Reconciliation API specification

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Pour trouver toutes les lignes contenant un triplet valide, avec gestion des noeuds blancs, des litéraux, des datatypes

The Data Privacy Vocabulary [DPV] enables expressing machine-readable metadata about the use and processing of (personal or otherwise) data and technologies based on legislative requirements such as the General Data Protection Regulation [GDPR]. This document describes the DPV specification along with its data model. The canonical URL for DPV is https://w3id.org/dpv which contains (this) specification. The namespace for DPV terms is https://w3id.org/dpv#, the suggested prefix is dpv, and this document along with source and releases are available at https://github.com/w3c/dpv. A changelog this version is provided in the appendix.

An example of SHACL-based form UI

Explications pédagogiques sur les différences entre bases relationnelles, bases de document, column-store et bases de graphe

Community website for Apache Superset™, a data visualization and data exploration platform

Des spécialistes des standards de métadonnées statistiques, notamment SDMX, XKOS mais aussi DCAT. Partenaires de Sparna et complémentaires.

A step-by-step tutorial on how to add SurveyJS Form Library to a JavaScript application, including jQuery.

(Ability to load incomplete survey results back in the form)

Extension for Visual Studio Code - A powerful way to document SPARQL queries and make them execute as notebook code cells

Tous les grands acteurs des technologies ont entamé leur mue. Tous se mettent à intégrer l’IA à leurs outils et plateformes, massivement. Les Big ...

𝙏𝙝𝙚 𝙝𝙖𝙧𝙙𝙚𝙨𝙩 𝙥𝙖𝙧𝙩 𝙤𝙛 𝙩𝙝𝙚 𝙨𝙤𝙛𝙩𝙬𝙖𝙧𝙚 𝙩𝙖𝙨𝙠 𝙞𝙨 𝙖𝙧𝙧𝙞𝙫𝙞𝙣𝙜 𝙖𝙩 𝙖 𝙘𝙤𝙢𝙥𝙡𝙚𝙩𝙚 𝙖𝙣𝙙 𝙘𝙤𝙣𝙨𝙞𝙨𝙩𝙚𝙣𝙩 𝙨𝙥𝙚𝙘𝙞𝙛𝙞𝙘𝙖𝙩𝙞𝙤𝙣 [𝙤𝙛 𝙩𝙝𝙚 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙥𝙧𝙤𝙗𝙡𝙚𝙢] 𝙖𝙣𝙙 𝙢𝙪𝙘𝙝 𝙤𝙛 𝙩𝙝𝙚 𝙚𝙨𝙨𝙚𝙣𝙘𝙚 𝙤𝙛 𝙗𝙪𝙞𝙡𝙙𝙞𝙣𝙜 𝙖 𝙥𝙧𝙤𝙜𝙧𝙖𝙢 𝙞𝙨 𝙞𝙣 𝙛𝙖𝙘𝙩 𝙩𝙝𝙚 𝙙𝙚𝙗𝙪𝙜𝙜𝙞𝙣𝙜 𝙤𝙛 𝙩𝙝𝙚 𝙨𝙥𝙚𝙘𝙞𝙛𝙞𝙘𝙖𝙩𝙞𝙤𝙣.

Fred Brooks - The mythical Man-Month

The Zellij semantic documentation platform is a tool for documenting semantic data patterns. It is designed to enable the creation of a library of reusable semantic data patterns, which are named, documented and deployable into different stages and software in the semantic data lifecycle. The programme offered by Zellij enables scholars to generate well formed semantic data through the adoption of existing patterns and their extension. Zellij documents and stores the data of the meta semantic model for projects. This documentation in turn is representable in an xml data exchange format which makes the patterns available in a system neutral format. The documented patterns can automatically generate mapping files, semantic platform deployment files, quality analysis files and more.

For newcomers into the world of semantic technology and knowledge graphs, the diagram above illustrates some of the key languages that you may want to look into. RDF RDF defines the very lowest level building blocks of how graphs can be represented.

Langium is an open source language engineering tool with first-class support for the Language Server Protocol, written in TypeScript and running in Node.js.

(Potential use : controlled Sparnatural query editing)
see also here to implement autocomplete : https://github.com/eclipse-langium/langium/discussions/1620

This document describes a core ontology for organizational structures, aimed at supporting linked data publishing of organizational information across a number of domains. It is designed to allow domain-specific extensions to add classification of organizations and roles, as well as extensions to support neighbouring information such as organizational activities.

The namespace for all terms in this ontology is: http://www.w3.org/ns/org#

This document defines the Simple Knowledge Organization System (SKOS), a common data model for sharing and linking knowledge organization systems via the Web.

Many knowledge organization systems, such as thesauri, taxonomies, classification schemes and subject heading systems, share a similar structure, and are used in similar applications. SKOS captures much of this similarity and makes it explicit, to enable data and technology sharing across diverse applications.

The SKOS data model provides a standard, low-cost migration path for porting existing knowledge organization systems to the Semantic Web. SKOS also provides a lightweight, intuitive language for developing and sharing new knowledge organization systems. It may be used on its own, or in combination with formal knowledge representation languages such as the Web Ontology language (OWL).

This document is the normative specification of the Simple Knowledge Organization System. It is intended for readers who are involved in the design and implementation of information systems, and who already have a good understanding of Semantic Web technology, especially RDF and OWL.

The PROV Ontology (PROV-O) expresses the PROV Data Model [PROV-DM] using the OWL2 Web Ontology Language (OWL2) [OWL2-OVERVIEW]. It provides a set of classes, properties, and restrictions that can be used to represent and interchange provenance information generated in different systems and under different contexts. It can also be specialized to create new classes and properties to model provenance information for different applications and domains. The PROV Document Overview describes the overall state of PROV, and should be read before other PROV documents.

P-Plan is an OWL2 ontology developed to describe abstract scientific workflows as plans and link them to their past executions.

P-Plan extends the W3C PROV-O Ontology [PROV-O], which encodes the W3C PROV data model [PROV-DM]. PROV-DM describes the provenance of objects (prov:Entities) as a record of assertions about the steps (prov:Activities) that generated them and the entities used in those steps. Provenance describes past execution, but does not offer a vocabulary to express the plan that the execution was supposed to follow.