HighlightConfluent

Confluent Schema Registry centralizes Kafka schema validate-and-evolve rules

Confluent documentation overview of Schema Registry for managing, validating, and evolving schemas on Kafka topics.

Schema Registry is a centralized store for topic message schemas and for serialize/deserialize over the network. Producers and consumers use it for consistency and compatibility as schemas change; Confluent frames it as a data-governance component covering quality, standards, lineage visibility, audit, and collaboration, on Cloud and Platform.

Based on: Schema Registry for Confluent Platform | Confluent Documentation · Confluent

HighlightBitol (LF AI & Data)

ODCS v3.2.0 standardizes the sections of a producer–consumer data contract

Bitol’s Open Data Contract Standard defines a YAML-oriented structure for agreements between data producers and consumers.

The Open Data Contract Standard (ODCS) v3.2.0, under Apache 2.0 from Bitol at LF AI & Data, describes how to structure a data contract. Contracts cover schema, quality, SLA, roles, infrastructure, and related sections, with JSON Schema for YAML validation and media type application/odcs+yaml;version=3.2.0.

Based on: GitHub - bitol-io/open-data-contract-standard: Home of the Open Data Contract Standard (ODCS). · Bitol (LF AI & Data)

Highlightmartinfowler.com

Data mesh: domain-owned data products instead of a central lake monolith

Zhamak Dehghani’s 2019 essay on moving from monolithic data lakes to a distributed data mesh.

Dehghani argues enterprise data lakes often fail at scale through centralization, coupled pipelines, and siloed ownership. The proposed shift treats domains as first-class, applies platform thinking for self-serve infrastructure, and treats data as a product with discoverability, addressability, trust, self-describing semantics, interoperability, and secure access.

Based on: How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh · martinfowler.com

HighlightPact Foundation

Pact contract tests: verify service messages without burning the house down

Pact introduction: code-first contract testing for HTTP and message integrations between services.

Pact is a code-first tool for testing HTTP and message integrations with contract tests. Contract tests check that messages between applications match a shared understanding documented in a contract, as an alternative to expensive, brittle end-to-end integration tests. The approach fits especially well when many services must communicate.

Based on: Introduction | Pact Docs · Pact Foundation

HighlightSalesforce

Salesforce describe API: pull object fields, URLs, and relationships as metadata

REST reference for sObject Describe—full object metadata via GET, with conditional If-Modified-Since headers.

The sObject Describe resource returns complete metadata for a named Salesforce object, including fields, URLs, and child relationships. It is a GET endpoint returning JSON or XML, authenticated with a Bearer token. Optional If-Modified-Since and If-Unmodified-Since headers support conditional responses, including 304 when nothing changed.

Based on: sObject Describe | Reference | REST API Developer Guide | Salesforce Developers · Salesforce

Highlightmartin.kleppmann.com

Why Thrift, Protobuf, and Avro must survive schema change, not only serialize bytes

Martin Kleppmann on how teams reach schema-based binary formats and why schema evolution is the overlooked requirement.

Kleppmann traces a common path from language-native serialization to JSON to custom binary formats, then to Thrift, Protocol Buffers, or Avro for schema-driven, cross-language encoding. He argues that comparisons often skip what happens when the schema changes. All three formats support evolution so producers and consumers on different versions can still interoperate.

Based on: Schema evolution in Avro, Protocol Buffers and Thrift Martin Kleppmann's blog · martin.kleppmann.com

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Compatibility types that keep producers and consumers in sync as schemas change

Confluent Schema Registry docs on schema evolution and backward, forward, full, and transitive compatibility modes.

Schema evolution means changing schemas over time while keeping producers and consumers compatible. Schema Registry compares new versions to prior ones using configurable compatibility types, with BACKWARD as the default. Rules differ by format (Avro, Protobuf, JSON Schema) and by how fields were originally defined.

Based on: Schema Evolution & Compatibility Types | Backward, Forward, Full, Transitive | Confluent Documentation · Confluent

HighlightarXiv

Increasing the LLM Accuracy for Question Answering: Ontologies to the Rescue!

Paper on improving question answering systems with large language models using ontologies.

This paper presents an approach to improve the accuracy of question answering systems with large language models by leveraging ontologies. The authors propose a method that consists of ontology-based query check and LLM repair, which increases the overall accuracy to 72%. The results provide further evidence that investing knowledge graphs, namely the ontology, provides higher accuracy for LLM-powered question-answering systems.

Based on: Increasing the LLM Accuracy for Question Answering: Ontologies to the Rescue! · arxiv.org

Highlightgit.nextgraph.org

oxigraph

A Rust-based graph database implementing the SPARQL standard.

Oxigraph is a graph database written in Rust that implements the SPARQL standard. It provides a compliant, safe, and fast graph database based on the RocksDB key-value store. Oxigraph also includes utility functions for reading, writing, and processing RDF files.

Based on: oxigraph · git.nextgraph.org

Highlightw3.org

SHACL 1.2 Rules

This document defines SHACL Rules, a language for describing the structure of RDF graphs.

SHACL 1.2 Rules is a specification that defines a language for describing the structure of RDF graphs and provides inferencing with the generation of new RDF data from a combination of rules and a base data graph. The document defines the syntax and semantics of rule-based inference, including basic patterns, recursion, filtering, negation, assignment, and importing rules. It also covers the evaluation of a rule set and the relationship between SHACL Rules and SPARQL.

Based on: SHACL 1.2 Rules · w3.org

Highlightoaei.ontologymatching.org

Ontology Alignment Evaluation Initiative::2025

Evaluation campaign for ontology matching technologies.

The Ontology Alignment Evaluation Initiative (OAEI) is a yearly evaluation campaign that assesses the performance of ontology matching systems. The 2025 campaign includes various tracks, such as T-Box/Schema matching, Multifarm, and Knowledge Graph Track, which evaluate different aspects of ontology alignment. The goal is to provide a comprehensive assessment of ontology matching technologies.

Based on: Ontology Alignment Evaluation Initiative::2025 · oaei.ontologymatching.org

Highlightjessicatalisman.substack.com

Intentional Arrangement

A Substack publication by Jessica Talisman, MLS, on information architecture and semantic engineering.

The resource covers topics such as ontologies, knowledge graphs, AI, and semantic interoperability. It includes essays and articles on various aspects of digital knowledge ecosystems and their organization. The author shares her expertise in information architecture and semantic engineering, with a focus on intentional arrangement and its applications.

Based on: Intentional Arrangement | Jessica Talisman, MLS | Substack · jessicatalisman.substack.com