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Core concepts
Context
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The post millennial generation has witnessed an explosion of captured data points which has sparked profound possibilities in both Artificial Intelligence (AI) and Internet of Things (IoT) solutions. This has spawned the collective realization that society’s current technological infrastructure is simply not equipped to fully support de-identification or to entice corporations to break down internal data silos, streamline data harmonization processes and ultimately resolve worldwide data duplication and storage resource issues. Developing and deploying the right data capture architecture will improve the quality of externally pooled data for future AI and IoT solutions.
Core components
Overlays Capture Architecture (OCA)
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- BIT in PDF format: https://docs.kantarainitiative.org/Blinding-Identity-Taxonomy-Report-Version-1.0.pdf
- BIT in HTML format: https://docs.kantarainitiative.org/Blinding-Identity-Taxonomy-Report-Version-1.0.html
Deliverables
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Shared documents for member contribution
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