Version of Record online: 29 JAN 2013
© 2013 Wiley Publishing Ltd
Volume 30, Issue 1, pages 1–2, February 2013
How to Cite
Hall, J. G. (2013), Editorial. Expert Systems, 30: 1–2. doi: 10.1111/exsy.12012
- Issue online: 29 JAN 2013
- Version of Record online: 29 JAN 2013
Welcome to Volume 30 (Issue 1) of Expert Systems: The Journal Of Knowledge Engineering! As you will have noticed, Expert Systems has a new format, designed to provide a more capacious home for the increasing number of quality manuscripts that we receive.
There are other changes as 2013 brings new opportunities for publishing: Expert Systems' authors will now have the option to publish using our Open Publishing model: OnlineOpen. With OnlineOpen the author, the author's funding agency, or the author's institution pays a fee to ensure that the article is made available even to non-subscribers through Wiley's Online Library, as well as being deposited in the funding agency's preferred archive. Expert Systems' OnlineOpen program fulfils the requirements of the Wellcome Trust and the other UKPMC Funders. More details on the web-site.
I'm also pleased to welcome Professor Atilla Elçi (pictured), Head of the Department of Electrical-Electronics Engineering, Aksaray University, as a new Associate Editor. His research includes web semantics, agent-based systems, robotics, machine learning, knowledge representation and ontology, information security, software engineering, and natural language translation. Also, Professors Paolo Remagnino and Adrian Hopgood are joining the non-executive Editorial Board of Expert Systems, both having served as Associate Editors for the journal for a number of years.
Knowledge Science, Now!
One might assume that the more precise a theory the better it is for practical use but this isn't necessarily the case. In [Rogers], GFC Rogers observes that the nature of knowledge in engineering differs from that in science: “a theory can be of great practical use for design purposes, yet inadequate from a scientific point of view.” As illustration, Rogers mentions the preferential use of the older, known inadequate, corpuscular theory of light in the design of optical equipment, even though the more comprehensive wave theory that replaced it scientifically deals additionally with diffraction, interference and polarisation.
Science progresses through the scientific method: the youtube video (http://www.youtube.com/watch?v=b240PGCMwV0) shows Richard Feynman presenting on precisely that. Made in black and white, like many of the great comedy classics, the film is not only instructional but quite hilarious due to the audience's reaction to the great scientist. Already, within 7 seconds, Feynman has his first laugh: the audience guffawing – one can only assume that their disbelief got the better of them – at his assertion that science starts with a Guess. After mildly chastising the audience for their reaction Feynman follows up with Compute the Consequences, and then Compare with Experience. Feynman is propounding Popper's theory of science central to which is falsifiability – that one must be able to test to failure a scientific theory.
What does testing to failure mean? It means finding those predictions of a theory that do not stand up to comparison with observation, i.e., identifying where the theory is falsified by reality.
In 1687 Newton published his second law of motion: what is now the well-known equation F = ma of schoolroom science. Scientists took 200 years of computing the consequences of Newton's law to find an observation that didn't agree with it: in 1859 Urbain Le Verrier compared observations of Mercury's perihelion precession to those predicted by Newton's law, to find it wanting for the first time. In failing Le Verrier's test, Newton's second law was second guessed by Einstein with General Relativity.
Even as science progresses, then, it may appear that engineering stands still: but engineering is also the beneficiary of scientific progress. From the engineering viewpoint, the failure of Newton's second law did not damage the utility of F = ma; rather, with Einstein's extra precision, engineering gained knowledge of the accuracy and applicability of F = ma.
The basis of our discipline is knowledge: knowledge engineering is the application of knowledge through information systems. However, unlike traditional engineering disciplines whose sciences are well known and explored, we do not yet have a science of knowledge – knowledge science – whose explicative and predictive theories contribute to the engineering we do and from whose scientific method our engineering knowledge benefits. The next step in a maturing knowledge engineering discipline may well be a definition of knowledge that is a fit subject for scientific study.
The peer reviewers for Expert System that continue to dedicate their time to our community are unsung heroes. It is their dedication to the task, and the dedication of peer reviewers everywhere, that keep academia alive. Nowhere else in today's world is constructive criticism and guidance needed so much as in academic publication. So a big thank you to all that contributed peer reviews to Expert Systems in 2012. A list of people that contributed reviews is available at the end of this issue.