Semaphore Knowledge Modelling Workshop – September 20th, 2019

Date: September 20th, 2019
Time: 9:30 to 12:30 hours
Location: BDVC, Utrecht
Hosted by: Kenny Baird & Steve Ingram (remote)

Workshop description

Modelling what is important to your organization – topics, concepts, entities, and relationships between them – creates a complete picture of the information that organizations use. Smartlogic Semaphore Knowledge Model Management (KMM) complies with Linked Data standards and best practices. Built upon Resource Description Framework (RDF), models are expressed as triples; powerful and flexible structures, which scale to the needs of the enterprise.

Semaphore KMM is a web-based, feature-rich, modelling and collaboration platform used by data modelers to interact with stakeholders and subject matter experts to create models that accurately reflect the organization. The easy-to-use web interface is designed for business users to support a fully business-driven modeling process without lengthy training. KMM also supports text analysis/mining from existing sources to discover e.g. core concepts and alternative labels.

During this workshop you will get a first introduction to the web-based Semaphore Knowledge Modelling environment (KMM) We will cover the main modelling steps to develop knowledge models, like taxonomies, thesauri and ontologies and we will highlight the commonalities and differences between them. We will also illustrate how these models can be used to improve e.g. the search results of search engines, how to map muliple models with each other, how to link to external sources like e.g. DBpedia (and re-use content from DBpedia), how to improve the results of data analytics, etc. (or a selection of these topics given the time we have available for this workshop).

You are expected to bring your own laptop to this hands-on session, but you don’t have to install any software, since we will make use of an online Semaphore Knowledge Modelling environment for this workshop.

Smartlogic's Semaphore is een Semantic AI-platform waarmee organisaties gekwalificeerde contextuele gegevens kunnen onthullen en kennis uit informatie kunnen halen voor het verkrijgen van nieuwe bedrijfsinzichten

Resource Description Framework (RDF) is een standaardmodel voor gegevensuitwisseling op het web. RDF heeft functies die het samenvoegen van gegevens vergemakkelijken, zelfs als de onderliggende schema's verschillen, en het ondersteunt specifiek de evolutie van schema's in de loop van de tijd zonder dat alle gegevensgebruikers moeten worden gewijzigd.

Formele definitie van de klassen, eigenschappen en relaties van een datastructuur en de bijbehorende constraints als een knowledge graph

DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.