Interoperability, Digitalisation, Innovation, Form 4DSiG, 6 th March 2025 Chris Partridge (BORO Solutions and University of Westminster) 2 Form (noun): the shape and structure of something as distinguished from its material https://www.merriam-webster.com/dictionary/form form (n.) c. 1200, forme , fourme , "semblance, image, likeness," from Old French forme , fourme , "physical form, appearance; pleasing looks; shape, image; way, manner" (12c.), from Latin forma "form, contour, figure, shape; appearance, looks; a fine form, beauty; an outline, a model, pattern, design; sort, kind condition," a word of unknown origin. One theory holds that it is from or cognate with Greek morphe "form, beauty, outward appearance". From c. 1300 as "physical shape (of something), contour, outline," of a person, "shape of the body;" also "appearance, likeness;" also "the imprint of an object." From c. 1300 as "correct or appropriate way of doing something; established procedure; traditional usage; formal etiquette." Mid-14c. as "instrument for shaping; a mould;" late 14c. as "way in which something is done," also "pattern of a manufactured object." Used widely from late 14c. in theology and Platonic philosophy with senses "archetype of a thing or class; Platonic essence of a thing; the formative principle." From c. 1300 in law, "a legal agreement; terms of agreement," later "a legal document" (mid-14c.). Meaning "a document with blanks to be filled in" is from 1855. From 1590s as "systematic or orderly arrangement;" from 1610s as "mere ceremony." From 1550s as "a class or rank at school" (from sense "a fixed course of study," late 14c.). Form-fitting (adj.) in reference to clothing is from 1893. https://www.etymonline.com/word/form Structure (Form?) BORO situation: setting up the strategic question Framing – then leveraging – the challenge a human information evolution perspective: a narrow framework a biological information evolution perspective: a wider framework a digital information transmission perspective: v isualising interoperability an information evolution population analysis Innovation innovation and diffusion (adoption): a frame for human information evolution post-digitalisation – evolved-digital Adding form explicitly to the framing some of our form challenges Summary 3 BORO situation Setting up the strategic question Strategic question: where do we go from here? Initial question: where are we now? there are multiple ways to characterise this we look at some in this section we pick one as our starting point – information transmission What is a sensible way forward – from here? obvious questions is there a clear way forward? if not, how do we find one? topic of subsequent sections How have we presented the BORO work? 5 One view: two mutually supporting frameworks The two frameworks validate and inform each other the bCLEARer frames the process BORO FO – top-down framework bCLEARer – bottom-up framework 6 Another view: route to using a top ontology data collect collect collect increasing semantic maturity reuse reuse foundational ontology bCLEARer process leading to a foundational ontology 7 Another view: ontology exploitation routes 8 transform assess build has the application already been deployed? is there a commercial application available in the market? has it already been selected? standard needs to be implemented in application? sustain target requires a standard? requirement semantics composition mereology classification external identifiers content standardise configure Another view: information transformation 9 Classic example is data migration at the start: one, or more, source systems are operational with data other target system(s) are waiting to become operational: they have no data after the (large scale, asynchronous) information transmission the source system(s) are no longer operational the target system(s) is operational using the source systems’ data Information transformation is at the heart of all the previous views bCLEARer time time interoperability is a major barrier source system(s) target system(s) The ‘R’ in bCLEARer stands for Reuse style.visibility intra -operability inter -operability A Coasian test for the level 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 10 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 4d (over time) schematic transmission example: two stage integration time fill colour = data object shape = schema/structure data migration Broadly generalise this application of bCLEARer to data migration Data migration is the process of extracting and transforming data permanently from one or more computer systems and transferring it to another. aligning data to a new system aligning data from two systems 11 Also, introduce a schematic way of visualising the process 4d view of transmission practice: series of migrations 12 system 1 system 2 system 4 system 6 system 3 system 5 system 7 time … … fill colour = data object shape = schema/structure interoperability issues data migration Data (not-Quite-) Weismannism : ( August Friedrich Leopold Weismann 1834-1914 ) the data germline is preserved the schema soma is not ‘not-quite’ as data acquired during the lifetime of the system is inherited (Lamarckism) In this scheme, data is potentially immortal (a typical Weismannian claim) whereas schema is not so long as the transmission is high fidelity (a topic we return to) otherwise, (in other words, too little interoperability), an ‘error catastrophe’ occurs Note: biological inheritance is not exactly like this Situation - recap There are multiple ways to view the current BORO situation We have elected to start with one that focuses on bCLEARer as information transmission, and interoperability – or the lack thereof – occurring in the transmission 13 Framing – then leveraging – the challenge Framing – then leveraging – the challenge We return to the wider question: what is a sensible way forward? obvious questions is there a clear way forward? if not, how do we find one? We reckon there is no clear way forward so, we need to find one we propose to do this using framing Framing I Idea expounded in many disciplines in the 1990s systems thinking, design thinking and professional practice goes by different names (setting, framing and identification) in different disciplines Can be seen as a kind of re-hash of Kuhn’s view of scientific revolutions Kuhn, T. S. (1970). The structure of scientific revolutions) Haufe , C. (2024). Fruitfulness: Science, metaphor and the puzzle of promise Camp, E. (2019). Perspectives and Frames in Pursuit of Ultimate Understanding. In S. R. Grimm (Ed.), Varieties of Understanding References D. A. Schön, The Reflective Practitioner. Routledge, 2017 T. Kelley and J. Littman, The art of innovation: lessons in creativity from IDEO, America’s leading design firm. 2004 P. M. Senge, The Fifth Discipline: The Art and Practice of the Learning Organization, 1st ed. New York: Doubleday/Currency, 1990 16 Framing II All the disciplines recognised this strategic perspective firstly, making the distinction between framing and problem solving where framing involves developing an understanding of the underlying causes and interconnections of a situation typically within a complex system when this is done, this directs the problem solving which involves developing interventions that address the identified root causes the reframing often reveals a new, different set of challenges to solve secondly, recognising that for foundational issues, getting the right frame can have a much bigger impact on improvements than improving the quality of pre-existing problem-solving processes thirdly, the need to find and exploit leverage points —places within a system where a small change can lead to significant, long-term improvements 17 Visualising reframing: Rubin vase example Kuhn (1970) noticed that the radical change driving scientific revolutions was often not the result of new data but often involved seeing existing data in a new way (a re-framing) He compared this with the way we can see the same image in two radically different ways we make the radical differences explicit using a conceptual model Radical change involves a radical reseeing – a radical reframing The (meta-)problem IRL is finding the fruitful reframing same image different interpretation 18 A fruitful reframing is ‘surprising’ Isaac Newton’s Principia (1687) is an example of a radical reframing where Newton’s choice of reframing is regarded as the work of a genius D r Arbuthnott told me that he being in France in 1699, the Marquis de l'Hospital hearing he understood Mathematicks sent to him & said none of the English could explain to him the problem of what curve would find the least resistance in a fluid – the Dr shewed him that problem in a scholium of Sr I. N.s Principia wch the Marquis had overlooked – he cried out with admiration Good god What a fund of knowledge there is in that book? he then asked the Dr every particular about Sr I. even to the colour of his hair said does he eat & drink & sleep is he like other men? & was surprized when the Dr told him he conversed chearfully with his friends assumed nothing & put himself upon a level with all mankind – Keynes MS. 130.05, King’s College, Cambridge, UK, www.newtonproject.ox.ac.uk/view/texts/diplomatic/THEM00168. Quoted in Westfall (1980), 473. Westfall, Richard S. 1980. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press. 19 Chlorine isotope reframing example 20 In the 19th century, analytical chemists worked hard to determine atomic weights. Every element was measured to at least three places of decimals. Then around 1920 new physics made it clear that naturally occurring elements are mixtures of isotopes. In many practical affairs it is still useful to know that earthly chlorine has atomic weight 35.453. But this is a largely fortuitous fact about our planet. The deep fact is that chlorine has two stable isotopes, 35 and 37. These isotopes are mixed here on earth in the ratios 75.53% and 24.47%. The 19th century analytical chemists framed their weighing on the assumption that atoms were indivisible – like billiard balls. The new physics reframed this assumption with atoms built of components – like a solar system. Hacking, I. (1983). Representing and intervening. Partridge, C. (1996). Business Objects: Re-Engineering for Re-Use The leverage point was found by radiochemist Frederick Soddy, based on studies of radioactive decay. He recognized that emissions could lead to the formation of an element chemically identical to the initial element but with a different mass and with radioactive properties. In 1921, he received the Nobel Prize in Chemistry for his work in this area. Panama canal example Two attempts at building the Panama Canal the first French, the second American The French worked on their project from 1881–1894 based upon their successful Suez Canal project when the French project eventually collapsed, they had spent approximately $287 million and lost an estimated 22,000 workers, but completed only a fraction of the canal The Americans worked on their project from 1904–1914 a key difference in approach was launched an aggressive campaign against mosquito-borne diseases. this included clearing the jungle around the path of the canal they completed the canal with 5,600 deaths One key leverage point turned out to be recognising the role of the mosquito as a disease vector another was the use of locks (so success can depend upon multiple leverage points) 21 Framing - recap We have adopted an approach to finding the way forward - framing For foundational issues, need to (re-)frame the situation finding the new frame can be challenging Use the framing to identify the new problem-solving approaches Find leverage points in the new frame places within a system where a relatively small change can lead to significant, long-term benefits finding the leverage points can be challenging 22 A human information evolution perspective a narrow framework Framing BORO’s situation Methodology: genealogy to critically analyse and deconstruct the historical origins and development of a topic Start the framing by confirming the topic and selecting a history topic: Digital information transmission history: Start with human information evolution will extend in the next section Friedrich Nietzsche. (2006). On the genealogy of morality (K. Ansell-Pearson, Ed.). Foucault, M. (2001). Nietzsche, Genealogy, History. In J. Richardson & B. Leiter (Eds.), Nietzsche (pp. 139–164). Oxford University Press. Dutilh Novaes , C. (2015). Conceptual Genealogy for Analytic Philosophy. In J. A. Bell (Ed.), Beyond the analytic-continental divide: Pluralist philosophy in the twenty-first century 24 media revolution Human information revolution – media (form) 25 digital text speech medium (physical) I dentify three disruptions (external to the brain) key evolutionary events Historically, a s new information media (forms) have emerged, they have cause d disruptive events mid 20 th century mid 15 th century Homo sapiens, emerged around 300,000 years ago human language emerged between 50,000 and 100,000 years ago Broad timescales: media revolution mechanism classification Human information revolution - facet framework storage processing communication brain external location mechanism 26 digital text speech medium (physical) These media can be given a faceted classification. T his minimal set of facets broadly characterises information technology’s evolutionary past through classical major disruptions. It provides a framework for us to see the disruptions Visualising the classifications 27 brain external communication pre-speech speech text digital processing all the components for a digital information ecosystem have emerged: storage, processing and communication? {5C22544A-7EE6-4342-B048-85BDC9FD1C3A} pre-speech speech text digital brain storage YES YES YES YES processing YES YES YES YES communication brain-brain NO YES YES YES brain-external NO NO YES YES external-external NO NO NO YES external processing NO NO NO YES storage NO NO YES YES Visualising the disruptions 28 We map the (recent) information revolution structural disruptions below. legend disruption l atest disruption The other ‘economic’ human information revolutions There are revolutions that are not structural / formal printing is a major one Western Europe – 1440 – moveable type paper a less major one Western Europe – 11 th Century – from the East These had a disruptive economic impact changing the cost of information had massive disruptive effect These are more recent revolutions are useful as they are much better documented than earlier revolutions one thing the historical record shows it that printing had its disruptive effect in Western Europe it had no such effect in China where movable type technology was invented around 1040 (Bi Sheng) revolutions are a co-evolution of technology and cultural practices China did not co-evolve the same cultural practices 29 Looking ahead We have listed three human information revolutions Where there was an evolution in information transmission the last is the digital revolution It is plain that some kind of digital change has happened digital technology has emerged But: has the real digital revolution occurred yet? have the associated cultural practices co-evolved? 30 A human information evolution perspective – recap The genealogical approach shows we can fit the digital information revolution into a wider framework of human information revolutions within human information evolution it is the last of a series of changes in medium we can see this as analogous to biological evolution This reveals the structural novelty of the digital technology it is the emergence of an information transmission ecosystem outside the brain a completely novel machine-to-machine ecosystem this is likely to be the locus of some radical disruption but does the emergence of digital technology, by itself, constitute a digital information revolution? It may be ne cessary , but is it sufficient 31 A biological information evolution perspective a wider framework Information evolution as biological evolution In the last section, we could see human information evolution as analogous to biological evolution Here we review how human information evolution can be positioned as the later stages of biological evolution we see how biological evolution has been presented as information evolution this enables us to position human information evolution as part of its later stages so, we move from analogy to mereology 33 The similarities are commonplace The notion that technology evolution and biological evolution are similar, if not the same kind of thing, is commonplace in the literature i n particular, that they exhibit the same patterns of emergence The next two slides illustrate this with a list of examples from the literature 34 Innovation’s common technical and biological patterns I Many metaphors for the process(es) of innovation are possible. However, in common with authors such as Schumpeter [5], Campbell [6], Nelson & Winter [7], Kauffman [8,9], the authors of a volume edited by Ziman [10] (and see [11]), Rivkin [12,13], Goldberg [14], Olsson & Frey [15], Frenken & Nuvolari [16,17], Khanafiah & Situngkir [18,19], Baldwin et al. [20], Hodgson [21,22], Arthur [23], Fleming & Szigety [24], Valverde et al. [25], Ganco & Hoetker [26], Caminati & Stabile [27], Geisendorf [28], Simonton [29,30], Johnson [31], Vermeij & Leigh [32], Ko ̈ nig et al. [33], Wagner [34], Sole ́ et al. [35] and Gabora [36], we find that an evolutionary metaphor captures all of the necessary hallmarks of innovation in an accessible and accurate manner, and we set it out here. For example, both technologies and scientific discoveries follow evolutionary trends in the form of change, typically improvement, with time. A recent article in this journal [37] develops a similar theme, featuring nine separate hallmarks or commonalities of biological and other evolution, and in some ways, this article might be seen as a complement to it. The ‘now’ is caused by the ‘before’ and also influences what the ‘after’ will look like—these evolutionary stages are intimately connected. In systematic innovation, these progressions are referred to as trends of engineering system evolution (TESE). TESE postulates that all technological systems, from soap to aircraft engines, develop according to the same objective trends. In other words, the evolutionary paths for all different kinds of technologies are actually similar [38]. The ‘laws’ of technical systems evolution were discovered by G.S. Al’tshuller after reviewing thousands of USSR invention authorship certificates and foreign patent abstracts. Al’tshuller studied the way technical systems have been invented and modified over time and developed the theory of inventive problem solving (TRIZ in Russian and TIPS in English) [39–42]. The TRIZ ideas sit very easily with the evolutionary metaphor, because TRIZ implies that most inventions are in fact ‘ recombinations ’ of existing principles, a theme that is a core focus of this article. (Biomimicry provides a similar and related example [43].) We note that evolution comes in various forms, including natural (e.g. cosmological, biological) evolution, directed evolution (a term often used in improving molecules for biotechnology, see below), in computational modelling (e.g. mathematical algorithms known as evolutionary or genetic algorithms [44–46], including in improving software itself [47–49]), in cultural evolution [50] and even in the evolution of (scientific or other) ideas [51,52], in problem solving [53] and in the diffusion of best clinical practice [54]. 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Large literature on this 36 Macroevolutionary perspective In biology, the wider perspective is macroevolutionary Major transitions many of the crucial steps in the last four billion years of evolution – the “major transitions in evolution” – involve the creation of new ways of transmitting information across generations and storing information within a generation – more reliable, more fine-grained, and more powerful ways of making possible the reliable re-creation of form across events of biological reproduction “major transitions in evolution typically involve transitions to new kinds of ways in which information is stored and transmitted, understood as transitions to new kinds of replicating entities” Maynard Smith, John and Eörs Szathmáry , 1995, The Major Transitions in Evolution Evolution evolves through the emergence of new forms of information storage and transmission 37 Szathmáry and Maynard Smith’s major transitions 38 The point of departure for most work on major transitions has been Szathmáry and Maynard Smith’s (1995) list of game-changing alterations in evolutionary history: Replicating molecules to populations of molecules in compartments Unlinked replicators to chromosomes RNA as gene and enzyme to DNA and protein (genetic code) Prokaryotes to eukaryotes Asexual clones to sexual populations Protists to animals, plants, and fungi (cell differentiation) Solitary individuals to colonies (non-reproductive castes) Primate societies to human societies (language) One of Maynard Smith and Szathmáry’s insights is that the very mechanisms of evolution—the way evolution works—have changed over the course of evolutionary history. Maynard Smith, John and Eörs Szathmáry , 1995, The Major Transitions in Evolution From:Turner , Derek and Joyce C. Havstad , "Philosophy of Macroevolution", https://plato.stanford.edu/archives/sum2019/entries/macroevolution/ tl;dr – Szathmáry and Maynard Smith suggest eight major transitions (see below) - this broad view enables us to see that evolution evolves t hat information storage and transmission evolves - their last one is the evolution of language (where our human story starts) Replicators, vehicles, inheritance and fidelity Focus on one pattern of information transmission Dawkins (1976, 1982) introduced replicators and vehicles as a generalisation of the genetic inheritance pattern we can use this to characterise the inheritance aspect of digital ecosystems green shapes are vehicles (storage and process) and blue arrows (communication) replicators. central to replication is its fidelity (interoperability) Poor fidelity/interoperability leads to the breakdown of heredity 39 Dawkins, Richard, 1976, The Selfish Gene Dawkins, Richard, 1982, “Replicators and Vehicles”, in Current Problems in Sociobiology Inheritance fidelity was and is an evolutionary challenge Inheritance, at its core, is all about fidelity of transmission it hinges on passing something down reliably enough to keep it recognizable across generations Inheritance fidelity is about the accuracy with which information is transmitted from one generation to the next without some level of fidelity, there’s no inheritance heritability relies on fidelity Fidelity keeps the system running, but infidelity fuels adaptation the balance needs to be right in genetics, species with higher mutation rates—like RNA viruses—evolve fast but risk “error catastrophe” if fidelity drops too low The replicators in primitive replication systems had high error rates this had to be ‘fixed’ to enable complex life to get off the ground Current digital interoperability looks like it is at a similar ‘infidelity’ stage 40 A biological information evolution perspective – recap We can fit the narrow human information evolution into a wider framework of biological evolution and correspondingly fit the human information revolutions into a wider pattern of biological information revolutions the digital information revolution is then the last in a series of radical changes in information transmission and storage Digital interoperability can then be seen as part of the more general inheritance fidelity high fidelity is needed to support complex systems current digital interoperability/fidelity seems lacking in the respect 41 A digital information transmission perspective v isualising the need for interoperability emerging Original: islands of automation in construction https://en.wikipedia.org/wiki/Islands_of_automation Useful metaphor for automation introduced in the 1980s 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 “Islands of automation was a popular term used largely during the 1980s … the … usage is [now] defunct” 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, 43 Four dimensional 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. 44 As the islands expand ( automation increases), the systems abut – and so, the need to communicate ( data sharing ) arises and increases. Alleyways of digital interoperability 45 When one tries to trace digital interoperability, to map the journey of data shared between systems, it often travels through narrow APIs. Continuing the metaphor: this leads to a cramped structure more akin to alleyways than bridges – alleyways that are not always onward connected. This is an indication that digital interoperability is not as evolved as it should be, that it still has a way to go. 4D communication: vertical and horizontal 46 time key system diachronous migration synchronous exchange (API) Computer system and human evolution has some rough structural similarity. 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. Currently, (vertical) migrations are typically fraught, difficult projects – with significant loss of data. (In other words, they are inefficient, ripe for improvement.) A digital information transmission perspective – recap Digital information transmission occurs between the digital systems i n digital ecosystems increases over time as the ecosystems grow and abut It can be both vertical and horizontal similar to biological information transmission though there are differences It is currently not particularly efficient – or accurate alleyways rather than highways it needs to evolve 47 An information evolution population analysis 48 Information population matters too We have considered the various types/forms of information The (relative and absolute) amount of information matters too Here we examine the populations over time (4D) v arious ways for the populations to change information can be introduced or removed – birth or death it can also be born into one type/form and migrate to other(s) 49 What populations?: media (form) distinctions Distinction analog – data that has not been encoded into a digital format e.g. a paper engineering drawing digital – data that has been encoded into a digital format that can be processed by a computer this encoded data is typically processed by a computer within digital: digitalised – digital data whose content has been sufficiently encoded to be processed by a computer this encoded content is typically processed by a computer e.g. a native data file for an engineering drawing digitised – digital data but not digitalised this content is not encoded in a way that is easy for a computer to process e.g. a file with a scanned engineering drawing All three examples are engineering drawings only the scanned and the native engineering drawings can be stored on a computer system only the native can be processed by engineering drawing software 50 major form digital form Digital evolution – facet framework digital-born analog-born digitised digitalised origin 51 digital analog Within the digital media form, there are finer grained forms These reflect (r)evolutionary steps within digital media current Two migration upgrade pathways 52 analog digitalised-immigrant analog to digital pathway d igitised to digitalised pathway digital digitised digitalised digital-immigrant digital-born data digitalised-born analog digital digitalised digital-immigrant digital-born data Within this framework, there are two clear migration upgrade pathways analog to digital pathway digitised to digitalised pathway For completeness, we show the downgrade pathways. Bi-directionality implies that the pathways form networks. Recurring patterns of revolution Two features that also happened in an earlier information revolution are: a half-way house between the technologies digitised data can be read by a computer but its content is, in a sense, still analog migration to the half-way house analog data is often migrated to digitised – as this is relatively easy e.g. document scanning There was a similar phenomenon in the emergence of printing incunabula – Latin word for "swaddling clothes“ metaphorically referring to the "infancy" of printed books used for books printed before 1501 these were often copies of manuscripts where they were not, they mimicked manuscripts used the old gothic typeface – and had manual illumination added 53 People think more (and more) data is being generated 54 Source: Statista, Bernard Marr & Co. https://explodingtopics.com/blog/data-generated-per-day One view The growth curves are typically increasing rather than linear A Wikipedia view on the shift from analog to digital data 55 https://en.wikipedia.org/wiki/Information_Age#Information_storage_and_Kryder's_law Information population is shifting from analog to digital, Percentage-wise, analog is becoming ‘insignificant’ Digitised but not necessarily digitalised 4d view (over time) analog versus digital 56 Within global data: analog may continue to grow (slowly), but digital grows faster and so swamps it eventually analog becomes relatively insignificant All analog -born data may not migrate to digital maybe never cost justified? time analog digital global data 4d view (over time) pre-digitalised versus digitalised 57 time pre-digitalised digitalised global data Within global data: pre-digitalised may continue to grow (slowly), but digitalised grows faster and so swamps it eventually pre-digitalised becomes relatively insignificant All pre-digitalised-born data may not migrate to digitalised maybe never cost justified? Digitalised data: in the digital ecosystem 58 brain external communication pre-speech speech text digital processing In volume terms, most of the information is in the digital ecosystem, as are most of the information transmissions Volume is a simplistic measure, but this suggests from a perspective of information management, our focus should be on the digital ecosystem. An information evolution population analysis – recap From a population perspective the digitalisation form is increasing over time becoming the largest population by orders of magnitude t his is the space where the digital ecosystem operates the land of machines talking to machines There are opportunities to migrate up the digital evolutionary scale data is not stuck in the format in which it was born what gets migrated when will be constrained by cost considerations pre-digitalisation data is being migrated to the digitalisation level all the pre-digitalisation data may not get migrated, as it will not be cost justified 59 Innovation answering an information evolution question The question Within the context of a series of human information revolutions t he digitalisation (computer) information revolution should classify as a disruptive innovation Has this disruptive innovation happened? Remember if the answer is yes the next question is what (disruptive innovation) happened If the answer is no the next question is when and how will it happen Remember, that information revolutions are meant to be radical and disruptive 61 Two interconnected stages in the innovation process Value creation and value extraction can be seen as interconnected stages in the innovation process initially the innovation needs to be created then the value from the innovation needs to be extracted From a global economic perspective, p rima facie: there needs to be a balance between creation and extraction if there is no creation, then the value becomes exhausted if there is no extraction, then the value is not exploited new disruptive innovations typically bring substantial improvements effectively rendering previous innovations redundant sensible to target creating these new disruptive innovations From a local enterprise level one can adopt strategy of creation or exploitation 62 Business innovation strategy: focus on opportunity There has been a shift in thinking about business strategy historically, there has been a focus on competition now there is an emerging literature suggesting a focus on innovation is better as it creates value by creating opportunity so innovation focuses on opportunities not problems this now has many advocates in the business literature One well-known approach is Blue Ocean Strategy – see next few slides also e.g. Thiel, P., & Masters, B. (2014). Zero to One: Notes on Startups, or How to Build the Future . Crown Publishing Group 63 Blue Ocean Strategy A Blue Ocean Strategy is a business concept it was developed by W. Chan Kim and Renée Mauborgne it’s a framework for creating new market spaces (or "blue oceans") rather than competing in existing, overcrowded markets (referred to as "red oceans"). the core idea is to shift focus from battling competitors to making competition irrelevant by innovating and unlocking untapped demand. Kim, W. C., & Mauborgne, R. (2005). Blue ocean strategy . Harvard Business Review Press. Kim, W. C., & Mauborgne, R. (2017). Blue ocean shift: Beyond competing: proven steps to inspire confidence and seize new growth . 64 Blue Ocean Shift “The Three Key Components of a Successful Blue Ocean Shift The first component is adopting a blue ocean perspective, so that you expand your horizons and shift your understanding of where opportunity resides. Organizations that open up new value-cost frontiers think differently. That is, they think about different things than those that are focused only on competing in their current markets. They raise fundamentally different sets of questions that enable them to see and understand opportunities and risk in fresh and innovative ways. This allows them to conceive of different kinds and degrees of value to offer customers that others either can’t see at all or dismiss as impossible or irrelevant. … Too many organizations are wedded to industry best practices even as they strive to break away from them. Adopting the perspective of a blue ocean strategist opens your mind to what could be, instead of limiting it to what is. It expands your horizons and ensures that you are looking in the right direction. Without expanding and reorienting your perspective, striving to open up a new value-cost frontier is like running west looking for the sunrise. No matter how fast you run, you’re not going to find it.” Kim, W. C., & Mauborgne, R. (2017). Blue ocean shift: Beyond competing: proven steps to inspire confidence and seize new growth . 65 Digital information revolution blue ocean strategy Applying these insights to the digital information revolution the opportunity we are looking for is a new form for digital data let’s call this evolved-digital to create this opportunity, we are thinking differently, expanding and reorienting our perspective raising fundamentally different sets of questions that enable us to see and understand opportunities and risk in fresh and innovative ways conceiving of different kinds and degrees of value not wedded to industry best practices we have found that the information evolution framing enables a new perspective the focus on form, provides a good tool for identifying opportunities 66 Innovation and diffusion (adoption) a frame for human information evolution Innovation adopter categories {5C22544A-7EE6-4342-B048-85BDC9FD1C3A} Category Adopter characteristics Innovators Who want to be the first to try an innovation. Early Adopters Who are comfortable with change and adopting new ideas. Early Majority Who adopt new innovations before the average person. However, evidence is needed that the innovation works before this category will adopt an innovation. Late Majority Who are sceptical of change and will only adopt an innovation after it’s been generally accepted and adopted by the majority of the population. Laggards Who are very traditional and conservative – they are very reluctant to adopt something new. Rogers’ book Diffusion of innovations constructed a framework for analysing the diffusion of innovations. This includes adopter categories that classify individuals within a social system on the basis of their appetite for innovation. Indirectly, this also classifies the nature of the adopters’ relation to the innovation (at that stage) 68 Innovation adoption S-curve Mapping market segment against adoption stages follows an S curve. early majority late majority laggards innovators early adopters 100% 84% 50% 16% 2.5% 0% market uptake adoption stages 16% 13.5% 34% 34% 2.5% Information technology evolution as adoption Can usefully apply this innovation adoption framework to the evolution of information technologies Inevitably a rough guess due to: lack of reliable data methodological issues e.g. what is the market? we assume the human phenotype (in other words, the whole human race) this is obviously a proxy in the case of digitisation and digitalisation as humans are part of a digital ecosystem, rather than being themselves digitalised But, despite this, there are some broad useful points 70 From an evolutionary perspective, speech is now effectively part of the human phenotype. 4d view of speech ‘technology’ diffusion 71 early majority late majority laggards innovators early adopters 100% 84% 50% 16% 2.5% 0% market uptake adoption stages 16% 13.5% 34% 34% 2.5% speech is currently essentially universal, close to 100% of people in every known human society use some form of spoken language it has been part of the human condition for tens (possibly hundreds) of thousands of years current uptake 4d view of text ‘technology’ diffusion 72 From a (cultural) evolutionary perspective, text is now part of the human phenotype. early majority late majority laggards innovators early adopters 100% 84% 50% 16% 2.5% 0% market uptake adoption stages 16% 13.5% 34% 34% 2.5% UNESCO estimates current global adult (15+) literacy rate at around 87% at a rough guess around 20% by the mid-late 19th century at a rough guess under 5% before the invention of printing the earliest known fully developed writing systems emerged in the late 4th millennium BCE (around 3200–3400 BCE) current uptake past uptake From an evolutionary perspective, different media are at different adoption stages. 3d snapshot – ‘now’: human information evolution diffusion early majority late majority laggards innovators early adopters 100% 84% 50% 16% 2.5% 0% market uptake adoption stages 16% 13.5% 34% 34% 2.5% speech text digital current uptake early majority late majority laggards innovators early adopters 100% 84% 50% 16% 2.5% 0% market uptake adoption stages 16% 13.5% 34% 34% 2.5% 3d current snapshot of digital ‘technology’ diffusion The stages of the digital evolution are at different adoption stages. digitisation digitalisation evolved-digital a very rough guess – difficult to factor in the born digital data core processes are automated, with some industries leading and others lagging key question: Has this digital evolution really started? Digital is too recent to have a (long) history current uptake Innovation and diffusion (adoption) – recap Looking at the human information evolution through the lens of innovation diffusion reveals: both speech and text are in the final laggards stage digitised and digitalised data are in the early adopters or early majority stage evolved-digital if it even currently exists, is in the innovators stage If evolved-digital is (or will be) in the innovators stage and it is disruptive then we should expect it to have some of these characteristics: offer novel solutions create new markets significantly reduce costs 75 Post-digitalisation – evolved-digital major form digital form Digital evolution – facet framework evolved-digital born digital-born analog -born digitised digitalised origin 77 digital analog evolved-digital Within the digital media form, roughly speaking, there are three finer grained forms, that reflect (r)evolutionary steps current revolutionary step Updated digital pathways 78 pre-evolved-digital to evolved-digital pathway pre-evolved-digital evolved-digital evolved-digital-immigrant evolved-digital-born data Within this framework, there is one clear migration upgrade pathway pre-evolved-digital to evolved-digital pathway For completeness, we show the downgrade pathway. 4d view (over time) pre-evolved-digital versus evolved-digital 79 pre-evolved-digital evolved-digital global data time Same general pattern: Within global data pre-evolved-digital may continue to grow relatively (slowly), but evolved-digital grows faster and so swamps it eventually pre-evolved-digital becomes relatively insignificant All pre-evolved-digital-born data may not migrate to evolved-digital maybe never cost justified? Post-digitalisation – evolved-digital – recap If things follow the same pattern, then from a population perspective the evolved-digital form will become the largest population by orders of magnitude t his is the space where a new digital ecosystem can operate the new land of machines properly talking to machines there should be opportunities to migrate up to this level in the digital evolutionary scale pre- evolved-digital data should not be stuck in the format in which it was born what gets migrated when will probably be constrained by cost considerations one should be able to migrate pre- evolved-digital data to the evolved-digital level all the pre- evolved-digital data may not get migrated, as it will not be cost justified 80 Adding form explicitly to the framing Add form to the framing Much of evolution framing has been done using form e.g. media is a kind of physical form Here we bring form into the foreground by highlighting the role form can play when formalising process that form has a big role in information transmission evolution that digital is essentially form(al) 82 Form and algorithms In general, developing the right form can help to algorithmicise operations Algorithm = a formal step-by-step procedure for performing a task for manual tasks, devising an algorithm reduces the cognitive resources required for the task 83 Whitehead on form (notation) The interesting point to notice is the admirable illustration which this numeral system affords of the enormous importance of a good notation. By relieving the brain of all unnecessary work, a good notation sets it free to concentrate on more advanced problems, and in effect increases the mental power of the race” […] This example shows that, by the aid of symbolism, we can make transitions in reasoning almost mechanically by the eye , which otherwise would call into play the higher faculties of the brain. … It is a profoundly erroneous truism, repeated by all copy-books and by eminent people when they are making speeches, that we should cultivate the habit of thinking of what we are doing. The precise opposite is the case. Civilization advances by extending the number of important operations which we can perform without thinking about them. Operations of thought are like cavalry charges in a battle — they are strictly limited in number, they require fresh horses, and must only be made at decisive moments. Whitehead, Alfred North (1911). An Introduction to Mathematics. Ch. V: tl;dr – one of the ways civilisations evolve is though notation (form) adaptions - this is because they improve computational efficiency 84 Simple example – evolution of form using writing What is the role of writing in mathematics? If one thinks of a sufficiently tedious problem in arithmetic—say, that of dividing forty-­three thousand eight hundred and seventy-­three by nine hundred seventeen million six hundred eighty-­nine thousand three hundred and eleven—the writing seems essential insofar as, although practically anyone can solve this problem, most (all?) of us can solve it only in the positional system of Arabic numeration. One simply cannot calculate in English, or any other natural language, as one can in Arabic numeration ; and again, for most of us, there is just no other way to solve arithmetical problems of any degree of difficulty. … It can furthermore seem that this is a paradigm case of reasoning in mathematics , that the various systems of written marks that have been devised for mathematics are merely useful devices that simplify the work of mathematics but are in no way essential to it. … Arabic numeration provides a paradigm of a system of written signs within which to work in mathematics. But a calculation in Arabic numeration, because it is algorithmic, is not very interesting as mathematics. Significant mathematics is not algorithmic and often intellectually very challenging. And yet, Jourdain claims, a good mathematical notation can make it accessible even to the less gifted of us. Macbeth, D. 2012. ‘Seeing How It Goes: Paper-and-Pencil Reasoning in Mathematical Practice’. doi : 10.1093/ philmat /nkr006. it is important to realize that the long and strenuous work of the most gifted minds was necessary to provide us with simple and expressive notation which, in nearly all parts of mathematics, enables even the less gifted of us to reproduce theorems which needed the greatest genius to discover. Each improvement in notation seems, to the uninitiated, but a small thing; and yet, in a calculation, the pen sometimes seems to be more intelligent than the user. Philip E. B. Jourdain, The Nature of Mathematics (1912), p. 16 tl;dr – useful forms – though hard to find – once found easily simplify computation - some useful forms depend upon (new) technology - Arabic numerals are a good example – as they require writing (technology) 85 Simple example – Roman versus Arabic numerals 86 To divide, say, twenty-­seven by three, one first writes the number: XXVII. Then one looks for signs that have three or more occurrences. Because in our example none do, we rewrite, putting ‘VV’ for each ‘X’ and ‘IIIII’ for ‘V’: VVVVIIIIIII. Now we can separate out three ‘V’ and three collections of two ‘I’, leaving VI, which we again break down to give IIIIII. Because this latter collection can be divided into three collections of two ‘I’ each, we can see that our original collection can be regarded also as three collections, each VIIII. We have our answer: twenty-­seven divides into three collections of nine. … The system of Arabic numeration is different. It is a positional, and in particular a decimal, system that does not directly picture collections of things (as Roman numeration does) but instead formulates arithmetical content in a mathematically tractable way, in a way that enables calculations in the system of signs. On does not operate on the signs of Arabic numeration in a calculation as above we operated on signs of Roman numeration. Macbeth, D. 2012. ‘Seeing How It Goes: Paper-and-Pencil Reasoning in Mathematical Practice’. doi : 10.1093/ philmat /nkr006. Referring to: D. Schlimm and H. Neth, “ Modeling Ancient and Modern Arithmetical Practices: Addition and Multiplication with Arabic and Roman Numerals” tl;dr – it is not just technology that enables the computational efficiency to emerge - it is the new form adaption as well Formality in information systems Formality is a feature of information systems For example, DNA has some of the features of a formal system with a 4-letter alphabet for its formal language protein synthesis follows formal rules however, DNA operates in a noisy, probabilistic environment which at a practical level reduces the formality Digital computers are far more formal they are at heart formal machines technically they are (finite, physical) Turing machines the physicality leads to practical concerns the battery may run out, or there could be a power surge but these situations are normally kept to a minimum, making them rare 87 Forms in information evolution Under the human information evolutionary perspective new forms are symbolic evolutionary adaptions can “involve the creation of new ways of transmitting information across generations—more reliable, more fine-grained, and more powerful ways” intimately linked to (symbolic) computing can be enabled by new information technology, such as computing their evolution (discovery) is contingent we have agency over their evolution (discovery) 88 Digital ecosystems are (effectively) formal The digital ecosystems – machines talking to machines – are formal in other words, they are constituted by form, they operate algorithmically there is a link between form and functionality functionality typically requires the development of a suitable form for example, there is a link between form and interoperability lack of interoperability is often down to form incompatibility interoperability is often down to form compatibility developing a suitable form is good way to simplify interoperability 89 Adding form explicitly to the framing – recap As Whitehead and Macbeth note, the use of the right form can enable complex operations to be done algorithmically finding the right form is not always easy Form is natural feature of information evolution both biological and human The opportunities for digital revolution are likely to involve form we don’t yet know for sure what opportunities there are to evolve form to support evolved digital but we can guess – and experiment discussed in the next section 90 Some of our form challenges There are a wide range of ‘form’ challenges As new work emerges , as part of seeking a solution we investigate and adopt new ways to frame the situation we attempt to contribute to the way forward to create radical value – and so disruptive opportunities New ‘form’ challenges naturally emerge maybe because we are sensitised to them Here are some we have encountered recently top-level ontology architecture graph foundation type unification data identity/ontology 92 Form of top-level ontology architecture Form is an important part of the top-level ontology architecture building the top-ontology architecture involves choosing forms See: Partridge, C., Mitchell, A., Cook, A., Sullivan, J., & West, M. (2020). A Survey of Top-Level Ontologies – to inform the ontological choices for a Foundation Data Model. 93 Form of graph structures Our work originated from a project to build a graph data interoperability service with a focus on Neo4J and Stardog Initial analysis has revealed that a major barrier to building any kind of framework in the graph data domain is a lack of comprehensive, unified foundations. this situation extends across the whole graph domain