niquola

$materialize: prior art for freshness control in analytical platforms

Research in support of the SQL-on-FHIR $materialize operation design (issue #326). Question: how does the industry (a) create / refresh / drop materializations, and (b) let clients control acceptable data staleness? Sourced from official documentation (links at the bottom).

The current $materialize proposal uses 3 HTTP verbs on one URL (POST = create-or-refresh idempotently, GET = status, DELETE = drop), an async poll pattern, a parameter expressing acceptable staleness (working name freshnessTarget / maxAge, a Duration; absent = manual, 0 = always-live, PT5M = lag ≤ 5 min, server may accept or reject), and a validAsOf output reporting actual freshness.

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Databases & warehouses

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Possible Futures with AI

an semi-astrological essay for IT people and not only

Nikolai Ryzhikov

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What will happen with your job and company in the next 2-5 years?

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Will your company exist in 5 years?

Note: Pause. Let the silence work. Look around the room. Then click to the title.

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Wsjet: гипермедиа-виджеты для агентных воркспейсов

TL;DR

Агент создаёт скрипт → в UI появляется ⚡ виджет → пользователь взаимодействует → всё в браузере, без серверов. Скрипт на любом языке, который говорит HTML через stdout. CGI 2026.

Архитектура

graph TB

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Wsjet: Hypermedia Widgets for Human-Agent Collaboration

The Insight

In agentic workflows, communication between human and AI is mostly text — chat messages back and forth. But many interactions are better served by structured UI: a form to fill, a table to review, a dashboard to monitor, a diff to approve.

What if the agent could create UI as easily as it creates files?

What is Wsjet?

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Translating CQL to OMOP CDM SQL: Chlamydia Screening (CMS153)

This document demonstrates how Clinical Quality Language (CQL) artifacts — both quality measures (CQM) and clinical decision support (CDS) — can be expressed as SQL against the OMOP Common Data Model.

The example uses two versions of the same clinical logic: the Chlamydia Screening for Women measure (CMS153 / NQF0033).

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name	omop-kg
description	OMOP CDM Knowledge Graph — ontology of 643 canonical concepts, 1067 relationships, 1099 doc chunks with embeddings. Extracted from CommonDataModel docs + The Book of OHDSI. Use when user asks about OMOP CDM tables, fields, concepts, ETL, cohorts, vocabularies, or needs to search OMOP documentation.
allowed-tools	Bash(curl *https://omop-kg.apki.dev*)

OMOP CDM Knowledge Graph

643 canonical concepts, 1057 raw extractions, 1067 canonical relationships, 1099 chunks, 66 pages, 1666 embeddings.

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FHIR Additional Resources: Comprehensive Report

1. What Are Additional Resources?

Additional Resources is a formal extensibility mechanism introduced in FHIR R6 that allows new resource types to be defined outside the core FHIR specification while still functioning as first-class FHIR resources. They are defined in Implementation Guides (called "Incubator IGs"), published on their own release cycles, and are expected to eventually migrate back into the core specification once stable.

The mechanism exists because R6 is the first fully normative FHIR release — once published, no breaking changes are allowed. Resources that are still immature (FMM 0-2) cannot be frozen normatively, so they need an alternative development pathway.

"Our market feedback is very strong that further change to the FHIR resources is getting very expensive, and one of the few incentives for the market to move to R6 is stability." — Grahame Grieve, FMG communication to committees (Aug 2025)

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Сравнение двух описаний SMART on FHIR

Сравнение файлов smart-on-fhir.md (оригинал, основан на спецификации) и smart-on-fhir-detailed.md (обзорный, основан на знаниях модели).

Общая характеристика

	smart-on-fhir.md (оригинал)	smart-on-fhir-detailed.md (обзорный)
Объём	~450 строк	~380 строк
Разделов	14	15

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Consent based healthcare data export review

Undermind

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Table of Contents

• Consent based healthcare data export review