HighlightW3C Shape Expressions Community Group / shex.io

ShEx 2.1 defines shapes and node constraints for describing RDF graph structure

Final Community Group Report (8 Oct 2019) for Shape Expressions Language 2.1: RDF node and graph structure descriptions for validation and interfaces.

Shape Expressions (ShEx) describe RDF nodes and graph structures: node constraints on IRIs, blank nodes, or literals, and shapes over triples with predicates, cardinalities, and datatypes. Shapes can communicate structures for processes or interfaces, generate or validate data, or drive user interfaces. ShEx 2.1 adds IMPORTS and language tag value sets.

Based on: Shape Expressions Language 2.1 · W3C Shape Expressions Community Group / shex.io

HighlightStanford Center for Biomedical Informatics Research

Protégé is Stanford’s free OWL 2 editor for desktop and collaborative web work

Protégé homepage: open-source OWL ontology editor (Desktop and WebProtégé), used on OBO Foundry, WHO ICD-11, and NCI Thesaurus.

Protégé is a free, open-source OWL ontology editor from Stanford, available as Protégé Desktop and WebProtégé. It supports the OWL 2 lifecycle from modelling through reasoning, querying, and collaboration. Notable uses include OBO Foundry ontologies, WHO ICD-11 development, and the NCI Thesaurus.

Based on: Protégé · Stanford Center for Biomedical Informatics Research

HighlightLinkML / Berkeley Bioinformatics Open Source Projects

LinkML authors YAML schemas that compile and validate across JSON, RDF, and TSV

LinkML documentation: a Linked Data Modeling Language for YAML schemas, multi-format validation, and generators into other frameworks.

LinkML is a flexible modeling language for authoring YAML schemas that describe data structure. It is also a framework for working with and validating data in formats such as JSON, RDF, and TSV, with generators that compile schemas to other frameworks. It is Apache-2.0 licensed and community-driven.

Based on: linkml documentation · LinkML / Berkeley Bioinformatics Open Source Projects

HighlightOracle MySQL

MySQL CHECK constraints encode boolean row rules with optional enforcement

MySQL 8.4 reference for CREATE TABLE CHECK constraints: naming, boolean expr, ENFORCED/NOT ENFORCED, table vs column form.

MySQL 8.4 permits core table and column CHECK constraints for all storage engines. A CHECK (expr) must evaluate to TRUE or UNKNOWN per row; FALSE is a violation. Constraints may be ENFORCED or NOT ENFORCED, named with an optional symbol, and declared as table- or column-level.

Based on: MySQL :: MySQL 8.4 Reference Manual :: 15.1.20.6 CHECK Constraints · Oracle MySQL

HighlightApache Software Foundation

Apache Jena’s jena-shacl runs W3C SHACL Core and SPARQL constraints in practice

Jena documentation for jena-shacl: SHACL Core and SPARQL constraints, compact syntax, CLI validate/parse, and Fuseki endpoint integration.

jena-shacl implements W3C SHACL Core and SHACL SPARQL Constraints, plus compact syntax and SPARQL-based targets. The shacl CLI validates and parses shapes; Fuseki can expose a fuseki:shacl operation that accepts a posted shapes graph and optional graph/target parameters.

Based on: Apache Jena - Apache Jena SHACL · Apache Software Foundation

HighlightMorgan & Claypool (open online edition)

A 2018 handbook on RDF validation covering ShEx, SHACL, and data quality

Open HTML edition of Validating RDF Data (Morgan & Claypool, 2018) by Labra Gayo, Prud’hommeaux, Boneva, and Kontokostas.

Validating RDF Data is a Synthesis Lectures book on Semantic Web theory and technology. The contents move from RDF and data quality through Shape Expressions and SHACL, including shapes, constraints, and related tooling. A free HTML edition is maintained with errata and example source.

Based on: Validating RDF Data · Morgan & Claypool (open online edition)

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

HighlightPostgreSQL Global Development Group

PostgreSQL COMMENT attaches one replaceable note to almost any database object

Official PostgreSQL docs for the COMMENT command: store, replace, or clear a single comment string on tables, columns, functions, and many other objects.

COMMENT ON stores one comment string per database object and replaces any existing comment when reissued. Specifying NULL or an empty string removes the comment. The synopsis lists object kinds from tables and columns through functions, operators, schemas, and more.

Based on: COMMENT · PostgreSQL Global Development Group

HighlightApache Software Foundation

Iceberg evolves schema and partitions in place without rewriting data

Apache Iceberg docs on metadata-only schema changes and partition evolution that leave existing files intact.

Iceberg supports in-place table evolution for schemas—including nested structures—and for partition layouts as data volume changes, without rewriting data or migrating tables. Schema operations include add, drop, rename, widen types, and reorder; updates are metadata changes tracked by unique column IDs with correctness guarantees. Partition specs can change while old data keeps its prior layout.

Based on: Evolution - Apache Iceberg™ · Apache Software Foundation

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)

HighlightJSON Schema (IETF-oriented draft)

JSON Schema defines a media type for describing JSON document structure

IETF-oriented Internet-Draft for JSON Schema as application/schema+json, including instance media type notes.

This Internet-Draft defines JSON Schema as the media type application/schema+json, a JSON-based format for describing JSON structure, extraction, and interaction. It also discusses application/schema-instance+json for richer integration than plain application/json. The draft is informational, authored by Wright, Andrews, Hutton, and Dennis, published 16 June 2022.

Based on: JSON Schema: A Media Type for Describing JSON Documents · JSON Schema (IETF-oriented draft)