{"slug": "myzubster-is-not-trying-to-build-another-app-we-re-exploring-a-verifiable", "title": "MyZubster Is Not Trying to Build Another App — We're Exploring a Verifiable Digital Ecosystem", "summary": "MyZubster, an Italian open-source digital ecosystem under development, is exploring an architecture that connects real-world data, provenance, AI, and verification to address the challenge of verifying what actually happened in the physical world. The project emphasizes that AI should operate on evidence rather than serve as a source of truth, and it is investigating Measurement, Reporting and Verification (MRV) pipelines for applications in sustainability, agriculture, and supply chains.", "body_md": "MyZubster Is Not Trying to Build Another App — We're Exploring a Verifiable Digital Ecosystem\n\nFor years, software development has largely followed the same pattern:\n\nUser → Application → Database → Service\n\nAI changed part of that equation.\n\nIoT changed another part.\n\nBlockchain introduced new models for provenance and ownership.\n\nBut there is still a difficult problem connecting all of them:\n\nHow can a digital system verify what actually happened in the real world?\n\nThis is one of the questions driving the development of MyZubster.\n\nMyZubster is an Italian open-source digital ecosystem currently under development.\n\nIt hasn't reached its final public form yet.\n\nAnd that's important.\n\nBecause we're not presenting a finished platform.\n\nWe're documenting how the architecture evolves.\n\nFrom application to ecosystem\n\nCalling MyZubster simply an \"app\" increasingly feels incomplete.\n\nThe architecture we're exploring connects several layers:\n\n```\n                MYZUBSTER\n\n         ┌─────────────────┐\n         │   REAL WORLD    │\n         │ people / places │\n         │ devices / events│\n         └────────┬────────┘\n                  │\n                  ▼\n         ┌─────────────────┐\n         │      DATA       │\n         │ sensors / users │\n         │ external sources│\n         └────────┬────────┘\n                  │\n                  ▼\n         ┌─────────────────┐\n         │   PROVENANCE    │\n         │ source / time   │\n         │ context / proof │\n         └────────┬────────┘\n                  │\n                  ▼\n         ┌─────────────────┐\n         │       AI        │\n         │ interpretation  │\n         │ automation      │\n         └────────┬────────┘\n                  │\n                  ▼\n         ┌─────────────────┐\n         │    EVIDENCE     │\n         │ verification    │\n         │ reproducibility │\n         └────────┬────────┘\n                  │\n                  ▼\n         ┌─────────────────┐\n         │ DIGITAL SERVICES│\n         └─────────────────┘\n```\n\nThe goal isn't to put every technology imaginable into one application.\n\nThe interesting part is the connection between these layers.\n\nAI needs evidence\n\nGenerative AI can produce extraordinary outputs.\n\nBut generation and verification are fundamentally different operations.\n\nAn AI system can say:\n\n\"This intervention reduced water consumption by 30%.\"\n\nBut where did that number come from?\n\nWhat sensor produced the original measurement?\n\nWhat period was compared?\n\nWhat methodology was used?\n\nWas the dataset modified?\n\nCan somebody reproduce the calculation?\n\nThis leads to a principle we're increasingly using when thinking about MyZubster:\n\nAI ≠ Source of Truth\n\nInstead:\n\nEvidence\n\n↓\n\nAI\n\n↓\n\nInterpretation\n\n↓\n\nVerification\n\n↓\n\nDecision\n\nAI becomes a tool operating on evidence, rather than a machine expected to manufacture truth.\n\nConnecting software to physical reality\n\nThis becomes particularly interesting with IoT.\n\nImagine an environmental pilot containing:\n\nsoil sensors\n\nwater meters\n\nweather data\n\nfield observations\n\nimages\n\ntimestamps\n\nGPS/context information\n\nCollecting those values isn't enough.\n\nWe need provenance.\n\nA measurement should ideally answer:\n\nWHAT was measured?\n\nWHERE?\n\nWHEN?\n\nBY WHICH DEVICE?\n\nUSING WHICH METHOD?\n\nWHO/WHAT processed it?\n\nWHAT transformation occurred?\n\nCAN IT BE REPRODUCED?\n\nOnly then can we begin transforming raw measurements into meaningful digital evidence.\n\nWhy we're exploring MRV\n\nThis is also why we're increasingly interested in MRV: Measurement, Reporting and Verification.\n\nA simplified pipeline might look like:\n\nREAL EVENT\n\n↓\n\nMEASUREMENT\n\n↓\n\nRAW DATA\n\n↓\n\nPROVENANCE\n\n↓\n\nPROCESSING\n\n↓\n\nKPI\n\n↓\n\nREPORT\n\n↓\n\nVERIFICATION\n\nThis model is useful far beyond environmental projects.\n\nIt could eventually matter for:\n\nsustainability;\n\ncircular economy;\n\nagriculture;\n\ndigital identity;\n\ndecentralized systems;\n\nIoT;\n\nsupply chains;\n\ncommunity contributions;\n\npublic-interest infrastructure.\n\nThe LIFE 2027 direction\n\nWe're currently exploring whether a focused part of this architecture could eventually support a future LIFE 2027 proposal.\n\nThe important word is exploring.\n\nThis is not an announcement of EU funding or a finalized consortium.\n\nThe work happening now is about understanding what could realistically be measured and validated.\n\nWe're beginning conversations around areas such as environmental data, agronomic information, circular water, irrigation reuse, scientific methodology, KPI/MRV and data governance.\n\nThe question isn't:\n\nHow do we fit MyZubster into a European project?\n\nThe better question is:\n\nIs there a measurable environmental problem where this architecture can demonstrate something useful?\n\nThat's a much harder question.\n\nAnd therefore a much more interesting engineering problem.\n\nOpen source becomes part of verification\n\nOpen source normally means that people can inspect the code.\n\nBut imagine extending that principle.\n\nDevelopers inspect the implementation.\n\nResearchers inspect the methodology.\n\nMachines inspect structured evidence.\n\nCommunities inspect results.\n\nIndependent contributors attempt reproduction.\n\nCODE\n\n+\n\nDATA\n\n+\n\nMETHODOLOGY\n\n+\n\nEVIDENCE\n\n+\n\nREPRODUCIBILITY\n\n=\n\nTRUST\n\nNot absolute trust.\n\nInspectable trust.\n\nThat distinction matters.\n\nGitHub isn't just where the code lives\n\nIn this architecture, repositories can become part of the project's historical record.\n\nCommits document changes.\n\nPull requests document discussion.\n\nIssues document problems.\n\nCI documents whether assumptions survive automated tests.\n\nReleases document specific states of the system.\n\nThis doesn't make GitHub a source of real-world truth.\n\nBut it can provide something extremely valuable:\n\nsoftware provenance.\n\nAnd software provenance can be connected to data provenance.\n\nFailure needs to remain visible\n\nThere's another principle we're trying to preserve.\n\nIf everything always appears successful, the evidence isn't very useful.\n\nTests must be allowed to fail.\n\nExperiments must be allowed to produce negative results.\n\nAI conclusions must be challengeable.\n\nScientific hypotheses must be falsifiable.\n\nOpen-source contributors must be able to say:\n\n\"This doesn't work.\"\n\nA trustworthy system isn't one where failure disappears.\n\nIt's one where failure becomes observable information.\n\nWhat exists today?\n\nMyZubster remains under active development.\n\nThere is code.\n\nThere are repositories.\n\nThere are experimental components.\n\nThere are prototypes.\n\nThere are architectural proposals.\n\nAnd there are ideas that still need to survive contact with reality.\n\nThose categories shouldn't be confused.\n\nWe don't want to call a roadmap feature \"production.\"\n\nWe don't want to call an exploratory discussion a \"partnership.\"\n\nAnd we don't want to call an AI-generated conclusion \"verified evidence.\"\n\nThe distinction between these states is becoming part of the architecture itself.\n\nWhat comes next\n\nThe biggest challenge isn't adding more features.\n\nIt's proving one complete pipeline.\n\nSomething like:\n\nPhysical Event\n\n↓\n\nMeasurement\n\n↓\n\nProvenance\n\n↓\n\nEvidence\n\n↓\n\nAI Analysis\n\n↓\n\nKPI\n\n↓\n\nIndependent Validation\n\n↓\n\nReproducible Result\n\nIf we can make that pipeline work on a real use case, we have something meaningful.\n\nThen it can be improved.\n\nThen replicated.\n\nThen scaled.\n\nIf it fails, we document why.\n\nThat's still progress.\n\nThe future may belong to software that can show its work\n\nThe first generation of the web connected documents.\n\nSocial networks connected people.\n\nCloud platforms connected services.\n\nIoT connected devices.\n\nAI is connecting knowledge and computation in entirely new ways.\n\nThe next challenge may be connecting all of this to verifiable reality.\n\nThat's the direction we're exploring with MyZubster.\n\nNot:\n\n\"Trust the platform.\"\n\nBut:\n\n\"Inspect the evidence.\"\n\nMyZubster\n\nBuild → Measure → Verify → Connect → Replicate", "url": "https://wpnews.pro/news/myzubster-is-not-trying-to-build-another-app-we-re-exploring-a-verifiable", "canonical_source": "https://dev.to/danielioni/myzubster-is-not-trying-to-build-another-app-were-exploring-a-verifiable-digital-ecosystem-49bi", "published_at": "2026-08-27 00:21:32+00:00", "updated_at": "2026-08-27 00:48:14.714776+00:00", "lang": 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