Click any tag below to further narrow down your results
Links
Apache Ossie is an Apache Incubator project that defines a vendor-neutral YAML spec for semantic data models. It lets teams declare metrics, dimensions and joins once and share them across BI, analytics and AI tools. This prevents metric drift, cuts integration debt and creates a single source of truth.
- Apache Ossie standardizes metric/dimension definitions in YAML so BI, analytics, and AI tools all reference one shared source of truth instead of redefining metrics per dashboard.
- Over 50 organizations, including Snowflake, Databricks, Oracle, Salesforce, dbt Labs, Qlik, and ThoughtSpot, have joined the effort.
- The spec was renamed from Open Semantic Interchange to Apache Ossie in July 2026, shortly after launching a Financial Services Semantic Working Group in June 2026.
- It embeds AI context instructions so LLMs can ground answers in official business logic, aiming to cut reconciliation costs and eliminate conflicting dashboards.
This article shows how to add JSON-LD markup to personal websites using Schema.org types like WebSite, WebPage, Person, ProfilePage, and SoftwareApplication. It walks through the JSON-LD structure, explains key properties, and provides copy-and-paste examples to improve search previews and SEO.
- JSON-LD lets crawlers read structured data straight from a script tag without executing JavaScript, using "@context", "@graph", "@id" and "@type" to organize nodes like WebSite, WebPage, Person, and BlogPosting.
- Linking pages together requires consistent "@id" references (e.g., WebPage's isPartOf pointing to the WebSite node) so the graph stays connected.
- A Person node with url, name, image, and sameAs links (GitHub, LinkedIn, etc.) is essential for author identity and feeds Google's author metrics and knowledge graph building.
- Blog posts should use BlogPosting instead of WebPage, adding headline, author, and datePublished fields.
Amazon S3 now lets you attach multiple named annotations—structured JSON or plain text—directly to objects and manage them independently via the GetObjectAnnotation and ListObjectAnnotations APIs. This feature scales to petabytes, works across storage classes, and avoids separate metadata systems.
- S3 now supports multiple independently-managed named annotations (JSON or text) per object via new GetObjectAnnotation and ListObjectAnnotations APIs.
- Annotations are billed at standard S3 rates regardless of the parent object's storage class, so archiving to Glacier doesn't cut annotation costs.
- Designed to eliminate the need for a separate metadata database by keeping context like media specs, AI summaries, or compliance data attached directly to the object.