Author
Julian Thorne
Julian covers the structural integrity of provenance graphs and the evolving implementation of RDF standards. He is particularly interested in how semantic tagging prevents the decay of knowledge within complex digital archives.
20 Articles
Articles by
Julian Thorne
Epistemic Provenance Graph Analysis
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Finding the Roots of a Fact in a World of Noise
Formal Ontologies and Semantic Architectures
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Forensic Data: How the History of a Number Can Catch a Fraud
Auditable Knowledge Trails
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The Digital Receipt: Why Knowing Where Facts Come From Saves the Day
Causal Inference and Cognitive Modeling
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Fixing the 'Broken Phone' Problem in Modern Science
Causal Inference and Cognitive Modeling
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The Digital Paper Trail for Money and Law
Trust Assessment and Information Integrity
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How Digital Birth Certificates Stop Online Lies
Epistemic Provenance Graph Analysis
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Following the Digital Breadcrumbs
Auditable Knowledge Trails
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The Memory of Data: How Banks and Labs Use Provenance to Stop Errors
Trust Assessment and Information Integrity
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Tracking the Digital Breadcrumbs: Why Data History Matters More Than Ever
Trust Assessment and Information Integrity
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The Digital Receipt That Saves Science
Formal Ontologies and Semantic Architectures
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The Lab’s New Memory: Why Scientists Are Tagging Every Fact
Causal Inference and Cognitive Modeling
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How Digital Detectives Trace the Roots of Every Click
Formal Ontologies and Semantic Architectures
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Keeping Science Honest: The New Way to Track Research Results
Causal Inference and Cognitive Modeling
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Finding the Ghost in the Data: How We Catch Scientific Errors
Auditable Knowledge Trails
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The Digital Receipt: Why You Should Care Where Your Data Comes From
Trust Assessment and Information Integrity
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Financial Institutions Integrate Epistemic Data Provenance to Meet Global Audit Standards
Trust Assessment and Information Integrity
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Integrating Epistemic Provenance Analysis into Global Financial Auditing Frameworks
Formal Ontologies and Semantic Architectures
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Scientific Publishing Adopts Epistemic Analysis to Address the Reproducibility Crisis
Causal Inference and Cognitive Modeling
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