BORO – General Context C-FORS Summer School in Foundational Ontology (C-FORS 2025) 23 May 2025 , University of Oslo, Norway Chris Partridge, Chief Ontologist, BORO Solutions Schedule {5C22544A-7EE6-4342-B048-85BDC9FD1C3A} Morning Sessions 9:00 - 9:05 Session 0 – Introduction 9:05 - 9:45 Session 1 – Context 10:00 - 10:45 Session 2 – BORO Ontology 11:00 - 12:00 Session 3 – Analysis Tools Afternoon Sessions 1:15 - 3:30 Session 1 – Practical Examples 3:30 - 5:00 Session 2 – Examples Discussion / Presentation 2 Session 1 – Context: Structure Overall approach Context ontologies foundational ontologies – purpose foundational ontologies – nature 3 Overall approach Overall practice-focused approach A common way of looking at engineering, including ontological engineering, is as a practice , a way of doing things engineering as a discipline emerges from and supports the practice Foundational ontology engineering, or ontological engineering using foundational ontologies, is then also a practice Aim is to give some idea of the practice of using the BORO Foundational Ontology 5 First step Start by providing a general context to situate the BORO practice frame this with three questions why bother with ontologies? why bother with foundational ontologies? what kind of thing are foundational ontologies? the way we answer these questions provides a frame for understanding BORO’s approach to foundational ontology 6 Ontologies Why bother with ontologies? Why bother with ontologies? A common (almost universal?) answer (which we subscribe to) is they are useful/needed for (the practice of) improving interoperability particularly semantic interoperability “However, knowledge-based systems pose special requirements for interoperability . … For such knowledge-level communication, we need conventions at three levels: representation language format, agent communication protocol, and specification of the content of shared knowledge. … Ontologies can be used for conventions of the third kind: content-specific specifications” Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), Article 2. https://doi.org/10.1006/knac.1993.1008 8 What is interoperability? Term only started appearing in the 1960s recognised as a capability Genealogically: the definitions reveal a shift in emphasis in the early days, interoperability, particularly semantic interoperability, was theoretically defined in terms of a capability to understand talk about ‘meanings’ however, as people studied the problem, this has evolved into seeing it as an operational capability talk about being able to do things Operational capability definition is more common nowadays among practitioners Early (theory): interoperability among components of large-scale, distributed systems is the ability to exchange services and data with one another. … Semantic interoperability ensures that these exchanges make sense—that the requester and the provider have a common understanding of the “meanings” of the requested services and data.") Heiler, S. (1995). Semantic interoperability. ACM Computing Surveys (CSUR), 27(2), 271–273. Evolved (pragmatic – operational): within the past decade, it has been commonly defined as “The ability of systems, units, or forces to provide services to, and accept services from other systems, units or forces and to use the services so exchanged to enable them to operate effectively together.” Ford, T. C., Colombi, J. M., Graham, S. R., & Jacques, D. R. (2007). A survey on interoperability measurement. Gateways, 2(3) 9 If interoperability is recent, why now? The genealogy of (the term) interoperability shows, as noted, it is relatively recent term only started appearing in the 1960s emerged around the same time as use of computing in enterprises/institutions closely linked to computers/machines working together This implies a connection with computing not the same kind of concern prior to computing 10 What kinds of computing (machine) interoperability? If the new concern is how does communication work in the age of computing machines? This naturally gives rise to a three-way distinction based on the types of systems doing the exchange Machine-Machine Machine-Human Human-Human of these three – the first (and second) seem novel the third is plainly not novel! we will argue that as automation increases more and more information is communicated from ‘Machine-Machine’ 11 Visualising the three-way distinction brain external communication pre-speech speech text digital processing all the components for a digital information ecosystem have emerged: storage, processing and communication? 12 Tower of Babel narrative in Genesis 11:1–9 speaks to the power of interoperability and to the curse of not having it. And the LORD said, "Look, they are one people, and they have all one language, and this is only the beginning of what they will do; nothing that they propose to do will now be impossible for them . Come, let us go down and confuse their language so they will not understand each other.” In this ‘myth’, implausibly, the journey is ‘backwards’ from being interoperable to not being interoperable Ancient Human-Human lack of interoperability 13 Opportunities for improving (machine-machine) interoperability capability Different ways to ‘lack’ (machine-machine) interoperability capability failing (existing) capability common example failures in ‘accuracy’ of existing interoperability capability Mars Reconnaissance Orbiter – imperial versus metric (new) capability gaps not in the current (existing) capability common example curation requirements in data lakes raw data does not interoperate – it needs prior curation curation is expensive, so limited From an opportunity exploitation perspective capability gaps offer more opportunity for machine-machine exploitation obvious area for improvement is reducing cost of ‘curation’ (i.e. interoperability) 14 intra -operability inter -operability A Coasian ‘metric’ for the cost of interoperability system a system a system b system b We can use intra-operability as a benchmark to assess interoperability. The goal is for the costs of intra- and inter-operability to be roughly comparable. I t should be (roughly) as easy to communicate within as across systems. machines talking to themselves system a system a system b system b machines talking to other machines a simple synchronous interoperability test Coase, R. H. (1937). The nature of the firm. Economica 15 The rise of machine-machine interoperability Metaphor from the 1980s: islands of automation in construction https://en.wikipedia.org/wiki/Islands_of_automation Islands are data (digitised) Sea is pre-data (manual) This version is from1996 Height of the island shows when data emerged: nothing before the 60s https://en.wikipedia.org/wiki/Islands_of_automation see also: Bjork, B. (1987) The integrated use of computers in construction - The Finnish experience, ARECCAD 87, Barcelona, 17 Expanding – over time - islands of automation time The typical enterprise is now so automated that it no longer makes sense to talk about ‘expanding islands’ of automation … maybe, given the size, ‘ continents of automation’. However, it does still make sense to look at the bridges between the islands/continents. 18 As the islands expand ( automation increases), the systems abut – and so, the need to communicate ( interoperability - data exchange ) arises and increases. tl;dr – as systems grow, they abut and so need to communicate 4D perspective reveals vertical and horizontal data exchange 19 time key system diachronous migration synchronous exchange (API) System migrations, and their integral data migrations, are diachronous. W here the time axis goes up the page, these can be thought of as vertical migrations. By the same reasoning, system to system APIs are synchronous and so can be thought of as horizontal exchanges. horizontal vertical The significant scale of interoperability As systems get bigger, and the types of data typically increase the size of the task of ensuring interoperability increases Systems are now quite big some idea of the scale take as a reference a common enterprise application: for example, SAP ERP (https://en.wikipedia.org/wiki/SAP_ERP) a typical system may have 40,000 tables with over 1 million columns anecdotal evidence that systems on average get replaced every decade or so so, an enormous amount of migration going on 20 Narrow alleyways of machine interoperability 21 Returning to the ‘ capability gaps ’ way to ‘lack’ (machine-machine) interoperability capability When one looks more closely at current interoperability, it becomes clear that the data scope is very narrow. In other words, the capability gaps are wide This becomes particularly apparent when we attempt to integrate data for example, when multiple systems’ raw data is merged into data lakes the data usually needs curating (transforming) before it is interoperable the cost of this is significant, prohibitive. narrow broad Lack of integrated interoperability The narrow data scope of the interoperability is a marker of missed opportunities – a ‘ capability gap ’ it is a symptom of our inability to fully exploit the information in our systems it is ubiquitous and endemic every application system seems to exhibit this feature it grows as our systems grow each new system creates another barrier to integrated interoperability better exploitation requires better tools ones that significantly reduce costs 22 Process versus the end product Process versus the end product There appears to be a natural general tendency in engineering to focus on the end product and not take much account of its life cycle. In the context of top-level ontologies, this results in a focus upon the ontology (even the top ontology) and significantly less attention, sometimes no attention, on the ontologisation process from which this emerges. this is clearly reflected in the current status of work on computational top-level ontologies. Chris Partridge, C., Mitchell, A., de Cesare, S., Beverley, J. (2025). "Broadening Ontologization Design: Embracing Data Pipeline Strategies". https://www.academia.edu/129382330 24 Process versus the end product in logic As ( Dutilh Novaes, 2015) notes, in the context of logic, the process of formalisation is often neglected, and attention is focused on the formal results. She notes the importance of the former for real life application of the latter. She discusses two historical examples of processes of logical formalisation: Aristotle’s syllogistic theory from the “Prior Analytics”, and medieval theories of supposition, to both illustrate and illuminate how to formalize logical arguments. Dutilh Novaes, C. (2015). "The formal and the formalized: The cases of syllogistic and supposition theory". Kriterion : Revista de Filosofia, 56, 253–270. See also: Dutilh Novaes, Catarina. 2012. Formal Languages in Logic: A Philosophical and Cognitive Analysis 25 The current formalisation process Formalisation is: an iterative, (discovery,) empirical exercise should aim to ‘let the data speak’ in evolutionary terms, exploring the paths through the fitness landscape Current situation the formalisation process is largely unexamined (AKA unmanaged) typically, uncritically gives control of the form to the syntax 26 Exploitation opportunity This suggests an exploitation opportunity improving the end product by better engineering the process the improved engineering is a way to reduce the capability gap increasing interoperability with a better engineered process 27 A closer look at a ‘ capability gap’: in the ‘data exchange process’ Look more closely at a ‘data exchange process’ time Schematically, there are end nodes. The data exchange migrates and transforms data between these nodes. The transformation changes the data from the format of one system into the format of another 29 Data exchange transformation The data exchange involves the transformation of data in the format of one system into the format of another Review two aspects of the transformation transformation as translation and translation reflecting reference 30 Translation - interlingua Translation via an interlingua (language) Use a common interlingua as the hub for each translation spoke. 31 Reference - triangulate 32 Triangulate the mapping using ‘reference’ to objects in the domain – that is, a domain ontology This assumes the systems represent (refer to) the same things in the world. domain ontology Why bother with ontologies? Because improving interoperability is key to improving computer ecosystems, and ontologies enhance interoperability by helping to enable the use of reference to triangulate the interlingua translation in the data exchange process 33 Foundational ontologies – purpose Why bother with foundational ontologies? Why bother with foundational ontologies? We have a domain ontology Why do we need a foundational ontology? Show that: the domain ontology, on its own, is undermined by ontological relativity’s three theses of indeterminacy this indeterminacy is resolved by the foundational ontology 35 Quine’s three theses of indeterminacy Ontological relativity is underpinned by three theses of indeterminacy “Three theses of indeterminacy have figured conspicuously in my writings: indeterminacy of translation , inscrutability of reference , and underdetermination of scientific theory.” Quine, W. V. O. (2008). Three Indeterminacies. NOTE: translation and reference are key to successful interoperability Regarded as an important topic: for example: “W. V. O. Quine’s contention that translation is indeterminate has been among the most widely discussed and controversial theses in modern analytical philosophy. It is a standard bearer for one of the late twentieth century’s most characteristic philosophical preoccupations …” Crispin Wright (1999). "Chapter 16: The indeterminacy of translation Leave aside the controversy we can use this to explain the role of foundational ontology as a tool to manage metaphysical indeterminacy 36 Three consequences of indeterminacy There may be no unique way to: translate between two languages so, no single candidate interlingua weakens the translation interlingua approach determine the reference of terms in the languages so, no unique set of real-world objects to refer to weakens the real-world approach build a scientific account of our empirical data so, we cannot empirically test our theories Roughly: the metaphysics deals with the ‘stuff’ science cannot 37 For more background on Quine’s ontological relativity WVO Quine’s essay, “Ontological Relativity” (1969) turned 50 in 2019 Recurring topic in his work, see (for example): 1960, Word and Object 1970, On the Reasons for the Indeterminacy of Translation 1974, The Roots of Reference 1975, On Empirically Equivalent Systems of the World 2008, Three indeterminacies … See also: https://plato.stanford.edu/entries/quine/#UndeTheoEvidIndeTran 38 Why bother with foundational ontologies? The domain ontology, on its own, is undermined by ontological relativity’s three theses of indeterminacy There are metaphysical choices that aren’t empirical Foundational ontologies are a way to regain determinacy the foundational ontologies address these choices in a systematic metaphysical architecture this mitigates the indeterminacy but, it can be resolved in multiple ways, by foundational ontologies with different metaphysical architectures in other words, there are multiple possible foundational ontologies 39 Visualising the revised architecture 40 foundational ontology domain ontology Whither truth? The existence of multiple foundational ontologies, where the choice between them cannot be determined by empirical tests is evidence of the indeterminacy But what happens to ‘truth’ in this situation? “This is an issue on which Quine has not merely changed his mind but vacillated, going back and forth between what he calls the “ sectarian ” and the “ ecumenical ” responses. the sectarian response is to say that we should not let the existence of the alternative in any way affect our attitude towards our own theory: we should continue to take it seriously, as uniquely telling us the truth about the world. (We are assuming that the two theories possess all theoretical virtues to equal degree; clearly Quine would say that if one theory were superior in some way then we would have reason to adopt it.) the ecumenical response, by contrast, counts both theories as true.” https://plato.stanford.edu/entries/quine/#Unde 41 Foundational ontologies – nature How do foundational ontologies resolve this indeterminacy? Explaining the nature of foundational ontologies One way of characterising the indeterminacy is through metaphysical choices A foundational ontology makes a range of metaphysical choices in a coordinated way this results in a metaphysical architecture the range of the metaphysical choice is what generates indeterminacy making the metaphysical choice resolves the indeterminacy So, one way of explaining the nature of foundational ontologies is through the metaphysical choices that underpin their metaphysical architecture 43 Example category of architectural choice: whether to stratify or unify “4.2.2 Horizontal aspects: stratification versus unification There is a group of fundamental choices that impact the ontological architecture which involves whether or not to make a distinction. If one chooses not to make the distinction, one only introduces a single type. If one chooses to make the distinction, one introduces two types; one for each alternative. The choice boils down to whether to horizontally stratify or unify. One can describe choosing to make the distinction as ‘separating one potentially unified type into two’, creating a horizontal stratification in the hierarchy – and not making the distinction, ‘ unifying the potentially separated two types into one ’.” web-based: https://digitaltwinhub.co.uk/a-survey-of-top-level-ontologies/#a_survey_of_TLOs_contents One of the categories of architectural choice: horizontal aspects 44 Example: Stratification as a journey 4.2.2.7 Stratification journey There is limited inter-dependence between the choices meaning that a range of permutations are possible. For a top-level ontology, one can visualise the architectural stratification choices being adopted in a sequence, starting with no stratifications and introducing the choices one or two at a time – as illustrated in the figures below. This sequence or journey is a rational reconstruction – the original development of the top-level ontology is most likely ad hoc and bottom up. However, this reconstruction gives us a good picture of the underlying architecture. 45 Example metaphysical choice: locations web-based: https://digitaltwinhub.co.uk/a-survey-of-top-level-ontologies/#a_survey_of_TLOs_contents 4.2.2.2 Locations People often talk of physical objects and their locations, where physical objects occupy their locations, suggesting two related types; objects and locations (let’s leave the decision whether the location is spatial, temporal or spatiotemporal to the previous choice). For example, “today your car is parked in the same place as mine was yesterday” could be regarded as a location which was occupied by my car (a physical object) yesterday and your car today. There is a debate going back to Newton and Leibnitz in the 17th century as to whether location is absolute or relative. If it is relative, then location is clearly fundamentally different from physical objects – which aren’t. However, if it is absolute, a kind of substance, then this opens the possibility that one could unify objects and their locations as fundamentally the same, technically known as supersubstantivalism. If one does not have cases of interpenetration (see 4.3.3) then this resolves the oddity where physical objects exactly occupy a single location throughout their life – unifying eliminates this double counting. If there is interpenetration, then two objects may collapse to the same location – which may have unintended consequences. After the unification, the physical object and its location, two kinds of substance, are replaced by a single supersubstantival object. One has a broad choice between separating or unifying physical objects and locations. 46 Two (of many) levels of unifying-stratifying locations in space and locations in time are unified as locations in space-time matter and the space-time it is located in are unified as supersubstantival objects – matter is then a way space-time can be temporal locations spatial locations spatio -temporal locations more stratified more unified happens at supersubstantival objects spatio -temporal locations material entities supersubstantival objects located at web-based: https://digitaltwinhub.co.uk/a-survey-of-top-level-ontologies/#a_survey_of_TLOs_contents 47 (physical) objects locations (physical) object 1 super-substantival objects super-substantival (physical) objects super-substantival (physical) object 1 (unified) entities (separated) entities location 1 unified separated Locations example choice 48 maps to subset of instance of located at Legend The HMELR test We developed the HMELR test to expose the implicit ‘horizontal’ metaphysical choices Acronym: H ow- M any-things- E xactly- L ocated-in-this- R egion? Basing the test on a region is empirically conservative it does not introduce empirical differences The test trades on a difference stratification: leads to a multiplication of exactly coinciding objects of the stratified types and a linking relation between the types unification: leads to a collapse into a single object of the unified type with identity as the linking relation (if you need one) this difference leads to a difference in numerical identity the count reveals the underlying metaphysical choice The ‘numerical identity’ difference also illustrates how data behaves under the choice multiplying objects leads to multiplying their representations (rows, etc.) 49 (physical) objects locations (physical) object 1 super-substantival objects super-substantival (physical) objects super-substantival (physical) object 1 (unified) entities (separated) entities location 1 unified separated Locations example - HMELR test HMELR 1 2 50 Corresponding database indeterminacy There is a corresponding ‘numerical identity’ difference for data behaves under the choice. Multiplying objects leads to multiplying their representations (rows, etc.) super-substantival database substantival database 51 A framework for: m apping the metaphysical architecture landscape https://www.repository.cam.ac.uk/handle/1810/313452 Appendix E: Summary of Framework Assessment Matrix Results 31 ontological choices 37 top ontologies shortlisted and assessed The ontological choices shape the architecture of the ontology web-based: https://digitaltwinhub.co.uk/a-survey-of-top-level-ontologies/#a_survey_of_TLOs_contents A map to navigate the different architectural possibilities 52 Mapping the metaphysical architecture landscape web-based: https://digitaltwinhub.co.uk/a-survey-of-top-level-ontologies/#a_survey_of_TLOs_contents Horizontal stratification choices 53 Mapping the metaphysical architecture landscape Horizontal Aspect: Stratification Clustering Stratification: (in the survey) unifying and separating clusters at each end of the spectrum – especially for the more ontologically commited . Dependencies seem lead to attraction one way or the other. web-based: https://digitaltwinhub.co.uk/a-survey-of-top-level-ontologies/#a_survey_of_TLOs_contents 54 What kind of thing are foundational ontologies? Foundational ontologies provide a metaphysical architecture different top ontologies provide different metaphysical architectures the architecture is underpinned by metaphysical choices addressed in a coordinated way the existence of the choice introduces indeterminacy making the choice resolves the indeterminacy resolving the metaphysical indeterminacy makes translation and reference (more) determinate enabling better interoperability 55 Summary Summary Improving interoperability is key to improving computer ecosystems, and ontologies enhance interoperability by helping to enable the use of reference to triangulate the interlingua translation in the data exchange process but these are undermined by ontological relativity’s indeterminacy Ontological relativity’s indeterminacy can be resolved by a foundational ontology it can be resolved in multiple ways, by foundational ontologies with different metaphysical architectures in other words, there are multiple possible foundational ontologies Foundational ontologies provide a metaphysical architecture the architecture is underpinned by metaphysical choices resolving these resolves metaphysical indeterminacy makes translation and reference (more) determinate enabling better interoperability 57 Questions 58 59 60