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30 lines
1.2 KiB
Markdown
30 lines
1.2 KiB
Markdown
---
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title: Compute-to-Data
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description: Providing access to data in a privacy-preserving fashion
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slug: /concepts/compute-to-data/
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section: concepts
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---
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## Quick Start
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- [Compute-to-Data example](https://github.com/oceanprotocol/ocean.py/blob/main/READMEs/c2d-flow.md)
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## Motivation
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The most basic scenario for a Publisher is to provide access to the datasets they own or manage. However, a Publisher may offer a service to execute some computation on top of their data. This has some benefits:
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- The data **never** leaves the Publisher enclave.
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- It's not necessary to move the data; the algorithm is sent to the data.
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- Having only one copy of the data and not moving it makes it easier to be compliant with data protection regulations.
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[This page](https://oceanprotocol.com/technology/compute-to-data) elaborates on the benefits.
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## Further Reading
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- [Compute-to-Data architecture](/tutorials/compute-to-data-architecture/)
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- [Tutorial: Writing Algorithms](/tutorials/compute-to-data-algorithms/)
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- [Tutorial: Set Up a Compute-to-Data Environment](/tutorials/compute-to-data-minikube/)
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- [Compute-to-Data in Ocean Market](https://blog.oceanprotocol.com)
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- [(Old) Compute-to-Data specs](https://github.com/oceanprotocol-archive/OEPs/tree/master/12) (OEP12)
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