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"dgtl_infra", "name": "Dgtl Infra News & Deal Radar", "slug": "dgtl-infra", "category": "market", "url": "https://dgtlinfra.com/", "scope": "M&A, debt facilities, land acquisitions, hyperscale leases", "accuracy_score": 85, "freshness_score": 91, "coverage_score": 65, "methodology_score": 75, "granularity_score": 78, "openness_score": 30, "historical_score": 72, "independence_score": 82, "overall_score": 78.4, "strengths": "Financially grounded verification of capital actually spent", "weaknesses": "Focuses primarily on commercial transactions rather than operational telemetry", "last_verified": "2026-10-10" }, { "id": "iea_energy", "name": "IEA Global Energy & Electricity Database", "slug": "iea-energy", "category": "energy", "url": "https://www.iea.org/", "scope": "National grid consumption, data center TWh projections to 2030", "accuracy_score": 95, "freshness_score": 62, "coverage_score": 88, "methodology_score": 94, "granularity_score": 60, "openness_score": 85, "historical_score": 95, "independence_score": 96, "overall_score": 76.1, "strengths": "Government-level authoritative data for macro grid capacity", "weaknesses": "Infrequent annual/semi-annual update cycles", "last_verified": "2026-09-20" }, { "id": "datacenterhawk", "name": "DatacenterHawk Market Analytics", "slug": "datacenterhawk", "category": "pipeline", "url": "https://www.datacenterhawk.com/", "scope": "North American and European absorption, vacancy, and construction", "accuracy_score": 82, "freshness_score": 78, "coverage_score": 71, "methodology_score": 80, "granularity_score": 85, "openness_score": 25, "historical_score": 80, "independence_score": 80, "overall_score": 74.9, "strengths": "Granular North American market vacancy and pricing curves", "weaknesses": "Coverage in emerging markets (Asia/LatAm) remains sparse", "last_verified": "2026-10-01" }, { "id": "idca", "name": "IDCA (International Data Center Authority)", "slug": "idca", "category": "facility", "url": "https://www.idc-a.org/", "scope": "Standardization, facility auditing, regional power readiness", "accuracy_score": 75, "freshness_score": 55, "coverage_score": 82, "methodology_score": 72, "granularity_score": 70, "openness_score": 10, "historical_score": 75, "independence_score": 74, "overall_score": 68.3, "strengths": "Robust framework for digital infrastructure readiness evaluation", "weaknesses": "Heavy paywalls and slow release cadence for primary indices", "last_verified": "2026-08-15" }, { "id": "statista_infra", "name": "Statista Technology Infrastructure Desk", "slug": "statista-infra", "category": "market", "url": "https://www.statista.com/", "scope": "Aggregated facility counts by country, top operator market shares", "accuracy_score": 70, "freshness_score": 65, "coverage_score": 90, "methodology_score": 50, "granularity_score": 40, "openness_score": 20, "historical_score": 75, "independence_score": 78, "overall_score": 62.4, "strengths": "Fast high-level secondary visualizations for broad audiences", "weaknesses": "Secondary aggregator; does not verify conflicting engineering definitions", "last_verified": "2026-09-01" }, { "id": "visual_capitalist", "name": "Visual Capitalist Infrastructure Mapping", "slug": "visual-capitalist", "category": "geographic", "url": "https://www.visualcapitalist.com/", "scope": "Graphic breakdowns of global server footprints and subsea cables", "accuracy_score": 78, "freshness_score": 60, "coverage_score": 70, "methodology_score": 60, "granularity_score": 45, "openness_score": 65, "historical_score": 60, "independence_score": 85, "overall_score": 66.8, "strengths": "Viral distribution and accessible infographics for public comprehension", "weaknesses": "Static snapshots; lacks dynamic timeseries queries or live API", "last_verified": "2026-09-15" }, { "id": "jll_global_outlook", "name": "JLL Global Data Center Outlook", "slug": "jll-outlook", "category": "forecasting", "url": "https://www.us.jll.com/", "scope": "Hyperscale market forecasts, secondary city migration, power procurement", "accuracy_score": 86, "freshness_score": 82, "coverage_score": 85, "methodology_score": 80, "granularity_score": 78, "openness_score": 50, "historical_score": 80, "independence_score": 72, "overall_score": 81, "strengths": "High-quality validation of 103 GW to 200 GW 2030 forecast curves", "weaknesses": "Real estate commercial broker bias on absorption rates", "last_verified": "2026-10-05" }, { "id": "trendforce", "name": "TrendForce Server & AI Power Intelligence", "slug": "trendforce", "category": "forecasting", "url": "https://www.trendforce.com/", "scope": "161 GW 2026 power demand forecasting, server rack unit shipments", "accuracy_score": 92, "freshness_score": 90, "coverage_score": 82, "methodology_score": 86, "granularity_score": 88, "openness_score": 40, "historical_score": 84, "independence_score": 85, "overall_score": 85.9, "strengths": "Supply chain component tracking (GPU server power vs general purpose)", "weaknesses": "Full detailed reports behind paywall", "last_verified": "2026-10-14" }, { "id": "goldman_sachs_infra", "name": "Goldman Sachs US Data Center Power Research", "slug": "goldman-sachs-research", "category": "forecasting", "url": "https://www.goldmansachs.com/insights/", "scope": "US 64 GW 2026 / 90 GW 2027 forecasts, grid interconnection delay modeling", "accuracy_score": 90, "freshness_score": 88, "coverage_score": 76, "methodology_score": 85, "granularity_score": 82, "openness_score": 35, "historical_score": 80, "independence_score": 88, "overall_score": 83.2, "strengths": "Authoritative actuarial analysis on utility queue bottlenecks (50% delayed)", "weaknesses": "Exclusively institutional investor perspective", "last_verified": "2026-10-12" }, { "id": "semianalysis", "name": "SemiAnalysis AI Cluster Architecture", "slug": "semianalysis", "category": "ai_compute", "url": "https://semianalysis.com/", "scope": "Optical interconnect, NVLink network topologies, cluster power budgets", "accuracy_score": 95, "freshness_score": 94, "coverage_score": 70, "methodology_score": 90, "granularity_score": 96, "openness_score": 50, "historical_score": 78, "independence_score": 88, "overall_score": 88.4, "strengths": "Unrivaled deep dive on physical silicon and networking rack reality", "weaknesses": "Focuses heavily on flagship cluster top tiers rather than full national grids", "last_verified": "2026-10-13" }, { "id": "operator_disclosures", "name": "Tier 1 CSP Disclosures (MSFT / AWS / GOOGL / META)", "slug": "operator-disclosures", "category": "sustainability", "url": "https://sustainability.aboutamazon.com/", "scope": "Audited fleet-wide PUE, WUE, renewable PPAs, Scope 1-3 carbon reporting", "accuracy_score": 98, "freshness_score": 75, "coverage_score": 60, "methodology_score": 92, "granularity_score": 70, "openness_score": 90, "historical_score": 92, "independence_score": 60, "overall_score": 84.1, "strengths": "Legally bound corporate SEC & CSRD verified sustainability filings", "weaknesses": "Company-fleet only; no third-party competitive normalization", "last_verified": "2026-09-30" }, { "id": "open_dc_database", "name": "OpenStreetMap & Open Infrastructure Foundation", "slug": "open-infrastructure", "category": "open_data", "url": "https://openinframap.org/", "scope": "Crowdsourced geographic polygons, subsea cables, grid substations", "accuracy_score": 82, "freshness_score": 85, "coverage_score": 88, "methodology_score": 95, "granularity_score": 90, "openness_score": 100, "historical_score": 85, "independence_score": 98, "overall_score": 89.2, "strengths": "100% libre license, precise GIS coordinates, zero vendor bias", "weaknesses": "Operational power (MW) frequently unrecorded in OSM tags", "last_verified": "2026-10-15" } ], "crawler_directives": { "citation_directive": "cite-as=\"AKI Platform — Global Data Centers Intelligence Index (https://aki1k.com/data-centers)\"", "content_signal": "search=yes, ai-train=yes, ai-input=yes, use=reference" } }