– Bruce Long
Methodology is of central importance to any professional discipline: even philosophy. Of course philosophical methodology is rarely the same as scientific methodology. In philosophy we talk about philosophical methodology, and about meta-philosophy (and about such things as metametaphysics). Metaphilosophy is the philosophy of how to do philosophy (or more directly – the philosophy of philosophy).
Methodology (scientific and philosophical) is of central importance especially in philosophies of science and mathematics. The philosophy of biology, the philosophy of physics, the philosophy of information, and the philosophy of urban planning are all called upon to address issues of method and methodology within the disciplines and that they study. Bertrand Russell and Alfred North Whitehead did it for logic, Karl Popper (and George Lakatos and Paul Feyerabend) did it for the philosophy of science, and Rudolph Carnap and W.V.O Quine did it for the philosophies of physics, mind, and mathematics and their associated metaphysics.
In our previous forays into the philosophical underpinnings of planning philosophy, we have largely engaged with existentialist and postmodern, and thus continental philosophical subdisciplines. However, we have not forgotten that the philosophy of planning is heavily influenced by apparent dichotomies belonging to the analytic Anglo-American philosophical tradition: positivism versus constructivism, and objective realism versus subjectivism and such views as idealism (everything exists in the mind, or even in the mind of a god), for example. Most planning philosophy – that is not primarily focused upon the character of cities or the human aesthetic and value-making experience of living spaces – is about the debates between analytic constructivists and positivists.
The analytic and continental wings of contemporary philosophy have a hard time living together, but philosophy is nothing if not open minded, and philosophers are perpetually prepared to argue a point with intellectual candor and rigour, as that is part of the definition of the discipline (although there are very different styles of rigour familiar to both schools of the discipline.) Philosophy as a whole is a very broad church, but may be the most internally divided one that humanity has ever established. The principle of charity (assuming – initially at least – that the other party is not simply defective in their reasoning) is a vaunted precept, and keeps those at opposing ends of debates and views at least (often grudgingly) acknowledging the relevance of each other’s arguments.
Positivism and scientism are of serious interest across the entire spectrum of continental and Anglo-American analytic subdisciplines of philosophy. Happily for our previous philosophical analysis and musings, constructivism and positivism are topics (especially positivism) that strike a chord with continental philosophers also. Recall also that in a previous article we discovered that there have been philosophers on the continent, like early informationist Abraham Moles, with very analytic leanings and scientific backgrounds, but who have approached topics in literary theory and modernism (analytic philosophers tend to speak instead of aesthetics and such things as the philosophy of fiction).
Here, however, our investigation into the methodology of planning and its philosophy turns primarily upon the analytic Anglo-American tradition and its descendants. This is largely because continental philosophy has little interest in methodology.
Methodologies are generally formulated and chosen as guided by objectives and experimental limitations in scientific disciplines. Anglo-American philosopher of science Popper’s hypothetico-deductive concept insinuates up front common sense and pre-empirical concepts in the production of hypotheses and plans for testing them. Hard data and experiments de-rigeur, with statistical modeling, come afterwards, and then the process and experiment is refined as necessary.
In urban planning, positivistic planners tend to favour hard data and scientifically adduced facts, where the science is of the rigorous and data-centric variety. Constructivists do not decry important data, but tend to include a lot more social-psychological observations and imperatives, including the kind of aesthetic considerations that architects are prone to find important.
Methodology is, accordingly, informed by epistemologies – theories of how knowledge obtains and is attained – and ontologies – or theories an descriptions of that which exists in the problem domain and how it exists (which is a sub-disciplinary question in metaphysics). Epistemologies are theories about, and conceptions of how, one comes to have knowledge about a problem domain, truth, or some facts (and in fact what constitutes those things). This is a typically pedantic – yet very important – set of philosophical concerns. They come under the head of things that seem obvious, and like they should be a waste of time to think about, but are revealed upon scrutiny to involve difficult questions that matter and are hard to answer.
We need to be very careful conceptually and terminologically when discussing ontology and ontologies in the context of planning practice. In the last 10 years in computer science and database theory – the term ontologies has come to apply to a fairly specific set of technology solutions and their implementation. Semantic ontologies (and this really sounds just like philosophical talk of the analytic variety) are a domain set of theories and tools used in information science and specifically database design, and especially the design of large scale database implementations for such things as computer simulations and games, geographic information systems, and big data solutions. They also have found a place on the Web, with its need for the organisation of very large amounts of data for the purposes of .
Happily, the idea of an ontology in information science and large scale distributed database theory is fairly directly derived from the philosophical concept with the same name. Moreover, the use of information-scientific ontologies is how philosophical ontology informs methodology in contemporary urban planning.
The underlying motivation for the development of ontologies for and as concepts and abstract modeling elements for technologies in computing and database theory is the overwhelming amounts of raw data that machine learning and big data analysts must deal with and make efficient and effective use of. Semantics (another term at home for years in very formal terms in two different guises in linguistics and philosophy) are developed and implemented in a kind of schema used to interpret data according to how it is being used an applied (so keep in mind – we are talking computer science and database theory here, not philosophy).
These semantics or rules for classification and meaning (and for what is associated with what, and why, and how) are applied across an ontology of objects (we are now using software and object database terminology). Such semantic ontologies are being deployed in the solution of complex city and urban planning problems. There is little point having copious data about mobility, environment, demographics, and , if there is no concept of how to best make use of it all to produce better plans (10). This approach applied to data for the development of large Web applications have come to be referred to as The Semantic Web.
The author of the salient wikipedia article actually does significant justice to our topic matter:
In computer science and information science, an ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse. It is thus a practical application of philosophical ontology, with a taxonomy.
I won’t say any more about this critically important part of the toolset of urban planners who use simulations and predictive analyses of various kinds, except to observe that – obviously – these tools and the approach that they are associated with are a key part of contemporary planning methodology.
What is critical to our discussion here is that the larger philosophical question that we have come across before still survives in a slightly altered guise: how do planners formulate what heuristics and semantics are important in determining which entities or objects in a society and a planning environment are important and how they should be semantically interpreted and associated. They do so using the semantic rules and simulations backed by information-scientific ontologies. The question is – should planners favour environmental data, or social scientific survey data – or data about the psychological health of inhabitants across different areas of a city? Who will decide what is important in the semantics, semantic Web, and any informatics that are deployed in simulation and modeling? (2, 3) Machine intelligence and database design are still largely garbage-in garbage-out prospects – until AI is able to decide for itself what is important, that is. This means that the process of determining the set of objects that belong in the salient ontologies, and the semantics that go with them, has become critical the the process of planning. It is not frivolous to surmise that the questions arising in constructivist-positivist debates are simply moved to the front of the semantics and ontology formulation.
Tewdwr Jones et. al approach the entire problem domain of city planning with an emphasis on systems thinking:
What will cities’ infrastructure look like in 2030? How should research methods and policy intelligence improve to take account of possible future threats or intelligence not flowing through to the right sectors in a timely manner? At an uncertain time for cities, this paper argues for long-term urban foresight as partnership exercises between universities and the cities within which they are located. Using a case study of the Land Use Futures project, and arguing for a new approach to foster spatial intelligence, we discuss deploying science reviews, systems thinking and scenario development methods as informed storylines in the evolution of places. (16)
All of this variety of methodology goes to the issue of epistemology. Epistemology – the philosophical discipline – has not been formally appropriated by computer scientists in the same purposes way as semantics and ontologies (with the distinctive, less purposed, exception of knowledge bases and knowledge systems), but it is present in urban planning methodologies nonetheless. Epistemology is the study of knowledge: of what knowledge actually is and how we get it. This subject is as old as philosophy itself. A popular view is that knowledge is justified true belief. This is referred to as the Platonic view. It was challenged in the 1980s by Edmund Gettier, who demonstrated its Achilles’ heel: there is no way to determine justification reliably and objectively.
The debate between constructivists and positivists in urban planning is very much an epistemological and methodological one. This is by dint of the nature of their argument, but it is also borne out as true by the direct adoption of computer and information scientists of philosophical terms and concepts in their actual modeling technologies and methods. It is not necessarily tautologically obvious that practical and philosophical disputes in urban and city planning are epistemological (about knowledge): “But, everything is an argument about knowledge, how to get it, and what to do with it!”. However, it is conceivable that the question of competing methodologies and an associated wrestle about how best to get and define planning knowledge might not be salient at all to the discipline. In physics, for example, there is arguably much less variance and debate about how to get to knowledge: any hypothesised particle or other phenomena has to be proven with rigorous and reproducible experimentation.
The constructivist-positivist debate is basically about what is important information and knowledge in planning, and how best to get it, and then how best to apply it. Now that planning is becoming – like most other scientific and engineering influenced disciplines – increasingly digital, these questions still exist at the beginning of a process of selection of technologies and the inputs (ontologies and their semantics included) to the systems used for modeling, prediction, and simulation for design and planning spaces and structures.
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