Product development describes the path through which an object goes from being an idea to being a saleable result. The phase of product development encompasses diverse processes – based on the complexity of implementation of a product that is ready for production, from an idea that needs to be transformed. The people that participate in these processes occupy the different positions in the company.
Man as agent
The know-how pertaining to this is distributed among employees in different departments that work with different applications. The employees have completely different perspectives of the end product, evidenced in the analysis and design phases as well as the development and production of internal and external documentation.
In such processes, each person is available to communicate what they know. Often the data exchange is through documents:
* As knowledge carriers, the challenge is to incorporate knowledge (of the product, of specific processes or requirements from the project) in the form of suitable data in the documentation.
* As knowledge seekers, the task is to obtain the relevant information from the documentation.
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In philosophical sense
The origins of the word “Ontology” stem from synonyms of “metaphysics” or “leading philosophies” as defined by Aristotle. In this sense, Ontology is basically linked with the study of existence and being. Ontology is thus a part of philosophy, which wants to find out which things, and phenomena in the world are related to existence and which only in the thoughts of people or under specific conditions. A typical ontology question could be: when a tree in the forest topples, and there is nobody there that can hear it, does the falling tree even make a noise?
In the view of Information Technology
The 20th century is characterized by linguistic movements and strides in Science and Technology based on the methods and knowledge in formal logic. The term ontology is constantly changing and is subject to a modified understanding of the interaction between real objects of the world, symbols and thoughts. The fundamental discussion about these coherences is not new – they can be traced back to Plato and Aristotle. For instance, as observed in the Peri hermeneias [1]: “Spoken words are the symbols of mental experience and written words are the symbols of spoken words. Just as all men have not the same writing, so all men have not the same speech sounds, but the mental experiences, which these directly symbolize, are the same for all, as also are those things of which our experiences are the images.”
The semiotic triangle of ontological basis
Aristotle’s approach was further developed several times in the history of philosophy and schematically presented by Ogden and Richards for the first time in the year 1923 as a semiotic triangle.
The semiotic triangle exists in several variants. The relationships and characteristics of the vertices of the triangle are, for instance, extensively discussed by Charles Sanders Peirce. Basically it signifies that words, according to Peirce, do not symbolize a unique object in the world, nor can they be assigned to a related concept. For example: the word Jaguar could bring to mind either “animal“ or “car” and either object could be indicated by the word.
If we envisage that the intra-personal agent has access to a kind of semantic network of concepts, which is exhausted by the conversion to data of knowledge, then the data exchange between two agents can be represented by the diagram 3. The conversion to data is done using the semantic data model by Sieber/Kammerer [2] which represents the understanding of symbols by Peirce.
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The basic idea of ontology is that a specific group of agents can agree on the concepts that are important in their application area and how these are linked with one another. The term ontology in Information Technology thus signifies a formally defined system of terms (concepts) and their relationship with one another.
Prevent wrong interpretation
Ontology therefore minimizes the possibility of wrong interpretations of the used words and their corresponding relationships. Therefore, Ontology presents a conceptual basis to communicate knowledge (compare [3]).
The scope within which things can be termed as ontology range from
* very simple glossaries to
* Taxonomies, the concepts and relationships contained to
* very complex ontologisms that also contain rules apart from concepts and their relationships.
The latter allow a logical conclusion over a data quantity described with ontology. One such complex application can, for instance, be used to validate a product against its technical specifications and to determine early on if the product really does what it is supposed to. The successful application in projects is illustrated by the example of an implemented ontology-based validation of control equipment from the automobile industry.
Machine-supported validation of control equipment
The complexity as well as the number of control equipment in a vehicle is steadily increasing. High quality requirements and constantly sinking development cycles require intensive testing of control equipment during the development process. Several control equipment are produced by manufacturers today and delivered to car makers. These must test if the delivered control equipment corresponds to the requirements as well as product specifications. Different scenarios are simulated with control equipment at special testing bays and the results are recorded. The measured data must then be checked for accuracy using suitable methods. In spite of the enormous quantity of measured data, the amount of manual work required is very high.
The basis for further automation of this test process is a formal, or through machine processable description of the required result of individual control equipment. Using such information, the results obtained on the test bay for control equipment can be automatically validated. Deviations from the required result or errors can therefore be identified early. Ontologisms and rules form a promising technological basis to implement this application.
Illustration of Know-how
Using Ontology, the terms of an application area are formulated and set in relationship with one another. Diagram 4 shows a schematic abstract from ontology. It defines, for instance, that a vehicle is comprised of several parts. The parts can be classified into different classes such as motor, electronic and motor control. In the same way, it is defined that the motor control equipment only supports certain motors. Terminological occurrences such as synonyms – vehicle or car – can similarly be recorded in the corresponding ontology.
Finally, rules use the terms that were already defined in the ontology to create additional and very complex relations. Thus, the complete functionality of a control device is described while also describing specific error configurations. As diagram 4 shows, you can therefore check if the correct motor control equipment is built into the vehicle.
Integrated application in product development
The central task of the presented approach for test data analysis is the transformation of the know-how from technical documentation, for instance control equipment specifications, into ontologisms and rules. This procedure must be carried out manually today and is therefore prone to error and expenditure. Through integrated application of ontologisms in product development, this preliminary work can be carried out in a precedent process step. Apart from this, all the participating processes benefit from such a formal model as:
* While recording specifications, ontologisms and regulations can be used to create a uniform know-how basis for the product to be developed.
* Process steps arising later can use the available know-how and also enhance it.
* During development, ontology can be used to communicate without errors with external developers.
* During the test phase, the formal model can be used to validate the products.
Bridging knowledge management
Overall, the use of ontologisms can produce an integrated and uniform documentation of a product and its development. Not only technical documents need to be part of such know-how. Other data that are relevant for the creation of the product, for instance, regulations can also be a part. The heart of ontology-based documents and their machine-processability are the people involved in the process steps that need to be able to translate their knowledge into suitable form into data. Ontologisms can be the bridge, so to say, between knowledge management, documentation and data integration on all levels.
Links und Literature
[1] Aristotle: (2007): On interpretation.
http://etext.library.adelaide.edu.au/a/aristotle/interpretation/
[2] Sieber, T.; Kammerer, M. (2006): Sind Metadaten bessere Daten? In: technische Kommunikation. H. 5, S. 56–58.
[3] Sieber, T. (2005): Ontologies and their representation. Doktoranduszok Fóruma.
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