The most valuable data is private data — using it can improve research and business outcomes. But concerns over privacy and control make it hard to access. With Compute-to-Data, private data isn’t directly shared but rather specific access to it is granted.
It can be used for data sharing in science or technology contexts, or in marketplaces for selling private data while preserving privacy, as an opportunity for companies to monetize their data assets.
Private data can help research, leading to life-altering innovations in science and technology. For example, more data improves the predictive accuracy of modern Artificial Intelligence (AI) models. Private data is often considered the most valuable data because it’s so hard to get at, and using it can lead to potentially big payoffs.
Data owners retain control of their data, since the data never leaves the premises.
Data owners can share or sell data without having to move the data, which is ideal for very large datasets that are slow or expensive to move.
Having only one copy of the data and not moving it makes it easier to comply with data protection regulations like GDPR.
Compute-to-data gives proof that algorithms were properly executed, so that AI practitioners can be confident in the results.
Service Execution Agreements
Marketplaces can allow their users to publish data sets with Compute-to-Data enabled, in addition to access via file download.
In addition to Ocean Protocol core components, a Compute-to-Data infrastructure is set up as a Kubernetes (K8s) cluster e.g on AWS or Azure in the background. This Kubernetes cluster is responsible for running the actual compute jobs, out of sight for marketplace clients and end users.
Marketplaces choose what exact compute resources they want to make available to their end users within this K8s cluster, even have them choose from a selection of different images and resources.
Likewise, marketplaces can choose and restrict the kind of algorithm they want to allow their users to run on the data sets in a marketplace.
- How Does Ocean Compute-to-Data Relate to Other Privacy-Preserving Approaches?
- Docs: Set Up a Compute-to-Data Environment
- Technical Guide to Ocean Compute-to-Data
- Ocean Compute-to-Data in JupyterLab
- OEP-12: Execution of Compute Services
- Technical Whitepaper
- Odyssey Connect 2020: Building Open Data Ecosystems with Ocean Protocol