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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-n1trd52t.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-n1trd52t.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-n1trd52t.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-n1trd52t.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-n1trd52t.nxe :where(ul,ol){padding-left:20px}#nxe-n1trd52t.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-n1trd52t.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-n1trd52t.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-n1trd52t.nxe svg{display:none}#nxe-n1trd52t.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-n1trd52t.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n1trd52t.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=\"console\" 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 reproducible-modelling<\/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\">Reproducible modelling<\/h1><p class=\"nx-tagline\">A model result should be reproducible: others should be able to rerun the model with the same code, data and settings and get the same result, and inspect every step. Many published models cannot be rerun because code, data or environments are missing. This page sets out how reproducible modelling is practised, how it is checked, and what evidence serves the modellers, publishers and institutions who depend on it.<\/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\">3<\/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>Hazards and exposure in North America<\/a><a href=\"#nx-sec-question\"><span>03<\/span>Reproducible modelling: how the risk\u2026<\/a><a href=\"#nx-sec-terms\"><span>04<\/span>Terms used on this page<\/a><a href=\"#nx-sec-indicators\"><span>05<\/span>What is measured, and how well<\/a><a href=\"#nx-sec-pipeline\"><span>06<\/span>From sources to decisions<\/a><a href=\"#nx-sec-sources\"><span>07<\/span>Where the evidence comes from<\/a><a href=\"#nx-sec-decisions\"><span>08<\/span>Who decides, and what the evidence\u2026<\/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\">Reproducible modelling is the practice of making model results rerunnable and inspectable by others, using the same code, data and settings. It depends on archived code and inputs with identifiers, recorded software environments, workflows that record every step and versioning that lets corrections be traced.<\/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\">Hazards and exposure in North America.<\/h2><p class=\"nx-lede\">For reproducible modelling, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, land cover and night lights with relief in 3D, 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:risk\" data-ml-src=\"risk\" data-ml-plan=\"p-ea62eddf\" data-ml-relief=\"1.3\"><div class=\"nx-wm\" data-nx-water=\"ctx-risk\" data-wm-domain=\"ctx-risk\" 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=\"Hazards and exposure, 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=\"true||||\" aria-pressed=\"false\">True colour<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"cover||||\" aria-pressed=\"false\">Land cover<\/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=\"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\">Hazards and exposure, for this page<\/p><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"true\" aria-pressed=\"true\" data-wm-z=\"20\" 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=\"cover\" aria-pressed=\"true\" data-wm-z=\"21\" 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=\"ntl\" aria-pressed=\"true\" data-wm-z=\"22\" 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=\"people\" aria-pressed=\"false\" data-wm-z=\"23\" 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=\"flood\" aria-pressed=\"false\" data-wm-z=\"24\" data-wm-lag=\"0\" data-wm-short=\"Flood water\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite detection; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Flood water, 3-day composite<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS Global Flood Product \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"flood\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"imerg\" aria-pressed=\"false\" data-wm-z=\"25\" data-wm-lag=\"0\" data-wm-short=\"Precipitation\" data-wm-prov=\"NASA GES DISC\" data-wm-kind=\"Satellite estimate, near real time\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Precipitation rate, daily mean<\/span><span class=\"nx-wm-layer-src\">NASA GES DISC GPM IMERG \u00b7 <span data-wm-date=\"imerg\">12 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"imerg\" 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 reproducible modelling, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, land cover and night lights with relief in 3D, 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 NASA EONET \u00b7 GDACS \u00b7 Copernicus Sentinel-2 L2A<\/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.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=\"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.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=\"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.gpm.imerg\">GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); 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>Live: NASA EONET Events are indicative, not official warnings.<\/li><li>Live: GDACS (EC JRC \/ UN OCHA) Events are indicative, not official warnings.<\/li><li>Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer<\/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>True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/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>Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC \u00b7 <span data-wm-date=\"ntl\">12 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>Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/li><li>Precipitation rate, daily mean: GPM IMERG, NASA GES DISC \u00b7 <span data-wm-date=\"imerg\">12 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\/reproducible-modelling\/#map\" data-nxf-title=\"Systems Science and Modelling live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-question\" class=\"nx-section\" data-hue=\"project\" data-variant=\"split\" 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\">The question<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Reproducible modelling: how the risk develops.<\/h2><p class=\"nx-lede\">Versioned models, data lineage and re-runnable results. 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=\"m16 6 4 14\"\/><path d=\"M12 6v14\"\/><path d=\"M8 8v12\"\/><path d=\"M4 4v16\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Code and data must be available<\/h3><p class=\"nx-p nx-mt-1\">Without the exact code and inputs, a result cannot be checked. Archiving them with identifiers makes reruns possible.<\/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\"><path d=\"m12.83 2.18a2 2 0 0 0-1.66 0L2.6 6.08a1 1 0 0 0 0 1.83l8.58 3.91a2 2 0 0 0 1.66 0l8.58-3.9a1 1 0 0 0 0-1.83Z\"\/><path d=\"m22 17.65-9.17 4.16a2 2 0 0 1-1.66 0L2 17.65\"\/><path d=\"m22 12.65-9.17 4.16a2 2 0 0 1-1.66 0L2 12.65\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Environments decay<\/h3><p class=\"nx-p nx-mt-1\">Software dependencies change over time. Recording environments with containers or lock files keeps models runnable for longer.<\/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\">Workflows record steps<\/h3><p class=\"nx-p nx-mt-1\">Workflow tools record every step from raw data to final figures, removing undocumented manual steps from the chain.<\/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\"><path d=\"M21 12a9 9 0 0 0-9-9 9.75 9.75 0 0 0-6.74 2.74L3 8\"\/><path d=\"M3 3v5h5\"\/><path d=\"M3 12a9 9 0 0 0 9 9 9.75 9.75 0 0 0 6.74-2.74L21 16\"\/><path d=\"M16 16h5v5\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Versioning supports correction<\/h3><p class=\"nx-p nx-mt-1\">When errors are found, versioned models and data let corrections be traced and affected results updated.<\/p><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"split\" 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\">Key terms<\/span><\/div><h2 id=\"nx-s-5\" 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\">Computational reproducibility<\/td><td data-label=\"Definition\">Obtaining the same results by rerunning the same code on the same data in the same environment.<\/td><\/tr><tr><td data-label=\"Term\">Lock file<\/td><td data-label=\"Definition\">A file recording the exact versions of software dependencies used.<\/td><\/tr><tr><td data-label=\"Term\">Research software<\/td><td data-label=\"Definition\">Software created for or used in research, such as models and analysis code.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-indicators\" class=\"nx-section\" data-hue=\"project\" 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\">Indicators<\/span><\/div><h2 id=\"nx-s-6\" 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\" data-lv=\"register\"><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\">Models with archived code<\/td><td data-label=\"Unit\">percent of published models<\/td><td data-label=\"Cadence\">per review<\/td><td data-label=\"Source type\">Code archive checks<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Successful independent reruns<\/td><td data-label=\"Unit\">percent of attempted reruns<\/td><td data-label=\"Cadence\">per audit<\/td><td data-label=\"Source type\">Reproduction studies<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Models with recorded environments<\/td><td data-label=\"Unit\">percent<\/td><td data-label=\"Cadence\">per review<\/td><td data-label=\"Source type\">Repository checks<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Software with persistent identifiers<\/td><td data-label=\"Unit\">count<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Archive records<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Corrections issued<\/td><td data-label=\"Unit\">count with reason<\/td><td data-label=\"Cadence\">continuous<\/td><td data-label=\"Source type\">Correction logs<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Models meeting FAIR4RS criteria<\/td><td data-label=\"Unit\">percent<\/td><td data-label=\"Cadence\">per assessment<\/td><td data-label=\"Source type\">FAIR assessment<\/td><td data-label=\"Label\"><span class=\"nx-chip\">ESTIMATED<\/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\/reproducible-modelling\/#indicators\" data-nxf-title=\"Indicators\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-pipeline\" 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\">Canvas<\/span><\/div><h2 id=\"nx-s-7\" 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 Reproducible modelling 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-reproducible-modelling-build-t nx-dag-g-p19-topics-reproducible-modelling-build-d\" data-nx-z=\"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\"><title id=\"nx-dag-g-p19-topics-reproducible-modelling-build-t\">Reproducible modelling: build, test and release in Nexus Foundry<\/title><desc id=\"nx-dag-g-p19-topics-reproducible-modelling-build-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=\"project\" data-variant=\"split\" 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\">Sources<\/span><\/div><h2 id=\"nx-s-8\" 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\" data-lv=\"register\"><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\">Software Heritage archive<\/td><td data-label=\"What it gives\">Archived source code with identifiers<\/td><td data-label=\"Licence class\">Open, archive terms<\/td><\/tr><tr><td data-label=\"Source\">Zenodo and institutional repositories<\/td><td data-label=\"What it gives\">Deposited models and data with DOIs<\/td><td data-label=\"Licence class\">Open, licence per record<\/td><\/tr><tr><td data-label=\"Source\">FAIR principles for research software (FAIR4RS)<\/td><td data-label=\"What it gives\">Principles for reusable research software<\/td><td data-label=\"Licence class\">Open, CC BY 4.0<\/td><\/tr><tr><td data-label=\"Source\">CoMSES Net and model archives<\/td><td data-label=\"What it gives\">Archived models with documentation<\/td><td data-label=\"Licence class\">Open, licence per model<\/td><\/tr><tr><td data-label=\"Source\">Reproducibility studies in computational science<\/td><td data-label=\"What it gives\">Measured reproduction rates<\/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\/reproducible-modelling\/#evidence\" data-nxf-title=\"Sources\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-decisions\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"split\" 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\">Decisions<\/span><\/div><h2 id=\"nx-s-9\" 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\"><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\">Modelling teams<\/td><td data-label=\"The question\">How to package models so others can rerun them<\/td><td data-label=\"Evidence this page serves\">Checklists; archiving guides<\/td><\/tr><tr><td data-label=\"Who decides\">Publishers and report editors<\/td><td data-label=\"The question\">What reproducibility evidence to require<\/td><td data-label=\"Evidence this page serves\">Rerun audits<\/td><\/tr><tr><td data-label=\"Who decides\">Funders<\/td><td data-label=\"The question\">Whether to fund archiving and research software engineering<\/td><td data-label=\"Evidence this page serves\">Reproduction rate evidence<\/td><\/tr><\/tbody><\/table><\/div><h3 class=\"nx-h4 nx-mt-4\">Outputs this topic produces<\/h3><ul class=\"nx-list\"><li>Reproducibility checklists for models<\/li><li>Model archiving and versioning guides<\/li><li>Rerun audits of published model results<\/li><li>Open teaching material on reproducible modelling<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-core-questions\" class=\"nx-section\" data-hue=\"project\" 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\">Core questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">What experts ask about reproducibility.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\"><li>Is the exact model version used for a result recorded and retrievable?<\/li><li>Can the input data be traced back to their sources, with every processing step?<\/li><li>Are software environments, random seeds and hardware differences documented?<\/li><li>Can an independent team re-run the analysis without the original authors?<\/li><li>How are errors found after publication corrected and communicated?<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-mechanisms-and-drivers\" 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\">Mechanisms and drivers<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">Why modelling results fail to reproduce.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\">Models change constantly as code is fixed and improved. Without version control, it may be impossible to know which version produced a published result. Input data are revised, cleaned and transformed through steps that are often undocumented. Software libraries change behaviour between versions, and stochastic models depend on random seeds.<\/p><p class=\"nx-p\">Coupled models multiply these problems, since each component has its own versions, data and settings. A result may depend on a particular combination that is never recorded.<\/p><p class=\"nx-p\">Incentives play a role: documenting and sharing models takes time that is rarely rewarded. But irreproducible results cannot be verified, and errors in widely used models can spread into many decisions.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods-and-data\" class=\"nx-section\" data-hue=\"project\" data-variant=\"split\" 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\">Methods and data<\/span><\/div><h2 id=\"nx-s-12\" class=\"nx-section-title\">Practices 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\">Version control<\/h3><p class=\"nx-p nx-mt-1\">Recording every change to code and configuration. It requires discipline and shared conventions.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Data lineage<\/h3><p class=\"nx-p nx-mt-1\">Documenting sources and processing steps for every input, using <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/probability-statistics\/\">statistical<\/a> and data stewardship practice. Some data cannot be shared.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Computational environments<\/h3><p class=\"nx-p nx-mt-1\">Capturing software dependencies so models can be re-run. Long-term preservation remains difficult.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">Independent re-runs<\/h3><p class=\"nx-p nx-mt-1\">Having another team reproduce key results before publication. Costly but highly effective.<\/p><\/div><\/li><\/ol><p class=\"nx-note nx-mt-3\">Reproducibility does not make a model right; it makes it checkable. Replication with independent models and data is a further step, covered in <a class=\"nx-link\" href=\"https:\/\/therisk.global\/systems-modelling\/topics\/model-intercomparison\/\">model intercomparison<\/a>.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" 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<\/span><\/div><h2 id=\"nx-s-13\" 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\/computing\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/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\/systems-engineering\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/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\/probability-statistics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Probability and statistics<\/span><span class=\"nx-mledger-role\">Bayesian calibration \u00b7 Proper scoring of predictions \u00b7 Ensemble statistics<\/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\/probability-statistics\/\" aria-label=\"Probability and statistics: 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\">Reproducing a model run shows consistency, not correctness. Some data cannot be shared, which limits reruns. Environments decay even when recorded. Large models are costly to rerun, so full reproduction is sometimes impractical. Systems Science and Modelling audits methods only; modelling teams and publishers decide.<\/p><\/aside><\/div><\/div><\/div><\/section><section id=\"nx-s-14-sec\" 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\">Questions<\/span><\/div><h2 id=\"nx-s-14\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What is computational reproducibility?<\/summary><div class=\"nx-answer\">The ability to obtain the same results by rerunning the same code on the same data in the same computational environment.<\/div><\/details><details><summary>Why archive model code?<\/summary><div class=\"nx-answer\">Because without the exact code, others cannot check how results were produced, and errors cannot be found or corrected.<\/div><\/details><details><summary>What are the FAIR4RS principles?<\/summary><div class=\"nx-answer\">Principles adapting FAIR to research software, so that software is findable, accessible, interoperable and reusable.<\/div><\/details><details><summary>Is open-source code required?<\/summary><div class=\"nx-answer\">Open code helps reproducibility but is not always possible. Where code cannot be shared, independent re-runs and detailed documentation are designed to compensate.<\/div><\/details><details><summary>What is data lineage?<\/summary><div class=\"nx-answer\">A record of where each input came from and every step applied to it, so that it can be traced and re-created.<\/div><\/details><details><summary>Does reproducibility mean the model is correct?<\/summary><div class=\"nx-answer\">No. It means the result can be checked. Correctness requires validation and comparison.<\/div><\/details><details><summary>How are errors corrected?<\/summary><div class=\"nx-answer\">Through dated corrections linked to the original result, reported via the platform's <a class=\"nx-link\" href=\"https:\/\/therisk.global\/systems-modelling\/trust\/\">trust page<\/a>.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-15\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-15\" 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-16\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Systems Science and Modelling<\/span><h2 id=\"nx-close-16\" 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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