward


but no ontology


no meanings


and no runtime options


needs more linguistic competence


W3C RIF

Copyright © 2009, Automata, Inc.

9


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



Copyright © 2009, Automata, Inc.

Forecasting beyond rules for…


Model
-
driven architecture


Service
-
oriented architecture


Complex event processing


Business process modeling


Business activity monitoring


Predictive analytics


Business intelligence


Corporate performance management


10

Copyright © 2009, Automata, Inc.

BI, BPM & CEP realities


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

11

Copyright © 2009, Automata, Inc.

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


12

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




Copyright © 2009, Automata, Inc.

13

Events are primitive


Events occur.


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





Copyright © 2009, Automata, Inc.

14

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





Copyright © 2009, Automata, Inc.

15

The ontology is the model

Copyright © 2009, Automata, Inc.

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and the process definition


the rest is the logic


including requirements and policies


and other rules