{"id":75,"date":"2026-10-17T11:30:37","date_gmt":"2026-10-17T11:30:37","guid":{"rendered":"https:\/\/therisk.global\/systems-modelling\/?page_id=75"},"modified":"2026-10-17T11:30:37","modified_gmt":"2026-10-17T11:30:37","slug":"digital-twins-method","status":"publish","type":"page","link":"https:\/\/therisk.global\/systems-modelling\/topics\/digital-twins-method\/","title":{"rendered":"Digital twins: method and limits"},"content":{"rendered":"\n<!-- Nexus network page \u00b7 https:\/\/therisk.global\/systems-modelling\/topics\/digital-twins-method\/ \u00b7 source authored \u00b7 generated by integrations\/wordpress\/network\/build.mjs, never edit this file --><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-fig-engine\" 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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-n2oc55e1.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-n2oc55e1.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-n2oc55e1.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-n2oc55e1.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-n2oc55e1.nxe :where(ul,ol){padding-left:20px}#nxe-n2oc55e1.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-n2oc55e1.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-n2oc55e1.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-n2oc55e1.nxe svg{display:none}#nxe-n2oc55e1.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-n2oc55e1.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n2oc55e1.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero\" data-layout=\"dossier\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>G-P19 \u00b7 TOPIC \u00b7 digital-twins-method<\/strong>GCRI dossier \u00b7 service level R0<\/div><div class=\"nx-hero-grid\"><div class=\"nx-hero-text\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">GCRI<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Systems Science and Modelling<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">In development<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Topic dossier \u00b7 Systems Science and Modelling<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Digital twins: method and limits<\/h1><p class=\"nx-tagline\">A digital twin is a model of a real system that is continuously updated with data from it, used to monitor, predict and test decisions. Twins of cities, grids, water networks and factories are widely proposed, and many are dashboards or static models under a new name. This page sets out what makes a digital twin, how twins are built and validated, and what evidence serves the institutions considering them.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/therisk.global\/systems-modelling\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/systems-modelling\/topics\/\">Back to Topics<\/a><\/div><\/div><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Dossier<\/strong><\/span><span class=\"nx-eyebrow\">G-P19 \u00b7 topic<\/span><\/div><ol class=\"nx-register-rows\"><li><a href=\"#nx-sec-brief-answer\"><span class=\"nx-register-n\">01<\/span><span class=\"nx-register-k\">In brief<\/span><span class=\"nx-register-v\">Definition and scope<\/span><\/a><\/li><li><a href=\"#nx-sec-question\"><span class=\"nx-register-n\">02<\/span><span class=\"nx-register-k\">The question<\/span><span class=\"nx-register-v\">4 mechanisms<\/span><\/a><\/li><li><a href=\"#nx-sec-terms\"><span class=\"nx-register-n\">03<\/span><span class=\"nx-register-k\">Key terms<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">3<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-field\"><span class=\"nx-register-n\">04<\/span><span class=\"nx-register-k\">Field<\/span><span class=\"nx-register-v\">H3 field plate<\/span><\/a><\/li><li><a href=\"#nx-sec-indicators\"><span class=\"nx-register-n\">05<\/span><span class=\"nx-register-k\">Indicators<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">6<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-pipeline\"><span class=\"nx-register-n\">06<\/span><span class=\"nx-register-k\">Pipeline<\/span><span class=\"nx-register-v\">Run graph<\/span><\/a><\/li><li><a href=\"#nx-sec-sources\"><span class=\"nx-register-n\">07<\/span><span class=\"nx-register-k\">Sources<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">5<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-decisions\"><span class=\"nx-register-n\">08<\/span><span class=\"nx-register-k\">Decision holders<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">3<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-methods\"><span class=\"nx-register-n\">09<\/span><span class=\"nx-register-k\">Methods<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><\/ol><p class=\"nx-register-foot\">GCRI \u00b7 In development \u00b7 service level R0<\/p><\/div><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-sec-field\"><span>02<\/span>Connected activity in North America<\/a><a href=\"#nx-s-4-sec\"><span>03<\/span>Coupled model runner, in outline<\/a><a href=\"#nx-sec-question\"><span>04<\/span>Digital twins: method and limits:\u2026<\/a><a href=\"#nx-sec-terms\"><span>05<\/span>Terms used on this page<\/a><a href=\"#nx-sec-indicators\"><span>06<\/span>What is measured, and how well<\/a><a href=\"#nx-sec-pipeline\"><span>07<\/span>From sources to decisions<\/a><a href=\"#nx-sec-sources\"><span>08<\/span>Where the evidence comes from<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">In brief<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The short answer.<\/h2><p class=\"nx-lede\">Digital twins are models of real systems that are continuously updated with data from them and used to monitor, predict and test decisions. They depend on reliable data flows, validated underlying models and feedback from decisions, and connecting models to live data raises security and accountability questions.<\/p><\/div><\/div><\/section><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Geography<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Connected activity in North America.<\/h2><p class=\"nx-lede\">For digital twins: method and limits, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with relief in 3D and true colour from NASA GIBS, framed on North America; every other NASA layer, live feed and forecast waits in the layer list.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-cmap-field\" data-nx-map=\"ctx-field\" data-cmap=\"north-america:digital\" data-ml-src=\"digital\" data-ml-plan=\"p-46ee27ab\" data-ml-relief=\"1.3\"><div class=\"nx-wm\" data-nx-water=\"ctx-digital\" data-wm-domain=\"ctx-digital\" data-wm-tiles=\"on\" data-wm-flat=\"on\" data-wm-focus=\"-170,7,-52,72\" data-ws-live=\"off\" data-claim=\"INTEGRATED\" data-wm-panel=\"closed\" data-wm-mode=\"2d\"><div class=\"nx-wm-stage\" tabindex=\"0\" role=\"application\" aria-roledescription=\"interactive map\" aria-label=\"Connected activity, North America: satellite and model layers from NASA on a 3D terrain of ASTER GDEM elevation. Arrow keys move; with Shift they turn and tilt in 3D; plus and minus zoom, 0 resets; I inspects, question mark lists the keys.\" aria-describedby=\"nx-wm-help\"><canvas class=\"nx-wm-canvas\" aria-hidden=\"true\"><\/canvas><p class=\"nx-wm-noscript\">The interactive map needs JavaScript; the layer list and sources are below.<\/p><div class=\"nx-wm-presets\" role=\"group\" aria-label=\"Quick views\"><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"ntl,people||||\" aria-pressed=\"false\">Lights and people<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"ntl||||\" aria-pressed=\"false\">Night lights<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"true||||\" aria-pressed=\"false\">True colour<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"people||||\" aria-pressed=\"false\">Population<\/button><\/div><div class=\"nx-wm-panel\" id=\"nx-wm-panel\" role=\"region\" aria-label=\"Map layers\"><div class=\"nx-wm-panel-head\"><p class=\"nx-wm-panel-title\">Layers <span class=\"nx-wm-count\">3<\/span><\/p><button type=\"button\" class=\"nx-wm-icon nx-wm-panel-close\" data-wm-act=\"panel\" aria-label=\"Close the layer list\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-panel-body\"><div class=\"nx-wm-group\"><p class=\"nx-wm-group-title\">Connected activity, for this page<\/p><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"ntl\" aria-pressed=\"true\" data-wm-z=\"20\" data-wm-lag=\"0\" data-wm-op=\"0.9\" data-wm-short=\"Night lights\" data-wm-prov=\"NASA LAADS DAAC\" data-wm-kind=\"Satellite radiance, corrected for moonlight and atmosphere\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Night-time lights, daily<\/span><span class=\"nx-wm-layer-src\">NASA LAADS DAAC VIIRS Black Marble (VNP46A2) \u00b7 <span data-wm-date=\"ntl\">12 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"ntl\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"true\" aria-pressed=\"true\" data-wm-z=\"21\" data-wm-lag=\"1\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite image\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">True colour<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS NOAA-20 corrected reflectance \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"true\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"people\" aria-pressed=\"true\" data-wm-z=\"22\" data-wm-lag=\"0\" data-wm-op=\"0.8\" data-wm-short=\"Population density\" data-wm-prov=\"NASA SEDAC (CIESIN, Columbia University)\" data-wm-kind=\"Census-based estimate, static (2020)\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Population density, 2020<\/span><span class=\"nx-wm-layer-src\">NASA SEDAC (CIESIN, Columbia University) Gridded Population of the World v4.11 \u00b7 <span data-wm-date=\"people\">static<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"people\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"cover\" aria-pressed=\"false\" data-wm-z=\"23\" data-wm-lag=\"0\" data-wm-time=\"latest\" data-wm-op=\"0.7\" data-wm-short=\"Land cover\" data-wm-prov=\"NASA LP DAAC\" data-wm-kind=\"Satellite classification; latest year GIBS publishes\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Land cover type (IGBP), yearly<\/span><span class=\"nx-wm-layer-src\">NASA LP DAAC MODIS Terra and Aqua land cover (MCD12Q1) \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"cover\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"evi\" aria-pressed=\"false\" data-wm-z=\"24\" data-wm-lag=\"0\" data-wm-op=\"0.85\" data-wm-short=\"Vegetation (EVI)\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite index; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Enhanced vegetation index, rolling 8 days<\/span><span class=\"nx-wm-layer-src\">NASA LANCE MODIS Terra EVI \u00b7 <span data-wm-date=\"evi\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"evi\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"ndvi\" aria-pressed=\"false\" data-wm-z=\"25\" data-wm-lag=\"0\" data-wm-op=\"0.85\" data-wm-short=\"Greenness (NDVI)\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite index; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Vegetation greenness (NDVI), rolling 8 days<\/span><span class=\"nx-wm-layer-src\">NASA LANCE MODIS Terra NDVI \u00b7 <span data-wm-date=\"ndvi\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"ndvi\" hidden><\/div><\/div><\/div><\/div><div class=\"nx-wm-rail\" role=\"toolbar\" aria-orientation=\"vertical\" aria-label=\"Map controls\"><button type=\"button\" class=\"nx-wm-icon nx-wm-open\" data-wm-act=\"panel\" aria-controls=\"nx-wm-panel\" aria-expanded=\"false\" aria-label=\"Layers\" title=\"Layers\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 2.5l-6.5 3.5 6.5 3.5 6.5-3.5zm-6.5 6.5 6.5 3.5 6.5-3.5m-13 2.8 6.5 3.5 6.5-3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"tools\" aria-controls=\"nx-wm-menu\" aria-expanded=\"false\" aria-label=\"Expert tools\" title=\"Expert tools\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 4.5l10 0m-10 3.5 10 0m-10 3.5 10 0m-7.5-8.5 0 3m5 .5 0 3m-3.5.5 0 3\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><span class=\"nx-wm-sep\" aria-hidden=\"true\"><\/span><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"in\" aria-label=\"Zoom in\" title=\"Zoom in\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 3v10M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"out\" aria-label=\"Zoom out\" title=\"Zoom out\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"reset\" aria-label=\"Reset the view\" title=\"Reset the view\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.2 8a4.8 4.8 0 1 0 1.5-3.5M3.2 2.6v2.6h2.6\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"full\" aria-label=\"Full screen\" title=\"Full screen\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M2.5 6l0-3.5 3.5 0m7.5 3.5 0-3.5-3.5 0m-7.5 7.5 0 3.5 3.5 0m7.5-3.5 0 3.5-3.5 0\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-menu\" id=\"nx-wm-menu\" role=\"menu\" aria-label=\"Expert tools\" hidden><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"inspect\">Inspect a point<kbd>I<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"measure\">Measure distance<kbd>M<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"compare\">Compare two dates<kbd>C<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"share\">Copy a link to this view<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"png\">Export as PNG with credits<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"xt\" data-wm-xt=\"6oPh6EhWj+gDMzpLLT8H\/wVfxJakWdyAB8snze2Nado=\">More expert tools<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"keys\">Keyboard shortcuts<kbd>?<\/kbd><\/button><\/div><div class=\"nx-wm-keys\" role=\"dialog\" aria-label=\"Keyboard shortcuts\" hidden><p class=\"nx-wm-keys-title\">Keyboard, with the map focused<\/p><dl class=\"nx-wm-keys-list\"><\/dl><button type=\"button\" class=\"nx-wm-icon nx-wm-keys-close\" data-wm-tool=\"keys\" aria-label=\"Close the shortcuts\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><p class=\"nx-wm-hint\" hidden>Hold Ctrl or \u2318 and scroll to zoom<\/p><p class=\"nx-wm-toolbar\" role=\"status\" hidden><\/p><div class=\"nx-wm-tip\" role=\"tooltip\" hidden><\/div><div class=\"nx-wm-pin\" hidden><div class=\"nx-wm-pin-head\"><p class=\"nx-wm-pin-title\"><\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"unpin\" aria-label=\"Close the card\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-pin-chart\"><\/div><div class=\"nx-wm-pin-body\"><\/div><\/div><div class=\"nx-wm-dock\"><div class=\"nx-wm-time\" role=\"group\" aria-label=\"Imagery date\"><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"prev\" aria-label=\"One day earlier\">\u2039<\/button><p class=\"nx-wm-time-label\">Latest available<\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"next\" aria-label=\"One day later\">\u203a<\/button><span class=\"nx-wm-track\" role=\"slider\" tabindex=\"0\" aria-label=\"Imagery date, up to 30 days back\"><\/span><button type=\"button\" class=\"nx-wm-latest\" data-wm-step=\"latest\" aria-pressed=\"true\">Latest<\/button><\/div><div class=\"nx-wm-chips\" role=\"group\" aria-label=\"Legends\"><\/div><p class=\"nx-wm-attrib\">NASA GIBS \/ EOSDIS \u00b7 ASTER GDEM (METI, NASA) \u00b7 Blue Marble (NASA) \u00b7 \u00a9 OpenStreetMap contributors (ODbL) \u00b7 Natural Earth<\/p><div class=\"nx-wm-legends\" aria-live=\"polite\" hidden><\/div><\/div><\/div><div class=\"nx-container nx-wm-below\"><p class=\"nx-wm-status\" role=\"status\">Loading the latest NASA imagery.<\/p><p id=\"nx-wm-help\" class=\"nx-wm-help\">Drag to move. Ctrl or \u2318 and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.<\/p><p class=\"nx-caption\"><span>For digital twins: method and limits, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with relief in 3D and true colour from NASA GIBS, framed on North America; every other NASA layer, live feed and forecast waits in the layer list.<\/span><span data-honesty=\"true\">Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.<\/span><\/p><details class=\"nx-wm-credits\"><summary><span class=\"nx-wm-credits-line\">Data: NASA GIBS \u00b7 ASTER GDEM \u00b7 Blue Marble \u00b7 \u00a9 OpenStreetMap contributors \u00b7 Natural Earth \u00b7 Copernicus Sentinel-2 L2A \u00b7 NASA HLS S30<\/span><span class=\"nx-wm-credits-more\">Sources and licences<\/span><\/summary><p class=\"nx-wm-credit\"><ul class=\"nx-wm-credit-list\"><li data-wm-credit=\"nasa.gibs.field-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.gibs.water-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.laads.black-marble\">VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.lance.viirs-water\">VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"sedac.gpw-v4\">Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" rel=\"noopener\" target=\"_blank\">CC BY 4.0<\/a><\/li><li data-wm-credit=\"nasa.modis-viirs.land\">MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa-meti.aster-gdem-v3\">ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"naturalearth.all-scales\">Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. <a class=\"nx-link\" href=\"https:\/\/www.naturalearthdata.com\/about\/terms-of-use\/\" rel=\"noopener\" target=\"_blank\">Public domain<\/a><\/li><li data-wm-credit=\"nasa.gibs.reference-osm\">\u00a9 OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.openstreetmap.org\/copyright\" rel=\"noopener\" target=\"_blank\">ODbL<\/a><\/li><li data-wm-credit=\"nasa.earth-observatory.blue-marble\">Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li>Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, \u00a9 OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.<\/li><li>Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, \u00a9 MapLibre contributors.<\/li><li>Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer<\/li><li>Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).<\/li><li>Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.<\/li><\/ul><p class=\"nx-wm-credit\"><strong>Layers and dates<\/strong><\/p><ul class=\"nx-wm-credit-list\"><li>Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC \u00b7 <span data-wm-date=\"ntl\">12 Oct 2026<\/span><\/li><li>True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/li><li>Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 \u00b7 <span data-wm-date=\"people\">static<\/span><\/li><li>Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/li><li>Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE \u00b7 <span data-wm-date=\"evi\">13 Oct 2026<\/span><\/li><li>Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE \u00b7 <span data-wm-date=\"ndvi\">13 Oct 2026<\/span><\/li><\/ul><\/p><\/details><\/div><\/div><div class=\"nx-live-slot nx-live-slot--map\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gcri\/G-P19\/topics\/digital-twins-method\/#map\" data-nxf-title=\"Systems Science and Modelling live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-s-4-sec\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Console<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Coupled model runner, in outline.<\/h2><p class=\"nx-lede\">The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.<\/p><\/div><div class=\"nx-section-body\"><figure class=\"nx-fk nx-cx\" data-fk=\"cx-systems-coupled\" data-cx=\"systems.coupled\" data-variant=\"section\" aria-label=\"Coupled model runner: illustrative console with placeholder names and values\"><div class=\"nx-fk-head\"><div class=\"nx-fk-heading\"><h3 class=\"nx-fk-title\">Coupled model runner<\/h3><p class=\"nx-fk-sub\">Digital twins: method and limits \u00b7 Coupled model A \u00b7 Scenario set 3<\/p><\/div><div class=\"nx-fk-actions\"><button type=\"button\" class=\"nx-fk-btn\" data-fk-act=\"menu\" aria-haspopup=\"true\" aria-expanded=\"false\" hidden><svg viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M12 4v11\"\/><path d=\"m7 10 5 5 5-5\"\/><path d=\"M5 20h14\"\/><\/svg>Export<\/button><ul class=\"nx-fk-menu\" data-fk-menu=\"true\" hidden><li><button type=\"button\" data-fk-act=\"export-png\">Image<small>PNG of the map or chart<\/small><\/button><\/li><li><button type=\"button\" data-fk-act=\"export-csv\">Data<small>CSV of the figure's values<\/small><\/button><\/li><\/ul><\/div><\/div><div class=\"nx-cx-status\"><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>Ensemble running<\/span><span class=\"nx-cx-prod\">GCRI \u00b7 Systems Science and Modelling<\/span><\/div><div class=\"nx-cx-grid\"><div class=\"nx-fk-panel nx-cx-p\" data-w=\"3\" data-t=\"map\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Model coupling graph<\/h4><p class=\"nx-fk-panel-sub\">nodes: models \u00b7 edges: exchanged variables<\/p><\/div><\/div><div class=\"nx-cx-map\"><svg class=\"nx-cx-svg\" viewBox=\"0 0 480 250\" role=\"img\" aria-label=\"Model coupling graph: schematic on placeholder geography. Illustrative.\" focusable=\"false\" data-nx-z=\"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\"><\/svg><\/div><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"3\" data-t=\"table\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Coupled components<\/h4><\/div><\/div><div class=\"nx-fk-tablewrap\" data-fk-view=\"table:cx-systems-coupled-t1\"><table class=\"nx-fk-table\" data-fk-table=\"cx-systems-coupled-t1\" aria-label=\"Coupled components\"><thead><tr><th scope=\"col\" data-col=\"c0\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c0\">Component<\/button><\/th><th scope=\"col\" data-col=\"c1\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c1\">Time step<\/button><\/th><th scope=\"col\" data-col=\"c2\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c2\">Exchanges<\/button><\/th><th scope=\"col\" data-col=\"c3\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c3\">Validated<\/button><\/th><\/tr><\/thead><tbody><tr data-fk-key=\"cx-systems-coupled:r1-0\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Hydrology<\/td><td>1 day<\/td><td>runoff<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Yes<\/span><\/td><\/tr><tr data-fk-key=\"cx-systems-coupled:r1-1\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Power system<\/td><td>1 h<\/td><td>demand, outages<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Yes<\/span><\/td><\/tr><tr data-fk-key=\"cx-systems-coupled:r1-2\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Economy<\/td><td>1 quarter<\/td><td>output, prices<\/td><td><span class=\"nx-fk-pill\" data-state=\"near\"><i aria-hidden=\"true\"><\/i>Partial<\/span><\/td><\/tr><tr data-fk-key=\"cx-systems-coupled:r1-3\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Population<\/td><td>1 year<\/td><td>exposure<\/td><td><span class=\"nx-fk-pill\" data-state=\"met\"><i aria-hidden=\"true\"><\/i>Yes<\/span><\/td><\/tr><\/tbody><\/table><\/div><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"6\" data-t=\"chart\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Ensemble output<\/h4><\/div><\/div><svg class=\"nx-fk-svg\" viewBox=\"0 0 460 210\" width=\"460\" height=\"210\" role=\"img\" aria-label=\"Ensemble output\" focusable=\"false\" tabindex=\"0\" preserveAspectRatio=\"xMidYMid meet\" data-fk-chart=\"cx-systems-coupled-c2\" data-fk-xs=\"lin,0,23,36,446\" data-fk-ys=\"lin,0,100,180,20\" data-fk-series=\"Median|acc|l||0:39.54472440080717;1:45.64217009497806;2:42.025176194962114;3:45.333401115052396;4:47.033849318325515;5:47.60240783886984;6:48.632745725661515;7:50.030519598629326;8:51.268987374752754;9:53.665810230467464;10:55.256125304102895;11:51.80324296755716;12:56.59412862313911;13:57.377835257817054;14:58.85243950206787;15:58.376656899414954;16:58.18561261296272;17:62.204661248251796;18:62.67432043878361;19:61.79267140505836;20:62.4088975504972;21:63.19873356642202;22:65.94164222571999;23:69.66347695784643~Member spread, upper|s3|l||0:45.54472440080717;1:53.842170094978066;2:52.42517619496211;3:57.9334011150524;4:61.83384931832552;5:64.60240783886984;6:67.83274572566151;7:71.43051959862933;8:74.86898737475275;9:79.46581023046747;10:83.2561253041029;11:82.00324296755716;12:88.99412862313912;13:91.97783525781705;14:95.65243950206786;15:97.37665689941495;16:99;17:99;18:99;19:99;20:99;21:99;22:99;23:99~Member spread, lower|s3|l||0:33.54472440080717;1:37.64217009497806;2:32.025176194962114;3:33.333401115052396;4:33.033849318325515;5:31.602407838869837;6:30.632745725661515;7:30.030519598629326;8:29.268987374752754;9:29.665810230467464;10:29.256125304102895;11:23.80324296755716;12:26.594128623139113;13:25.377835257817054;14:24.852439502067867;15:22.376656899414954;16:20.18561261296272;17:22.204661248251796;18:20.67432043878361;19:17.792671405058357;20:16.4088975504972;21:15.198733566422021;22:15.941642225719988;23:17.663476957846427\" data-nx-z=\"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\"><\/svg><\/div><\/div><div class=\"nx-fk-tip\" aria-hidden=\"true\" hidden><\/div><figcaption class=\"nx-fk-cap\"><span>Coupled model runner: the screen's structure, terms and states for Digital twins: method and limits.<\/span><span data-honesty=\"true\">Placeholder names and illustrative values; a design, not a record or a live system.<\/span><\/figcaption><\/figure><\/div><\/div><\/section><section id=\"nx-sec-question\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"inset\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">The question<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Digital twins: method and limits: how the risk develops.<\/h2><p class=\"nx-lede\">What a twin can and cannot represent, and how it is kept honest. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cells\" data-cols=\"2\"><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M4.9 19.1C1 15.2 1 8.8 4.9 4.9\"\/><path d=\"M7.8 16.2c-2.3-2.3-2.3-6.1 0-8.5\"\/><circle cx=\"12\" cy=\"12\" r=\"2\"\/><path d=\"M16.2 7.8c2.3 2.3 2.3 6.1 0 8.5\"\/><path d=\"M19.1 4.9C23 8.8 23 15.1 19.1 19\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Data keep the model current<\/h3><p class=\"nx-p nx-mt-1\">A twin assimilates sensor and operational data so that its state tracks the real system, which needs reliable data flows and quality control.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect width=\"8\" height=\"8\" x=\"3\" y=\"3\" rx=\"2\"\/><path d=\"M7 11v4a2 2 0 0 0 2 2h4\"\/><rect width=\"8\" height=\"8\" x=\"13\" y=\"13\" rx=\"2\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Models must be fit for purpose<\/h3><p class=\"nx-p nx-mt-1\">A twin is only as good as its underlying models. Visualisation without validated models is a dashboard, not a twin.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><circle cx=\"12\" cy=\"12\" r=\"6\"\/><circle cx=\"12\" cy=\"12\" r=\"2\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Decisions close the loop<\/h3><p class=\"nx-p nx-mt-1\">Twins add value when used to test options and inform action, and when outcomes are fed back to improve the model.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect width=\"18\" height=\"11\" x=\"3\" y=\"11\" rx=\"2\" ry=\"2\"\/><path d=\"M7 11V7a5 5 0 0 1 10 0v4\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Integration creates risk<\/h3><p class=\"nx-p nx-mt-1\">Connecting models to live data and to controls raises cybersecurity, data protection and accountability questions.<\/p><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Key terms<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Data assimilation<\/td><td data-label=\"Definition\">Combining model forecasts with observations to estimate a system's current state.<\/td><\/tr><tr><td data-label=\"Term\">State estimation<\/td><td data-label=\"Definition\">Estimating the current values of a system's variables from models and measurements.<\/td><\/tr><tr><td data-label=\"Term\">Physical counterpart<\/td><td data-label=\"Definition\">The real system that a digital twin represents and is synchronised with.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-indicators\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Indicators<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">What is measured, and how well.<\/h2><p class=\"nx-lede\">Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Indicator<\/th><th scope=\"col\">Unit<\/th><th scope=\"col\">Cadence<\/th><th scope=\"col\">Source type<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Indicator\">Data latency from system to twin<\/td><td data-label=\"Unit\">minutes<\/td><td data-label=\"Cadence\">continuous<\/td><td data-label=\"Source type\">Data pipeline monitoring<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">State estimation error<\/td><td data-label=\"Unit\">error metric<\/td><td data-label=\"Cadence\">per evaluation<\/td><td data-label=\"Source type\">Validation against measurements<\/td><td data-label=\"Label\"><span class=\"nx-chip\">ESTIMATED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Decisions informed by the twin<\/td><td data-label=\"Unit\">count<\/td><td data-label=\"Cadence\">per period<\/td><td data-label=\"Source type\">Decision records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Sensor coverage of the system<\/td><td data-label=\"Unit\">percent of key variables measured<\/td><td data-label=\"Cadence\">per assessment<\/td><td data-label=\"Source type\">Sensor inventory<\/td><td data-label=\"Label\"><span class=\"nx-chip\">DECLARED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Model components validated<\/td><td data-label=\"Unit\">percent<\/td><td data-label=\"Cadence\">per assessment<\/td><td data-label=\"Source type\">Validation records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Security assessments completed<\/td><td data-label=\"Unit\">count<\/td><td data-label=\"Cadence\">per assessment<\/td><td data-label=\"Source type\">Security records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">REPORTED<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"indicators\" data-nxf-kind=\"indicator\" data-nxf-resource=\"nexus:\/\/gcri\/G-P19\/topics\/digital-twins-method\/#indicators\" data-nxf-title=\"Indicators\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-pipeline\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Canvas<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">From sources to decisions.<\/h2><p class=\"nx-lede\">The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Pipeline canvas<\/strong> \u00b7 Digital twins: method and limits as a run graph<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-g-p19-topics-digital-twins-method-build-r-t nx-dag-g-p19-topics-digital-twins-method-build-r-d\" data-nx-z=\"zVzNcuM4kn4VBPcyHWvSBAHwJ6LkiGpb0+0Yl91jy93TR1qEJUZRpJqk\/FOnOe55H2JfYe\/7KPMku\/ghCUqiBIp0bR+qDNpiIr8E8mMiM8VPEX0uLj6tw7KkeQriaGKkb2YULsyFuYaBWWbreF6YUbyIyzAxy9c4LcwVLZdZZD5t4iQyczPKysIAr3FULicGdA2wpPFiWYqxlPyYxmUxMTYFzR\/W4ZzepY8FNS4+zeN8nlAwT8KC\/ZnJeo5pEhlg\/jYxfAPM3\/mPfGLYlmecX3w6lxIvPq3C\/CvNT9M5zPPs1QAvMX39MXubGDawgQ\/YRPT5HxPD44PfJwY2gJjmNwHPra5\/lhhdA2R5TNNyYoSbMjOLMsxLM6cvNOcA12G5bODJaaOJ8QWwKW+ADzC44ZN\/4+iE9BHAmUn8Qv+fEMq5NWCei\/2X03nZyJiH6UuobCnHtptNRVxsgPyN6XUub+z+3HOcJBNjkyd\/+beTtvUP9Ry1cuswpYnJBBuAmdUA7\/z\/vUq4NhOQxKmyxZdhnJuFAd4gv+\/NqW56h\/wG8O5UN5b0TZl5laUZ2Jhx+tXhU0Ofz42IAZ6ztDSL+BudGNC2iAHYnWaYzpdZPjH4ihkgocxxzGIdzuN0wRzKxnRlXOSbtADnoHgvSroqzGIe03ROzTCNzFUWUXAOpEloQsOCXe+1W\/jpnM26ba80i6hZhguwMcsn8ymMFpRrT2zPcjgAB9bWCxyFPXyxzqjTEpVok\/1VCCVICkXIatvF3zHLKo6ihO6zC2RmuZo+XP90C+4fbytgi0aD8skAUViGZjgv4yydGN+ybGXGqQHyLKET42lTlllqgDJ8itOIio0S5nFoJuETTcTnQZwaO3t\/Ga85lMD3LCzs0+wuB1sKv7I\/MAvh43slCALLE4bBx7ZLt11slxnm3yt7nC80bJJtyn5GYTd0W4Vgyx\/PKq5nwZGs8q\/\/+E9duzzH+iZhn+22hh1s2wJ5zD6n2MLxrGAkW\/z1eqZri3USvmsbg3+40xo+cdk+aNsDY+ZFJ9jD93y504bb45ebz7+rBukA4JGdrR3YJ25t30YWGkn9m8+\/3z3OwP\/8N7i530\/yizzbCAyO8Cfoo2ZLImJBZREglE9w\/xAMxMUhKS7wWiAC3SccdBiA++nfH6cPs2O6I2JzRd8nhhc0T3TPtojXqI8cR199t5YYoCEIrj7PPh9Tn0BseeOanziNyGFL8OXuanpzDIGPkeW72wuwDaDPAvikljhsAe6nN9PPD9MKQTvopdGCAvGjCn0ZxxUlXbP4RVw959lqYuR\/yMsymxivBT8gLW9ouuBbTcbM0Ass4gEHu+ASOBBVF9BthoEnh1W8btI0OjXWbaJ2HvHuojOfk\/rg0k+7817GIi1jMfvUxmLB1T5jIYwtiKU6yPOrC+TwIcQOQK4jh9\/dWP2062cst9tYL9FJxkLErtRBxP6zGWtLu37G8lvGYpupNtZTh7GI7Vse5Gt0CQh2qgsc8CHTjDiuHH53Y\/XTboix2GbSNRZbo1oddvGnMpamduetmJXy6LOHfbYfcEKA+bTgjyQcBNXBN4BWK3JXMgcQHTv9Sqny4Au96nxn85BR5+R7MU9omKqBafcWSfkRWzFB0DLBk2qCsuOx5nrIcgLp3h47\/4sLlzTDAMrhaFukY3e0wEDYQlOqVLoo96Px2VHLlWh8D1YXvtMMCZHD74vGaaFZlAqaPOkIOWzbsTCScKCN3Ooq8PmQUQu0HVuOxwV02NuO4DnsbkFA5KkQ+p7qblA9WfV0N2hDKLMzMHC1\/W0dFsVhdzvAMi3YXSy8vYykvsKe+4E8\/ENfztxGc3gRPVwdxh0UjLWInourfAH2tdfwOYyTHmvIDi5q+J8osIvORQwQf5r7kC+iuOJx9Z4xYuT1QcvIMqxVojXK0ja0yivZX5WDjczV3NM\/NrSoV\/l9TScGGxa0eY6EJZ0YV3e3U\/mbFZwY2WtKc5Zr4LfHWRWorZyJ8WuYxFHIfgmKTVxW6vADpDKjZjZJfv4MSLXOAIe4N4H9lL2JAz2SGRqvyQ9gt5Uf8Pzt+kRb1JKGka4sx+0pS8mlb8uCToeQeM7MxCITKPPxSBGiCMCKe7W3PZezSN7XSwOUeZgWz1nOnqNsmIQl\/QuGZw5EP4gNjgC2yNw2IXBMaBGA2f8FBmwIoEVeyNwG0HTY2OS\/KUxssjH74LcvCHjsA4B\/QNxSsL8LQbvOX4RpIZICEGzMV5cVW5hRJVwHb5UKIJNyIbdH5euH8wyV6XBwhEY08jwP09mxSZ3WpK5OZuNix7H6IfNcnUm2PfRwTUg8SxG2PE+aT6F2V01kQ9K\/GAQJsqAUTGB7XXqWgu5u68zPdsV6nbH1ZNVqkRcRJWv+bM0nBhL7cSsLfpBWUYtW61O9JK3fsvwrU4+2iLUMi68HWTUuMuaHkUKm4XxOiwI8vXO+HEaltVZngKmiw6QiRTQem2rK02ZUVd4gVnVsUgv6AGYV4lvsipb+i\/8z+qbNhI7TqNjBhvUK67GGCnooJ84+P\/xNjxDVWfVIsfKL\/qj0+LDtZBps6ASBhfAHsCFiGQL8HdlQ+s8eNuy+SSQAq5vsE24izqm8S1q8WycIJcNdp4tTotnrhzvgIAd7Vc8EYME3eM7DFX3N8q8KHyfxnPVdFG0mvgrLUJuGhZL9AlqeTxUnWRuNENTqydMPbBV50BtAw8izG8WC0WlYiD+DdvDnCnJR0MB27L3ULnaNHgOqVsTkO8a66sQk0KHe\/a73r3\/+V3+knqMzYeXAGiyPXWQFsq6K3BFZHvuOVdXMsffxLF+555xP6OgRtkjG772pD2G7LcKuk\/CSC+VJhPJftnh7EZb0IGkX8yVdheyotAjXhULRz0m4GMLPLZ3OAFOkJ0fzZM+IHH1I3ikcjRwyDkejFtmPytEIepKjPeAkBBCT\/zPJt1NYldUm97Fqa617Uw4iaBi5\/vR5Nu3NrMjV6fG4aPtHf2y+rTMLd7Z+XIow\/hguRYR8Xy7l1fe+XLp10wEu7Sz4Ci592uLSH1mOuMWhrDE4aZPo\/ePt7fXtTwqPsg7xOEtbWYd8k4KczrM8avPoFyFQk0i5QmeAa3EG8k2axuniMImKosd4+QZNedokqsoblG8gqO7Z+oh8gxDfyjdAmCCTAAcggExXm0QJaRTtyDrwddYjGBX20IxDq1ntMHuq0+qlHGqv6I9LL+fQuJgGe7p2YPnBTr6BELVt9hT2dJFnkWCMfIMkli4CZSmWtAQbSWpzDsrmoEQawWPLn0vtDzCpdEB+E0vBaNGvepNulqN1E\/GP3QTEDxUfb6Tom2n+Y0M3NRe3mzgE7ZdbuebZdsaDvtF8Hhdb0fPfH6eP0yuF95c0iUTff037xdc4SUBOGRA6iPpnPMNRaXIGJKqD3C+6Ssbjfk152tyvyhvE\/S7rLQo+jPuFeIX7WUvIEv1KlviFLJE283uwUbOD+WfaKQkV81Din\/5jen95\/aAZOasz63F\/5Rn9kelRf9vNNOjf823LdXfoH\/MWtSH079vEctwx6F\/Qy\/HwuXKiXlQsmrj6Mmkrg9DqHxNEWje31J0G4ptzyn1dqQh2blPrdmlE1zSNaFq2UsWruCxAWJbhfLlNp3KyHm0QjXJnyv+HKVW0to1HqZrytClVlTeIUn23\/gbBR1CqEK9Q6sk5Cd9vFO1saWiWWo+CVPRDyVU\/JaHOqlnHa\/ykPzA9bt1yOg1yDYhnuegDanmB51o2GoNc1TU5wJLSmXpRq2xF7FnMa9+lX82j87homsW2+kZlh1qyl5XbNb1tOZyUPz\/Ofr67v579rjAzj1pBUdLXMI\/296iJ5\/Ao7HwGKs3OQLgpl1kel+9HGixEs+54pT1dgfotFqrAQcU9aDt+o9r41T0pXynvOcBbQpux9Qu0tTka2rjRs6McJ1dcj8ZawAcX5KaX1w\/Xd7d6JN2aWq8k1\/KZEwDq1eF2PFCnCc1m0eNOQc71BjehQYdYoxTkahLS6L2oHKtXWQ5C1+tblNuTU6g7ngXrFlu55IcyTCMQZa\/pkQ62nbTCa9WCBOZJVrSzyjzdBb7S9UC6bbSrOtl08gsqkY1SodMVeBLVDqvRqQ75EUW6imqbKt0JDW0qz3YV6Jql7s9Eg8tz+j1trWn16nPbjnICPr0SneJ2OhwLWa55p1A3PNcAWQsxHqNQp5traBHs4bLbKk7jVbg29r5HqDK8OIj4jTMR5auAGCtvfWgLWa32tEhwkYhUX5jhmfz67VzsHR+1YCEX9pHLajYfIddD1be0iBV8hFyEh8sVGXgRLjjVd4dGsEP1FOV7mbPTWJJFgkn4iF29T2iMlavPSVw2Diw02uq1rFFLPnX92AvQKp+QAZ6CHvnqeyWEHKfy4h7v7cKOfHEXG5x3+7ojlgA7ja976gvDoKO+3ezYy0WELOxuPd20H0VYltfA7PrL9Ob6dsp6Ou7+78ePj9c3NQ3umkEYAbJ2Ym4G3lfMrEBcYQWCNfSHnmAo7OJTH6bi\/TR3a5oeUxbZLhPL1JXD\/goj8e6cMVRu91x2KY1RIFTmg\/4KY\/k4H6xuqw7fpS3xYGViOeyvMfHIWCaeaRjYs+UW5oP+6nr2SFu416G\/cvytIK1r0u1vsrW5qczD+Vfpj5KcvIYgCVLfZqiEZltCEvMpzHcfvx627B2ZHrG8\/UL1YAe2pZfo2P3SylHoPk+cjwLewdUr99pSB8InNtQD36aYo8iDsXAjEV9syRyKWkRFOrj3Nl4eg09sYo1vgLbU\/iaALRM4jp4BWmR9FDh0h8GuY2JsQ5noUmUOXXfk6K77rMduZx04A5dbiVLZqxWCPXKHYsdIl993y3pHLYC8YfjrkwUh1VFIldmNvZVJfG2nDquXQ76ZlarV9atUU2YWX03Z+eu42HORTwjEjmtsP+lT\/oYg7pew+ryMqORYPPOd1jO\/DVv0l8l4qm5qwK2C3u47KJxDy2xmaUtspQsTG1iDMhi3d791v2myOYd42N45iOAWjh4HEY84o5xErm8ffplezu7u2THkYXozvZxNr8Dt3VVH2Xg3+cevCrOMy4S2VXO3VHPq9lI2mewg1gu\/apn+yUEfX6q7326n960p+eaO00K+BcNodGCoXsCeSjmx9+rSkbC7pW+bAvw126RR\/s6A\/3R5f90TdRAMQn19+8vj7KEDdpyuN6wLUR93oFV4epExQdTj2xgVYAIHLvPj7ADibFP2hLytTwdk3hsPdnuBNUE7w1Z5+uv11fT2ctqBmr7EEfuuXB\/Yjl6JkbVu30yv2OaWndYFWMepdr91bQE8bNkfb2\/uLv\/WteybNMnmX3stO9ZadiUK+l8=\"><title id=\"nx-dag-g-p19-topics-digital-twins-method-build-r-t\">Digital twins: method and limits: build, test and release in Nexus Foundry<\/title><desc id=\"nx-dag-g-p19-topics-digital-twins-method-build-r-d\">A request opens a workspace; data are ingested and validated; the model is built and tested on held-out data; an independent gate approves release with limits; the workspace is stood down and the record kept. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig. 02<\/strong><span>Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.<\/span><\/p><\/div><\/div><\/section><section id=\"nx-sec-sources\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"inset\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Sources<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Where the evidence comes from.<\/h2><p class=\"nx-lede\">Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Source<\/th><th scope=\"col\">What it gives<\/th><th scope=\"col\">Licence class<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Source\">ISO 23247 digital twin framework<\/td><td data-label=\"What it gives\">Reference architecture for manufacturing digital twins<\/td><td data-label=\"Licence class\">Licensed standard, purchase required<\/td><\/tr><tr><td data-label=\"Source\">Digital Twin Consortium definitions and resources<\/td><td data-label=\"What it gives\">Industry definitions and capability frameworks<\/td><td data-label=\"Licence class\">Public, terms to check<\/td><\/tr><tr><td data-label=\"Source\">National academies reports on digital twins<\/td><td data-label=\"What it gives\">Assessment of foundational research gaps<\/td><td data-label=\"Licence class\">Public, terms per publisher<\/td><\/tr><tr><td data-label=\"Source\">Data assimilation literature<\/td><td data-label=\"What it gives\">Methods for combining models and observations<\/td><td data-label=\"Licence class\">Licence per publication<\/td><\/tr><tr><td data-label=\"Source\">Published city and utility digital twin case studies<\/td><td data-label=\"What it gives\">Applied twins and lessons<\/td><td data-label=\"Licence class\">Licence per publication<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gcri\/G-P19\/topics\/digital-twins-method\/#evidence\" data-nxf-title=\"Sources\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-decisions\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Decisions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Who decides, and what the evidence serves.<\/h2><p class=\"nx-lede\">Systems Science and Modelling prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"ledger\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Who decides<\/th><th scope=\"col\">The question<\/th><th scope=\"col\">Evidence this page serves<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Who decides\">Operators and city authorities<\/td><td data-label=\"The question\">Whether a digital twin is worth building and for which decisions<\/td><td data-label=\"Evidence this page serves\">Capability assessments<\/td><\/tr><tr><td data-label=\"Who decides\">Engineering teams<\/td><td data-label=\"The question\">How to validate and secure a twin<\/td><td data-label=\"Evidence this page serves\">Validation designs; architecture reviews<\/td><\/tr><tr><td data-label=\"Who decides\">Procurement bodies<\/td><td data-label=\"The question\">How to distinguish twins from dashboards in tenders<\/td><td data-label=\"Evidence this page serves\">Capability criteria<\/td><\/tr><\/tbody><\/table><\/div><h3 class=\"nx-h4 nx-mt-4\">Outputs this topic produces<\/h3><ul class=\"nx-list\"><li>Digital twin capability assessments<\/li><li>Validation designs for twin state estimates<\/li><li>Architecture and data flow reviews<\/li><li>Teaching material on twins as a method<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-core-questions\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-11\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Core questions<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">What experts ask about digital twins.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\"><li>What does the twin represent, at what resolution, and what does it leave out?<\/li><li>How often is it updated with data, and how is data quality checked?<\/li><li>How is the twin's accuracy tested, and for which purposes?<\/li><li>How are uncertainties shown to users?<\/li><li>Who is accountable when decisions rely on the twin?<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-mechanisms-and-drivers\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-12\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">11<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Mechanisms and drivers<\/span><\/div><h2 id=\"nx-s-12\" class=\"nx-section-title\">What twins can and cannot do.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\">A twin combines models with live or regularly updated data. Data assimilation adjusts the model state to match observations, which can make short-term predictions more accurate. Twins are useful for monitoring, testing interventions virtually and training operators.<\/p><p class=\"nx-p\">A twin is still a model. It represents only the processes and components that were built into it, at the resolution chosen, and it inherits the uncertainties and assumptions of its components. Visual realism can create an impression of completeness that the underlying model does not justify.<\/p><p class=\"nx-p\">Twins can drift. As the real system changes, through new construction, ageing or changing behaviour, the twin must be updated and revalidated. A twin that is not maintained becomes a misleading picture.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods-and-data\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"inset\" aria-labelledby=\"nx-s-13\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">12<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods and data<\/span><\/div><h2 id=\"nx-s-13\" class=\"nx-section-title\">Methods and their limits.<\/h2><\/div><div class=\"nx-section-body\"><ol class=\"nx-rows\"><li><span class=\"nx-eyebrow nx-index\">01<\/span><div><h3 class=\"nx-h4\">Data assimilation<\/h3><p class=\"nx-p nx-mt-1\">Combining model predictions with observations, using <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/probability-statistics\/\">statistical methods<\/a>. Requires good observation coverage.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Validation for purpose<\/h3><p class=\"nx-p nx-mt-1\">Testing the twin against independent data for each intended use, using <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/uncertainty-quantification\/\">uncertainty quantification<\/a>.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Systems engineering<\/h3><p class=\"nx-p nx-mt-1\">Defining scope, interfaces and requirements, using <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/engineering\/systems-engineering\/\">systems engineering<\/a>.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">Computing infrastructure<\/h3><p class=\"nx-p nx-mt-1\">Running and updating twins, using <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/technology\/computing\/\">computing<\/a>. Costs and security must be managed.<\/p><\/div><\/li><\/ol><p class=\"nx-note nx-mt-3\">A digital twin is a representation, not reality. Its outputs carry the uncertainty of its models and data, and they are shown with that uncertainty.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-14\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">13<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods<\/span><\/div><h2 id=\"nx-s-14\" class=\"nx-section-title\">How it is studied, and what the methods cannot say.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\" data-limits=\"true\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/systems-engineering\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Systems engineering<\/span><span class=\"nx-mledger-role\">Requirements for decision models \u00b7 Interface control for coupled models<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/engineering\/systems-engineering\/\" aria-label=\"Systems engineering: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/computing\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">High-performance, cloud and edge computing<\/span><span class=\"nx-mledger-role\">Ensemble design within budgets \u00b7 Workflow orchestration \u00b7 Reproducible environments<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/technology\/computing\/\" aria-label=\"High-performance, cloud and edge computing: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/uncertainty-quantification\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Uncertainty quantification and model validation<\/span><span class=\"nx-mledger-role\">Uncertainty budgets \u00b7 Surrogate models for expensive simulations \u00b7 Credibility assessment<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/uncertainty-quantification\/\" aria-label=\"Uncertainty quantification and model validation: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/optimization\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Optimization and operations research<\/span><span class=\"nx-mledger-role\">Problem formulation guidance \u00b7 Robust and stochastic comparisons \u00b7 Solver benchmarking<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/optimization\/\" aria-label=\"Optimization and operations research: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><aside class=\"nx-limits\" aria-label=\"What the methods cannot say\"><span class=\"nx-eyebrow\">What the methods cannot say<\/span><p class=\"nx-limits-text\">The term digital twin is used loosely, so claims vary widely. Validation of twins is rarely published. Sensor coverage is often incomplete. Benefits are hard to measure separately from other changes. Systems Science and Modelling builds or endorses no twin; operators decide.<\/p><\/aside><\/div><\/div><\/div><\/section><section id=\"nx-s-15-sec\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-15\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">14<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-15\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What is a digital twin?<\/summary><div class=\"nx-answer\">A virtual representation of a physical system that is updated with data from it and used to monitor, predict and support decisions about the system.<\/div><\/details><details><summary>How is a digital twin different from a simulation?<\/summary><div class=\"nx-answer\">A simulation can run without live data. A twin is continuously synchronised with its real counterpart through data assimilation.<\/div><\/details><details><summary>What is data assimilation?<\/summary><div class=\"nx-answer\">Methods that combine model forecasts with observations to estimate the current state of a system, widely used in weather forecasting.<\/div><\/details><details><summary>Is a 3D city model a digital twin?<\/summary><div class=\"nx-answer\">Not on its own. A twin also needs process models and data updates. Many products called twins are visualisations.<\/div><\/details><details><summary>Can a twin predict the future?<\/summary><div class=\"nx-answer\">It can make short-term predictions for represented processes, with uncertainty. Long-term or unrepresented effects are outside its reach.<\/div><\/details><details><summary>How is a twin kept honest?<\/summary><div class=\"nx-answer\">Through validation for each use, visible uncertainty, documented scope and regular revalidation as the real system changes.<\/div><\/details><details><summary>Does GCRI certify digital twins?<\/summary><div class=\"nx-answer\">No. GCRI does not certify. The topic provides method guidance.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-16\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-16\" class=\"nx-h3 nx-mt-2\">Around Systems Science and Modelling.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/therisk.global\/systems-modelling\/topics\/model-intercomparison\/\">Model intercomparison <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/topics\/uncertainty-and-validation\/\">Uncertainty and validation <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/topics\/coupled-systems-modelling\/\">Coupled systems modelling <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/topics\/networks-and-cascades\/\">Networks and cascades <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/topics\/agent-based-and-complexity\/\">Agent-based and complexity models <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/topics\/optimization-under-uncertainty\/\">Optimization under uncertainty <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/\">Systems Science and Modelling home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/\">The Global Centre for Risk and Innovation home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/trust\/\">GCRI governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-17\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Systems Science and Modelling<\/span><h2 id=\"nx-close-17\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. 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