Next Generation StandardsNext Generation Standards

A Science-Based Discipline of Information A Science-Based Discipline of Information Management for Integrated SystemsManagement for Integrated Systems

Steven Ray, Ph.D.

Distinguished Research Fellow

Carnegie Mellon University – Silicon Valley

The Global Supply ChainThe Global Supply ChainNot Quite FlatNot Quite Flat

– Increasing globalization of the manufacturing enterprise and of markets for manufactured goods

– Increased outsourcing as major manufacturers focus their businesses on design, integration, core fabrication, and assembly

– Compressed cycles of innovation and product introduction

– Increasing competitive pressures to manufacture products with higher quality and better performance at lower cost

As companies globalize, major informational barriersstill exist that impede the seamless interoperability of

technical and business systems amongcustomers and partners

Main PremiseMain Premise

• As a general rule, there is not enough rigor in the specification of information-exchange standards

Rigorous DefinitionsRigorous Definitions

Old-style (most common) standards specifications: (e.g. ISO 14258, Requirements for enterprise-reference architectures and methodologies)

“3.6.1.1 Time representation If an individual element of the enterprise system has to be traced then properties of time need to be

modeled to describe short-term changes. If the property time is introduced in terms of duration, it provides the base to do further analyses (e.g., process time). There are two kinds of behavior description relative to time: static and dynamic.”

Data-model standards (e.g. ISO 10303-41, Product Description and Support)

ENTITY product_context SUBTYPE OF (application_context_element); discipline_type : label;END_ENTITY;

Semantic-model standards (e.g. ISO 18629-11, PSL Core)(forall (?t1 ?t2 ?t3) (=> (and (before ?t1 ?t2) (before ?t2 ?t3)) (before ?t1 ?t3)))

Some Consequences of a Some Consequences of a Disciplined ApproachDisciplined Approach

• Formalization enables automation– Semantic technologies hold great promise for

machine-to-machine interactions

Self-integrating systemsSelf-integrating systems

Explicit, formal semanticsExplicit, formal semantics

Formalization Enables Formalization Enables AutomationAutomation

Common models of dataCommon models of data

Self-describing systemsSelf-describing systems

Some Consequences of a Some Consequences of a Disciplined ApproachDisciplined Approach

• Formalization enables automation– Semantic technologies hold great promise for

machine-to-machine interactions

• Engineering disciplines require measurements and testing

Engineering Disciplines require Engineering Disciplines require measurements and testingmeasurements and testing

“When you can measure what you are speaking about and express it in numbers, you know something about it; but when you cannot measure, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts, advanced to the stage of science.”

–Lord Kelvin

There is a deeper problemThere is a deeper problem

Source: Robert N. Charette, in “Why Software Fails,” IEEE Spectrum, September 2005

“Like electricity, water, transportation, and other critical parts of our infrastructure, IT is fast becoming intrinsic to our daily existence. In a few decades, a large-scale IT failure will become more than just an expensive inconvenience: it will put our way of life at risk. In the absence of the kind of industrywide changes that will mitigate software failures, how much of our future are we willing to gamble on these enormously costly and complex systems?”

- Robert N. Charette, in “Why Software Fails,” IEEE Spectrum, September 2005

from Mary Shaw, “Three patterns that help explain the development of software engineering”(position paper, Dagstuhl Workshop on Software Architecture, 1996)

“Engineering enables ordinary people to do things that formerly required virtuosos” – Mary Shaw, 1996

Evolution of Evolution of Engineering DisciplinesEngineering Disciplines

The State of Information The State of Information Engineering as a DisciplineEngineering as a Discipline

Information Science

Information Technology & Metrology

Information Applications Most software applications

Few rigorous metrics

Predictive theories virtually absent

Compared with a traditional Compared with a traditional engineering disciplineengineering discipline

Information Science

Information Technology & Metrology

Information Applications

Laws of Physicse.g. Conservation of Energy

S.I. Units, Measurements of

mechanical energy, etc.

Engines, turbines… Industry

Measurement Institutes (e.g. NIST)

Scientific research institutions

InformationEngineering

MechanicalEngineering

Practitioner

What can be done in the What can be done in the long term?long term?

• The research community needs to develop an additional science base:

A Science of Information

Information Science

Information Technology & Metrology

Information Applications

Success in the future will depend on Success in the future will depend on how well you handle informationhow well you handle information

Until we can Until we can predictpredict the behavior of the behavior of new, untested systems, new, untested systems, complex information systems will complex information systems will continue to be plagued with faultscontinue to be plagued with faults