The Basics of 4-Dimensionalism and the Role it Can Take in Supporting Large Scale Data Integration 4-Dimensionalism in Large Scale Data Sharing and Integration Dr Matthew West OBE 1 -- 1 of 38 -- Dr Matthew West OBE 30 years with Shell • Originally a Chemical Engineer • Doing digital twins in the 1970’s • 30+ years in information management • Information Quality • Data Modelling for data integration • Master and Reference Data • Projects include PIPPIN, Shearwater and Downstream One Cofounder of Information Junction 2008 • Consultant with the Centre for the Protection of National Infrastructure 2017 • Technical Lead National Digital Twin programme 2020 25+ years in standards development • Founding Chair of EPISTLE • ISO 15926, ISO 18876, ISO 10303, ISO 8000 • ISO TC 184/SC4 Policy and Planning Committee, • Member BSI-AMT/4 • UK Expert for ISO-IEC 21838 – Top Level Ontologies Author of “Developing High Quality Data Models” Trustee – Ontolog Forum 2 -- 2 of 38 -- Introduction • The presentations today should be seen as an integrated whole rather than a collection of separate presentations. • This one is an introduction to the whole and covers the Information Quality Management angle which is the motivation for our interest in 4- Dimensionalism • Later presentations will go down through the 7 circles of information management shown here showing how 4D permeates what we are doing in developing and using 4-Dimensionalism on the National Digital Twin programme. 3 Top Level Ontology Foundation Data Model Industry Data Models & Reference Data Integration Architecture Process Model based Information Requirements Information Quality Management Core Constructional Ontology -- 3 of 38 -- 4-Dimensionalism Background -- 4 of 38 -- The original 3D position Author Document Comment Aristotle On the Heavens a solid has magnitude "in three ways and beyond these there is no other magnitude because the three are all." Physics [IV, 1] in the context of motion, there are six "dimensions", dividing each of the three into two opposites, "up and down, before and behind, right and left," these terms being taken relatively. Simplicius Simplicii in Aristotelis De Caelo Connnentaria notes "it is possible to take only three lines that are mutually perpendicular, two by which the plane is defined and a third measuring depth so that if there were any other distance after the third it would ne entirely without measure and without definition." John Wallis Treatise of Algebra (1685) “For Length, Breadth and Thickness, take up the whole of Space. Nor can our Fansie imagine how there should be a Fourth Local Dimension beyond these Three.” As with many things, started with the Ancient Greeks – and lasted over a millennia. -- 5 of 38 -- Early appearances Cajori, Florian (1926). "Origins of Fourth Dimension Concepts" (PDF). The American Mathematical Monthly. 33 (8): 397–406. Year Author Document Comment 1754 D'Alembert Encyclopedie Art. "Dimension “… one may however look upon duration as a fourth dimension, and that the product of time and solidity is in a way a product of four dimensions 1788 Joseph-Louis Lagrange Mécanique analytique mechanics operating in a four-dimensional space — three dimensions of space, and one of time. 1827 A. F. Möbius Der barycentrische Calcul a fourth dimension would allow a three-dimensional form to be rotated onto its mirror-image 1854 Georg Friedrich Bernhard Riemann On the hypotheses which underlie geometry formalized higher-dimensional spaces 1880 Charles Howard Hinton What is the Fourth Dimension?“ Explained what a "four-dimensional cube" is. -- 6 of 38 -- Origin of (geometric) four-dimensionalism "Space and Time" address at 80th Assembly of German Natural Scientists and Physicians on 21 September 1908: “The views of space and time which I wish to lay before you have sprung from the soil of experimental physics, and therein lies their strength. They are radical. Henceforth space by itself, and time by itself, are doomed to fade away into mere shadows, and only a kind of union of the two will preserve an independent reality.” Hermann Minkowski -- 7 of 38 -- A brief history of the developments in four dimensionalism: Selected major publications - I Year Author Publications 1920 A. N. Whitehead The Concept of Nature. Cambridge University Press, Cambridge. 1923 C. D. Broad Scientific Thought. Harcourt, New York. 1927 B. Russell The Analysis of Matter. Allen & Unwin, London. 1928 R Carnap Der logische Aufbau der Welt. Weltkreis-Verlag, Berlin. 1928 H. Reichenbach Philosophie der Raum-Zeit-Lehre, Walter de Gruyter, Berlin and Leipzig. 1937 J. Woodger The axiomatic method in biology. Cambridge 1937 The first half of the 20th century -- 8 of 38 -- A brief history of the developments in four dimensionalism: Selected major publications - II Year Author Publications 1951 N. Goodman Goodman, N., 1951. The Structure of Appearance. Harvard University Press, Cambridge (MA). 1950 W.V.O. Quine Methods of Logic. Holt, Rinehart & Winston, New York. 1955 Taylor Spatial and temporal analogues and the concept of identity. The Journal of Philosophy, 52: 599–612. 1955 J. J. C. Smart Spatialising time. Mind, 64: 239–241. 1967 H. Putnam Time and physical geometry, Journal of Philosophy 64 (8):240-247. 1971 D. K. Lewis Counterparts of persons and their bodies. The Journal of Philosophy, 68: 203–211. 1972 J. J. C. Smart Space-time and individuals. In Rudner, R. S. and Scheffler, I., eds., Logic and Art 1976 H. W. Noonan The four-dimensional world. Analysis, 37: 32–39. 1980 H. W. Noonan Objects and Identity. An Examination of the Relative Identity Thesis and Its Consequences. Nijhoff 1986 D. K. Lewis On the Plurality of Worlds. Blackwell, Oxford. 1980 D. M. Armstrong Identity through time. In van Inwagen, P., ed., Time and Cause. 1982 D. Robinson Re-identifying matter. The Philosophical Review, 91: 317–341. 1984 M. Heller Temporal parts of four dimensional objects. Philosophical Studies, 46: 323–334. 1990 M. Heller The Ontology of Physical Objects: Four-dimensional Hunks of Matter. Cambridge University Press, 1990 P. van Inwagen Four-Dimensional Objects, Noûs, 24: 245–55. 1993 M. Heller Varieties of Four Dimensionalism, Australasian Journal of Philosophy, 71: 47–59. 1991 R. Le Poidevin Change, Cause and Contradiction. A Defence of the Tenseless Theory of Time. Macmillan, London. 1993 M. Jubien Ontology, Modality, and the Fallacy of Reference. Cambridge University Press, Cambridge. The second half of the 20th Century The 21st Century texts on four dimensionalism are too numerous to list here. -- 9 of 38 -- What is 4-Dimensionalism? Hint: It is not just adding time to 3D, or even acknowledging special relativity In ontology it is a series of commitments that characterize a Top Level Ontology 10 -- 10 of 38 -- What is an ontology? There are many definitions, but my favourite is: theory of what exists i.e. the things that exist and the rules that govern them 11 -- 11 of 38 -- 3D time space Object extended in time The past and the future exist as well as the present 1. Individuals extend in time as well as space and have both temporal parts and spatial parts. 2. When two individuals have the same spatio-temporal extent they are the same thing (extensionalism). time space The present (all that exists) Object passes through time. 1. Physical objects do not have temporal parts. 2. Different physical objects may coincide (non-extensional). 4D + Extensionalism 12 -- 12 of 38 -- A framework for assessing an ontology’s architectural choices 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 -- 13 of 38 -- Stratification: 4D Ontologies’ choices category type choice 4D Ontologies Stratification space-time unifying or separating unifying locations-objects unifying or separating unifying properties-objects unifying or separating unifying endurants-occurents unifying or separating unifying immaterial-material unifying or separating unifying Some choices multiply entities, others reduce them. One thing that characterizes 4D Ontologies is that they are (from the framework perspective) maximally unifying. Motivation: • the presumed benefits of parsimony and cost of separation. • Nothing is lost in ability to support information requirements. -- 14 of 38 -- Stratification: visualizing unifying and separating 15 temporal entities spatial entities entities more stratified supersubstantival objects more unified happens at A key 4D choice is unifying space and time -- 15 of 38 -- installed removed removed installed Biden President of the US Time Space The President of the United States in 4D 16 Trump -- 16 of 38 -- Trigger’s broom 17 A B C D time space Head Handle the identity of ordinary physical objects: they survive the changing of some, but not all their parts simultaneously The Ship of Theseus is the posh version of this. -- 17 of 38 -- Possible Worlds 18 Past Future Actual Possible Possible Desired Time Space -- 18 of 38 -- The 4D whole/part relationship (mereology) • Nothing is a (proper) part of itself. • If B is a part of A, then A is not a part of B (asymmetry). • If B is a part of A and C is a part of B, then C is a part of A (transitivity). • If A has parts (is not atomic – in the original, i.e. not physics, sense of the word) then it has at least two non-overlapping parts (e.g. B and D in Figure 11-1) • If there is a part of E that is not a part of A, then E is not a part of A. • In the sum of overlapping parts like D and F, any overlapping parts only count once. • If a part of F is a part of D then D and F overlap. • For any set of spatio-temporal extents, e.g. {B, D} there exists their mereological sum B+D. • There are versions of mereology (the study of wholes and parts) where spatio-temporal extents are (improper) parts of themselves. I will stay with the more everyday understanding of being a part. A B time space C D E F General Extensional Mereology just works for 4D -- 19 of 38 -- 20 Contents Part 1: Motivations and Notations 1. Introduction 2. Entity Relationship Model Basics 3. Some types and uses of data models 4. Data models and enterprise architecture 5. Some observations on data models and data modeling Part 2: General Principles for Data Models 6. Some General Principles for Conceptual, Integration and enterprise Data Models 7. Applying the principles for attributes 8. General principles for relationships 9. General principles for entity types Part 3: An Ontological Framework for Consistent Data Models 10. Motivation and overview for an ontological framework 11. Spatio-temporal extents 12. Classes 13. Intentionally constructed objects 14. Systems and system components 15. Requirements’ specification 16. Concluding Remarks Part 4: The HQDM Framework Schema 17. HQDM_Framework -- 20 of 38 -- Why are we interested in 4- Dimensionalism? Hint: the reasons are pragmatic as much as theoretical 21 -- 21 of 38 -- The National Digital Twin Programme 22 The National Digital Twin Programme § Is led by the Centre for Digital Built Britain, with the mission of: § delivering an Information Management Framework, enabling secure data sharing and effective information management § enabling the National Digital Twin, an ecosystem of connected digital twins that will deliver better outcomes from our built environment § aligning industry, academia and Government on this agenda. Data for the public good recommendations 2017 -- 22 of 38 -- The Built Environment: A system of systems … 23 Economic infrastructure Social infrastructure Natural environment Built environment … for human flourishing -- 23 of 38 -- The National Digital Twin An ecosystem of connected digital twins 24 -- 24 of 38 -- Top Level Ontology Foundation Data Model Industry Data Models & Reference Data Integration Architecture Process Model based Information Requirements Information Quality Management Core Constructional Ontology The Seven Circles of Information Management 25 -- 25 of 38 -- What is information used for? 26 decisions entertainment design films novels education training commercial decisions standards -- 26 of 38 -- Why bother with Information? 27 Reduced Risk of mistakes Identify Business Opportunities Responsive to change Increased effectiveness Reduced Cost Information Decisions Business supports drive -- 27 of 38 -- Information Quality Consistency Accessibility/ Security Clarity Relevance Cost/Benefit/ Risk Accuracy Timeliness/ Completeness Provenance Definition Values Informs the decision being made The meaning is unambiguous Easily accessible to authorised users, but not to unauthorised users Data is according to the same data model, reference data, and identification scheme. Who created the data, when and where did it came from? All the information being available when decisions need to be taken How close to the truth is the data? Is the cost of data justified by the benefit it gives or risk it reduces in decision taking? Property related to information definition Property related to information value -- 28 of 38 -- Process Based Quality Management System (ISO 9001) 29 Customers Customers Management Responsibility Resource Management Measurement analysis and improvement Information Product Realization Requirements Satisfaction Information Product -- 29 of 38 -- Information Management Landscape 30 Business Processes Organization Governance Strategy & Operating Model Plans, Justification & Risk Mgt Communications Application Portfolio IT Support Knowledge Management Training IM Community !"#$%&'()$" Information Quality Management Process !"#$%&'()$"*+'"',-&-"(*.%'&-/$%0 Policy/ Controls Framework Roles and Responsibilities Management Support Key Performance Indicators Data Quality Standards Development Methodology Architecture Standards Reference Data Security Framework Integration Architecture Foundation Data Model The resources you need to manage information -- 30 of 38 -- The pathway towards an Information Management Framework 31 https://www.cdbb.cam.ac.uk/news/pathway-towards-IMF 1. Foundation Data Model – A high level definition of the structure and meaning of data to enable the consistent sharing of data across Digital Twins and the ecosystems they support. 2. Reference Data Library – the particular set of classes and the properties we will want to use to describe our digital twins 3. Integration Architecture – the protocols that will enable the managed sharing of data -- 31 of 38 -- A National Digital Twin enabled by the IMF 32 -- 32 of 38 -- Thin Slice Digital Twins Shared Reference Data New Reference Data Common Reference Data What a thin slice looks like 33 Foundation Data Model Not to scale Ø Thin slices can be aggregated and compared. Ø Shared Reference Data means Digital Twins from different thin slices can be combined. -- 33 of 38 -- Approach to the FDM 34 -- 34 of 38 -- Pragmatic Requirements • Rooted in science and engineering • Extensible • Stable • Capable of consistent extension by different teams Ontological consequence • Principled and rigorous • Ontological and • Highly Committed • Rooted in science and engineering – i.e. rooted in reality • Foundational • Comprehensive scope • Categorical • As simple as possible but no simpler • Generative - some elements automatically inferred • Non-stratified – choosing not to divide entities where this is an option Requirements for a Top Level Ontology 35 -- 35 of 38 -- An Euler diagram of Top-Level Ontologies 36 BFO BORO IDEAS HQDM ISO 15926-2 YAMATO DOLCE UFO GFO Ontological (vs generic) Foundational (vs linguistic) Categorical Some formal generation No stratification Highly Committed SUMO KKO SENSUS FrameNet PrOton Wordnet UMLS CONML+CHA RM CIDOC Marine TLO COSMO EMMO IEC 62541 IEC 63088 ISO 12006-3 SKOS MIMOSA CCOM CIM DC Schema.org TMRM UML FIBO gist OWL UMBEL Cyc -- 36 of 38 -- Information Quality 37 customer supplier information requirements Quality is meeting agreed requirements -- 37 of 38 -- Questions? 38 -- 38 of 38 --