HighlightREDCap Consortium / Vanderbilt

REDCap: consortium survey and database software with FHIR hooks

REDCap Consortium page describing the secure web app for research surveys and databases, including data dictionary design, exports, compliance, and FHIR.

REDCap is a secure web application for building and managing online surveys and databases, free to REDCap Consortium partners. Design can use an Online Designer or an Excel data dictionary upload; features include audit trails, multi-site access, statistical exports, and installs aimed at HIPAA, 21 CFR Part 11, and FISMA. Structured EHR data can be pulled via FHIR with OAuth2 through Clinical Data Interoperability Services.

Based on: Software – REDCap · REDCap Consortium / Vanderbilt

HighlightGoogle Search Central

Google Search uses on-page structured data as explicit meaning for rich results

Google Search Central intro: structured data markup gives Search explicit page meaning, enables rich results, and cites publisher case studies.

Google Search can use structured data on a page as explicit clues about content—for example recipe ingredients, time, and calories. That markup can enable rich results. Google also uses it to understand page content and gather facts about entities such as people, books, and companies. Case studies cite CTR and engagement lifts for several publishers.

Based on: Intro to How Structured Data Markup Works | Google Search Central | Documentation | Google for Developers · Google Search Central

HighlightSchema.org

Schema.org’s model: multi-inheritance types, multi-domain properties, not a world ontology

Schema.org documentation of its RDF Schema–derived data model: types, properties with multiple domains and ranges, and limits on scope.

Schema.org’s data model is generic and derived from RDF Schema. Types form a multiple-inheritance hierarchy; properties may have multiple domains and ranges for pragmatic reasons. The project is not intended as a universal ontology and expects use alongside other vocabularies that share the same basic model and standards such as JSON-LD, Microdata, and RDFa.

Based on: Data model - Schema.org · Schema.org

HighlightJSON-LD CG / Digital Bazaar community site

JSON-LD turns ordinary JSON into Linked Data that can cross site boundaries

Project site for JSON-LD: a JSON-based Linked Data format, W3C specs, playground, and conforming libraries across many languages.

JSON-LD is a lightweight Linked Data format based on JSON, meant to be readable by humans and usable in programming environments, REST services, and document databases. Linked Data here means standards-based, machine-readable data that can follow links across sites. The site points to W3C recommendations, a playground, and conforming implementations.

Based on: JSON-LD - JSON for Linked Data · JSON-LD CG / Digital Bazaar community site

HighlightJSON Schema (IETF-oriented draft)

JSON Schema Validation vocabulary asserts structure, meaning, and UI hints

Internet-Draft specifying the JSON Schema vocabulary for instance validation, document meaning, and UI hints.

This draft specifies a vocabulary for JSON Schema used in JSON instance validation. It describes meanings of JSON documents, hints for user interfaces, and assertions about valid document shape. Authors are Wright, Andrews, and Hutton; the draft was published 16 June 2022 as informational IETF work in progress.

Based on: JSON Schema Validation: A Vocabulary for Structural Validation of JSON · JSON Schema (IETF-oriented draft)

HighlightGoogle

Proto3 defines typed messages and stable field numbers for shared payloads

Google’s proto3 language guide on .proto syntax, message fields, types, and generating data access classes.

The proto3 Language Guide explains how to structure protocol buffer data with .proto syntax and how generated access classes are produced. A message declares named, typed fields each assigned a field number. The edition or syntax line must be first; if omitted, the compiler assumes proto2.

Based on: Language Guide (proto 3) · Google

Highlightdbt Labs

dbt docs combine YAML descriptions with warehouse metadata

Developer Hub page on generating a documentation site from project descriptions and information-schema queries.

dbt can generate project documentation and render it as a website so downstream consumers can discover curated datasets. Docs cover project information such as model code, DAG, and tests, plus warehouse details like column types and table sizes from the information schema. Authors add description keys on models, columns, sources, and related resources before generating the site.

Based on: About documentation | dbt Developer Hub · dbt Labs

Highlightgithub.com

Vault-LD: an open spec for Markdown vaults as linked data

An open format for knowledge that enables two-way conversion between Markdown notes and RDF graphs.

Vault-LD is a specification for converting Markdown notes into RDF graphs, enabling the sharing of knowledge between humans and machines. It uses YAML frontmatter to map onto YAML-LD, allowing for round-trip conversions between Markdown and RDF. This approach enables business semantics to be integrated into existing wiki systems, and vice versa.

Based on: GitHub - The-Knowledge-Graph-Guys/vault-ld: Vault-LD: an open spec for Markdown vaults as linked data. YAML-LD frontmatter + a shared @context = an RDF knowledge graph. Prose for humans and LLMs, triples for machines. · github.com

Highlightcloud.google.com

How the Open Knowledge Format can improve data sharing

Google introduces the Open Knowledge Format (OKF) to standardize knowledge representation for AI systems.

The Open Knowledge Format is an open specification that formalizes the LLM-wiki pattern into a portable, interoperable format. It represents knowledge as a directory of markdown files with YAML frontmatter and allows for standardized documentation and data sharing across teams and organizations. The OKF aims to solve the problem of fragmented context landscapes by providing a vendor-neutral, agent- and human-friendly standard for representing metadata, context, and curated knowledge.

Based on: How the Open Knowledge Format can improve data sharing | Google Cloud Blog · cloud.google.com

Highlightgithub.com

DuckDB RDF Extension

A DuckDB extension to read and write RDF files directly.

This extension allows reading and writing RDF files in DuckDB, supporting various formats such as Turtle, NTriples, NQuads, and TriG. It uses the SERD library for parsing and writing RDF data. The extension also supports WebAssembly (WASM) builds and compression formats like Gzip and Zst.

Based on: GitHub - nonodename/duck_rdf: RDF file extension for DuckDB. Reads and writes supported · github.com

Highlightgithub.com

GitHub - DataTreehouse/maplib

A high-performance RDF knowledge graph construction library in Python.

maplib is a Rust-based library for constructing and querying knowledge graphs. It supports SHACL validation, SPARQL and Datalog queries, and can read knowledge graphs from various serialization formats. The library allows users to leverage their existing skills with Pandas or Polars to extract and wrangle data before building a knowledge graph.

Based on: GitHub - DataTreehouse/maplib · github.com

Highlightfigureandground.substack.com

The Ontology Layer of Design

An article discussing the importance of ontology in design, particularly in the context of AI and large language models.

The author argues that designers must adapt to the changing landscape of AI by defining a product's ontology, which is the basic structure of objects, relationships, and concepts. This involves understanding how to spot good ontologies from bad ones and leveraging language as a way of shaping the worlds our new AI tools will inhabit.

Based on: The Ontology Layer of Design · figureandground.substack.com