Smart Data Management Training (1 day)

Enapso Micro-Services

“Smart Data – Profit from Knowledge“

With the digitalization across all industry sectors, the world is moving quickly into an era of smart machines and the future of services and products depends on how smart they are or will become to assist us. In this trend, Knowledge Representation (KR) plays a vital role as a fundament of Artificial Intelligence (AI), dedicated to the modeling and retrieval of information about the real world using formalisms that computer systems can understand and process. 

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This training introduces into the concepts, utilization and technologies of knowledge bases based on OWL ontologies, which are widely established and standardized by the World Wide Web Consortium (W3C). The training focuses on knowledge management using OWL2 and imparts a holistic picture of semantic graph databases, of the open world assumption and of how new knowledge is gained by inference. The training introduces into SPARQL as language to query and maintain knowledge bases and demonstrates the value of smart data and knowledge management using an online-shop ontology as a portable real life example.

Target Group

  • Software architects und developers, project managers and CTO's

Topics

  • General approach of semantic Knowledge Representation
  • Introduction to the concepts of OWL Ontologies
  • Creation and retrieval, rules and constraints of knowledge in OWL ontologies
  • Conceptual and practical knowledge about reasoners and inference
  • Introduction to the practical use of Semantic Graph Databases
  • SPARQL for knowledge management with practical examples

Achievements

  • Approach to improve data quality and ensure data integrity and consistency
  • Strategies to make knowledge re-usable and turn data to digital enterprise assets
  • Architectures to improve interoperability in heterogeneous application environments
  • Consume and provide knowledge resources and services from and to the semantic web
  • Ability to create own solutions and provide knowledge and smart services for the semantic web
  • Ability to make your web contents machine understandable and processable

Time Table

  • This 1-day training is structured in 4 modules á 90 minutes and a subsequent open time window for questions and answers as well as discussions and networking.

Prerequisites

  • Basic understanding of traditional data base and programming models

Service

  • Hot drinks, soft drinks and snacks are included


Detailed time table

  • 09:00 - 09:15 (15 minutes)
    • Welcome and Warm Up
      • Presentation
      • Introduction to the training
      • Goals discussion
  • 09:15 - 10:45 (90 minutes)
    • Module 1 - Introduction
      • What is Knowledge Representation and why it is important in the field of Artificial Intelligence
      • Terms and definitions to understand features and use of ontologies as semantic knowledge bases
      • Objectives and purpose of ontologies and benefits compared to traditional database technologies
      • Overview of ontology languages and sub-languages, using RDF/OWL as target language for the training 
      • Brief introduction to the graph theory and how knowledge is represented nowadays using graphs
      • Introduction to the “Online-Shop” domain, which is used as an example during the training
  • 10:45 - 11:00 (15 minutes)
    • Coffee Break - Discussion, Q&A
  • 11:15 - 12:45 (90 minutes)
    • Module 2 - Knowledge Modeling
      • Modeling of RDF/OWL ontologies and best practices for creation, organization and versioning
      • Classes in ontologies, what can and should be represented as a Class, how to organize taxonomies and others useful concepts
        • Disjoint between classes
        • Equivalence of classes
        • Primitive and definitive classes
        • Understanding complex classes
      • Ontologies as knowledge bases and what knowledge to represent as individuals and others important individual related concepts
        • Equality and disjointedness of individuals
        • The unique name assumption
        • Create restriction to a set of individuals using enumeration
      • Properties in ontologies and how to use them to establish links between classes, individuals and data. Further important concepts
        • Property hierarchies and inheritance
        • Using domains and ranges
        • Property characteristics to achieve semantic meanings and to manage restrictions
      • Class restrictions, using restrictions to represent semantic associations between classes and to create consistent models and the use of universal, existential and cardinal restrictions
  • 12:45 - 13:30 (45 minutes)
    • Lunch Break
  • 13:30 - 15:00 (90 minutes)
    • Module 3 - Reasoning, Inference and Semantic Graph Databases
      • Brief overview of popular OWL2 reasoners and their features
      • The open world assumption and the importance of this concept for the development of ontologies
      • Detecting and fixing inconsistencies in ontologies
      • Reading and using the reasoner’s inference explanation to isolate issues and verify inference results
      • Practical examples and explanations how to use DL queries to query and validate the ontology design
      • Using semantic graph databases for knowledge representation and differences between RDF/OWL and property graph databases
      • Introduction to Fuseki and Stardog as an open source and an commercial solution to develop knowledge graph databases
  • 15:00 - 15:15 (15 minutes)
    • Coffee Break - Discussion, Q&A
  • 15:15 - 16:45 (90 minutes)
    • Module 4 - Knowledge Management and Retrieval with SPARQL
      • What is SPARQL2
      • SPARQL as a powerful language to query and maintain knowledge
      • SPARQL examples to introduce into syntax and query logic
      • Practical compilation and execution of SPARQL queries to maintain and query knowledge
      • Named graphs, handling and joining knowledge from different ontologies with complex queries
  • 16:45 - 17:30 (45 minutes)
    • Discussions and Networking
      • Open discussion on custom specific questions and requirements
      • Best practices applied in the online-shop ontology
      • Portability of examples to other uses cases and prospects
      • Live examples and insight into tools and data on demand

Net Price (excl. VAT)1 199,00 €
Germany VAT (19%)227,81 €
Price1 426,81 €