International Institute of Interoperability Science
Large-Scale Engineering Systems Integration







An Institute of Advanced Industrial Mathematics
to Permanently Solve the Crisis in Interoperability, Standards, and
Large-Scale Engineering Systems Integration.





Institute Mission Statement

The modern world is founded on large-scale engineering systems that are dependent on information integration across multiple project teams working in different technological disciplines and using heterogeneous computer-support systems. Major studies have shown that the costs to industry of inadequate integration are enormous - in the billions of dollars - and considerable effort and expense are being put into solving it. Yet most solutions that are attempted, at the considerable costs, have been found to have purely temporary validity and have required the investment of enormous costs over and over again, in a never-ending cycle.

As an example, the design and manufacturing of a complex weapon system or commercial aircraft involves an intensive collaboration between prime contractors and distributed supply chains. CAD incompatibility between software systems in different components of the supply chain is a major obstacle to the exchange of CAD model data - a problem that can be alleviated only by standards or point-to-point translators. A significant international standard being developed to deal with this is ISO 10303 (STEP, STandard for the Exchange of Product model data). This is intended to provide a system-independent/neutral computer-interpretable representation of product data (physical and functional characteristics) across the entire product life-cycle (design and engineering analysis, manufacture planning and control, utilization, maintenance and support, disposal). The goal is that this representation should be suitable for (1) neutral file exchange, (2) implementing product databases, (3) archiving data and long-term data retention.

However, the problem with the main current approach in ISO 10303 is that it tends to create standards as a compromise between existing programs. Therefore these standards are subject to loss of validity the moment any one of those programs changes. This means that the considerable time and cost spent on establishing standards, by the participating aerospace, automotive, ship-building, and military organizations, have no permanent value for them, since programs are continually changed, and therefore these costs must be re-expended by those companies in never-ending cycles. This problem is well-known and is being increasingly expressed by ISO members with a quite a strong sense of defeat. As one of the leaders at ISO exclaimed at a recent meeting: "What we want to know is the intersection of future systems!"

What is not understood is that the most fundamental problem is as follows: Currently, interoperability is not being regarded as a phenomenon that should be studied and developed as a rigorous mathematical and scientifically-lawful phenomenon. The current means of dealing with interoperability is much the same as the way mechanical problems were handled prior to Newton: ad-hoc trial-and-error constructions that were completely local to the present problem, and with no sense that each problem is an example of a set of globally-valid laws that are expressible in mathematical equations that directly reveal the real structure of the problem and the means of solving it.


Definition of Interoperability Science
(Leyton 2002)

The methods currently used by organizations to attempt to solve interoperability are ad-hoc trial-and-error constructions that are purely temporary to the present situation, because they are compromises between existing releases of software. In contrast, Interoperability Science will solve the problems by developing a principled and systematic mathematical science consisting of a set of globally-valid laws that directly reveal the real structure of the problems and permanently solve them despite the changes in software and engineering systems.


A further justification of this approach is that, throughout the history of science, it has been consistently proved that there is nothing more practical than theory: Newton's theoretical system lead to enormous practical advances for civilization. Similarly, Maxwell's laws for electromagnetism predicted electromagnetic waves, which lead immediately to the discovery of radio-waves, which turned the world into a global communications village. The theoretical science called quantum mechanics, which is largely based on mathematical group theory, lead to nuclear physics. Correspondingly the creation of an interoperability science will lead to immense practical advances for industry.


To carry this out this program, the institute consists of the following:

(1) A consortium of mathematically-advanced scientists of proven capacity to formulate new and powerful theoretical understanding of complex domains that have not previously been understood.

(2) The involvement of major engineering organizations, such as aerospace and automotive production companies, space and military agencies, etc., to continually present these scientists with the complex integration problems that must be solved.

(3) An educational framework in which a new generation of students can be raised to think in the advanced scientific and mathematical techniques that are developed to solve the complex integration problem.


Near the beginning of this document, we illustrated the issues with the example of CAD interoperability. However, the institute concerns all major examples of interoperability, since this is the only way that a principled mathematical science of interoperability can be formed. Major examples of interoperability include: multi-disciplinary engineering and scientific project integration, ground-systems operations for aerospace, data integration in scientific exploration, complex weapons systems coordination, product life-cycle management in large-scale manufacturing, image data-base integration, data life-cycle extension by establishing permanent reusability for data and software, etc.


Contact information: Director:


Professor Michael Leyton,
DIMACS Center for Discrete Mathematics,
& Theoretical Computer Science,
Rutgers University, Busch Campus,
New Brunswick, NJ 08854,

E-mail address: