Ontology - Introduction ONTOBRAS-2013 The Industrial Application of Ontology: Driven by a foundational ontology ‘Real World’ Foundational Ontology
Abstract • The aim of the tutorial is to provide a practical introduction for researchers and practitioners to potential for the use of foundational ontologies in industrial applications, based upon an actual application. The tutorial will be based upon industrial work currently being done using the BORO foundational methodology; an ontology-based systems (and data) re-engineering and modernisation approach. It will start with an introduction to ontology, particularly foundational ontologies. It will then introduce the BORO ontology. • Using these introductions as a basis, it will walk through a number of illustrative examples of how the BORO methodology has been used to re-engineer data in an industrial context.
A series of modules: BORO Top Ontology Introduction BORO Standards BORO BDM Introduction Case Studies Structure of the tutorial
A brief history of ontology The BORO Top Ontology Basis For Choosing The Right Top Ontology Methodological Themes BORO Top Ontology Introduction - Topics
History of the word the word ontology is from the Greek ὄν, genitive ὄντος: of being (part. of εἶναι: to be) and -λογία: science, study, theory While the etymology is Greek, the oldest extant record of the word itself is the Latin form ontologia, which appeared in 1661, in the work Ogdoas Scholastica by Jacob Lorhard (Lorhardus) and in 1631 in the Lexicon Philosophicum by Rudolph Göckel (Goclenius). By this stage, it is regarded as forming the basic subject matter of metaphysics A brief history of ontology
Origins ontology as a mode of analysis is generally thought to have originated in early Greece and occupied most famously Aristotle, who created the first system of ontology in the form of an ontology of substances – often represented pictorially in the tree of Porphyry Ontology – as philosophy
Connection with Ontology and ‘Reality’ recognised from the start the issue is ontology, or the question of what exists. (Mealy 1967. p. 525) for some time now my work has concerned the representation of information in computers. The work has involved such things as file organizations, indexes, hierarchical structures, network structures, relational models, and so on. After a while it dawned on me that these are all just maps, being poor artificial approximations of some real underlying terrain. (William Kent 1978, “Data And Reality: Basic Assumptions in Data Processing Reconsidered”) Resulting view codified / standardised in the early 80s ANSI-SPARC - Griethuysen, J.v. ISO/TC97/SC5/WG3-N695 - Concepts and Terminology for the Conceptual Schema and the Information Base., ANSI, New York, NY, 1982 Ontology in the 1960s and 1970s
20th Century views Quine claimed that the question ontology asks can be stated in three words ‘What is there?’ and the answer in one ‘everything’ not only that, “everyone will accept this answer as true” though “there remains room for disagreement over cases.” (“On What There Is”) Mealy refers to this essay of Quine’s Jonathon Lowe has a more technical definition an ontology is “the set of things whose existence is acknowledged by a particular theory or system of thought.” (E. J. Lowe, The Oxford Companion to Philosophy) Note the thing/object turn. Defining ontology – in philosophy
Enterprise systems can be seen as ‘theories’ of their domains (Naur 1985) Recasting the philosophical description in these terms Enterprise System ontology: The set of things whose existence is acknowledged by a particular enterprise system A common way of characterizing this ‘acknowledgment’ relationship is as one of ‘ontic commitment’. (Quine 1969) Defining ontology - in enterprise systems Naur, P, “Programming as Theory Building”, Microprocessing and Microprogramming, 15, (1985), 254-261 Quine, WV, Ontological relativity, and other essays, Columbia University Press, New York, 1969
For the ontology to be useful, to be an engineering artefact, we need to describe it In AI, the term ‘ontology’ tends to be used to refer to the description (the engineering artefact), rather than what the engineering artefact describes One can then characterise the way it is described (independently of what or how it describes) “An ontology consists of a specific vocabulary, plus a set of explicit assumptions in the form of a first-order logical theory, where vocabulary words appear as unary or binary predicate names” One can then develop ontology languages that enforce these ways of describing if one wishes to do reasoning, then it makes sense to take this route Ontology as an engineering artefact
Ontology and the real world what things exists? Ontology as an engineering artefact how is the description artefact structured? What language is used? Both aspects need to be formalised For enterprise systems, formalising the first aspect is important for semantic interoperability, it is essential no amount of work on the second aspect, by itself, can get to the heart of semantic interoperability Two aspects
Two Aspects in Context Domain Representation
The BORO Top Ontology Why you need to make metaphysical choices
The BORO Top Ontology • It is helpful if the top ontology is comprehensive • if it lists all the kinds of things that exist
It is a categorical ontology. It categorises every kind of thing into ontological categories; Things Classes tuples The prime distinction between these categories is their criterion of identity: Things = 4D extension Classes = instances tuples = objects in places Practically, the categories need to be disjoint to avoid clashes of identity. Top Ontology features
Criteria of Identity are clearly technical. 4D objects are also technical hopefully, this illustrates that this kind of work involves what we earlier called ‘rational reconstruction’ Criteria of identity are part of a bigger picture – technically called metaphysical choices the reason for the name is that the choice seems to be independent from any empirical checks on the ‘real world’ however, it looks as if the choice you make can affect how easy it is to build your ontology – so it is worth getting right Brief overview of the metaphysical choices Ontology as a technical discipline
A partial list of choices extensionalism versus non-extensionalism – I – Universals extensionalism versus non-extensionalism – II – Particulars Second Order Universals perdurantism versus endurantism presentism versus eternalism absolute versus relative space, time and space-time modally extended versus unextended individuals materialism and non-materialism topology of time – branching or linear. Include or exclude abstract individuals Metaphysical choices
Some references for metaphysical choices • Focusing on choices for ontological engineering: • Partridge, C. (2002). LADSEB-CNR - Technical report 06/02 - Note: A Couple of Meta-Ontological Choices for Ontological Architectures. Padova, LADSEB CNR, Italy • Recap of (2002) paper above. • Borgo, S., A. Gangemi, N. Guarino, C. Masolo, and A. Oltramari. (2002). “WonderWeb Deliverable D15 Ontology RoadMap.” The WonderWeb Library of Foundational Ontologies and the DOLCE ontology. • p. 11 - 4 ROADMAP OF MAJOR ONTOLOGICAL CHOICES • Salim K. Semy, Mary K. Pulvermacher, Leo J. Obrst. (2004). Toward the Use of an Upper Ontology for U.S. Government and U.S. Military Domains: An Evaluation. DOCUMENT NUMBER MTR 04B0000063, MITRE TECHNICAL REPORT • p. 3-10 Table 2. Ontological Choices Summary. • Guidelines for Developing Ontological Architectures in Modelling and Simulation (Book Chapter): Authors: Chris Partridge, Andy Mitchell, and Sergio de Cesare. Chapter 2 in Ontology, Epistemology, and Teleology for Modeling and Simulation: Philosophical Foundations for Intelligent M&S Applications. Series: Intelligent Systems Reference Library, Vol. 44. Andreas Tolk, (Editor). ISBN 978-3-642-31139-0. Publisher: Springer. • Will find a discussion of these choices in any introductory textbook on metaphysics.
Extensionalism – I – Universals Extensionalism – II – Individuals Higher order universals Perdurantism Eternalism Relative space-time Modally unextended individuals Materialism Topology of time –linear Exclude abstract individuals BORO’s choices
They are not independent, so need to be made consistently For example, it is difficult to be extensional and include abstract objects, which typically have no extension Choices need to reflect the enterprise system ontology’s (engineering) goals Making metaphysical choices
We call these ‘types of sophistication’ Based upon the notion of what makes a good scientific theory – so have a pedigree Normally list six characteristics generality. The degree by which the scope of the types in the improved model can be increased without the loss of information simplicity. The degree by which the model can be made less complex explanatory power. The ability of the improved model to give increased meaning fruitfulness. The degree to which the improved model can meet currently unspecified requirements or is easily extendable to do so objectivity. The ability of the model to provide a more objective (shared) understanding of the world : in particular, to index a thing to its mode of existence as opposed to its mode of representation and/or application precision. The ability of the improved model to give a more precise picture of the business object These types are closely inter-related In our experience, the result is the identification of very general (highly re-usable) business patterns Basis for making the choices
Methodological Themes Ways of explaining what is happening in the ontological analysis process
Methodological Themes • (A slightly arbitrary selection) • All have the similar underlying theme; change can lead to improvements • Opaque Vision • Things are not what they seem to be; we need to ‘(re-)educate’ our current vision • Paradigm Shift • Reorganise the internal structure – see things in a (radically) new way • Shift to a new technology (e.g. from pen and paper to computing) needs a corresponding ‘conceptual’ shift. • Refactoring • Internal reorganisation can lead to substantially better knowledgebase • Rational Reconstruction • Improvements in in clarity and exactness • These all offer support for a revisionary rather than a descriptive approach. • A top ontology is a mechanism for delivering these kinds of changes.
Opaque Vision transparent vision opaque vision Now... that should clear up a few things around here No need for a top ontology Useful to have a top ontology
From code to ontological refactoring Code refactoring is a "disciplined technique for restructuring an existing body of code, altering its internal structure without changing its external behavior", undertaken in order to improve some of the nonfunctional attributes of the software. Advantages include improved code readability and reduced complexity to improve the maintainability of the source code, as well as a more expressive internal architecture or object model to improve extensibility. Ontology refactoring is a "disciplined technique for restructuring an existing body of knowledge, altering its internal structure without changing its external behavior", undertaken in order to improve some of the nonfunctionalfeatures of the knowledgebase. Advantages include improved readability and reduced complexity to improve maintainability, as well as a more expressive internal architecture or model to improve extensibility.
Paradigm Shift (Kuhn) Kuhn claims that the major scientific revolutions were conceptual rather than empirical shifts. They were about looking at the existing empirical data in a new way. He used the gestalt pictures as an analogy.
Carnap’s ‘Rational Reconstruction’ • 'Rational reconstruction’ (‘rationale Nachkonstruktion’) was the underlying motivation of his first major book, Der logischeAufbau der Welt. • "This holds especially for the problems that are posed, and for the essential features of the method which was employed. The main problem concerns the possibility of the rational reconstruction of the concepts of all fields of knowledge on the basis of concepts that refer to the immediately given. By rational reconstruction is here meant the searching out of new definitions for old concepts. The old concepts did not ordinarily originate by way of deliberate formulation, but in more or less unreflected and spontaneous development. The new definitions should be superior to the old in clarity and exactness, and, above all, should fit into a systematic structure of concepts. Such a clarification of concepts, nowadays frequently called “explication”, still seems to me one of the most important tasks of philosophy, especially if it is concerned with the main categories of human thought." • 1928, Der logischeAufbau der Welt, Berlin-Schlachtensee: Weltkreis-Verlag, 2nd ed. Hamburg: Felix Meiner, 1961 • This evolved into ‘explication’: • “The task of making more exact a vague or not quite exact concept used in everyday life or in an earlier stage of scientific or logical development, or rather of replacing it by a newly constructed, more exact concept, belongs among the most important tasks of logical analysis and logical construction. We call this the task of explicating, or of giving an explication for, the earlier concept ... (Carnap 1947, 8-9.)” • 1947, Meaning and Necessity, Chicago: University of Chicago Press, 2nd ed. 1956
Summary • An ontology is “the set of things whose existence is acknowledged by a particular theory or system of thought.” • A top ontology should set the architecture for the overall ontology; • One way it can do this is by providing a categorical breakdown of the things that exist. • Another way is by making the major ontological choices • The BORO top ontology uses these categories based upon their criterion of identity: • Things = 4D extension • Classes = instances • tuples = objects in places • It explicitly makes the major ontological choices.