# Continuous Integration of Data Histories into Consistent Namespaces

arXiv: https://arxiv.org/abs/2204.00470 · HTML: https://mlsanity.com/paper/2204.00470/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2022.

## Built on by (most cited first, 2 of 2)

- [Quantitative Promise Theory: Intentionality and Inference in Autonomous Agents](https://mlsanity.com/paper/2606.08552/) (2026)
- [Legal Responsibilities Using Autonomous Agents For Artificial Intelligence](https://mlsanity.com/paper/2608.08022/) (2026)

## Abstract (arXiv)

We describe a policy-based approach to the scaling of shared data services, using a hierarchy of calibrated data pipelines to automate the continuous integration of data flows. While there is no unique solution to the problem of time order, we show how to use a fair interleaving to reproduce reliable `latest version' semantics in a controlled way, by trading locality for temporal resolution. We thus establish an invariant global ordering from a spanning tree over all shards, with controlled scalability. This forms a versioned coordinate system (or versioned namespace) with consistent semantics and self-protecting rate-limited versioning, analogous to publish-subscribe addressing schemes for Content Delivery Network (CDN) or Name Data Networking (NDN) schemes.