Designing Semantic Technology Proof-of-Concept

The live online training that will help you deliver a successful project.

Live Online Training 4: Designing Semantic Technology Proof-of-Concept

The registration for this training is currently closed.

Detailed Curriculum

Pre-class assignments (recorded sessions):

  • Semantic Technology overview:
  • Making the most of Semantic Technology;
  • Managing data as a graph;
  • Explaining Semantic Web standards (RDF, RDFS);
  • Defining schemas (Ontologies fundamentals, OWL, SKOS);
  • Querying data with SPARQL (query types, patterns, and modifiers);
  • Using and publishing Linked Data and Linked Open Data;
  • Success stories overview: AstraZeneca, FT, BBC, DSP, LinkedLifeData;
  • GraphDB overview: features, setup and configuration, examples;
  • Two hours worth of tailored SPARQL exercises (+ sample solutions) to get comfortable with designing and executing queries.

Live Class Sessions:

  • Designing PoC with GraphDB (1 hour):
  • Extract, Transform and Load (ETL) your data with GraphDB OntoRefine;
  • Merge and isolate data from multiple sources (using named graphs);
  • Find what you have – explore data in GraphDB;
  • Infer new data facts using basic ontologies;
  • Visualize data (SPARQL queries results);
  • Integrate new resources from LOD;
  • PoC design practical session (3 hours) – following the workflow above as a group we will clean, transform, enrich & link a rich (movies) dataset and explore how semantic technologies enable us to discover hidden insights about the data.
  • Lessons learned; Q&A (30 m).

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What is a successful Semantic Technology Proof-of-Concept?

 

Who is the training for?

Building a successful PoC requires a good understanding of the technology basics, as well as its practical implementation. This training covers both aspects in a concise, yet comprehensive way. We will help:

    • product managers,
    • system architects
    • developers
    • academic researchers
    • data scientists

to agree on their PoC functional design.

Although you will need to have some basic understanding of Semantic Technology, no detailed knowledge is required. All advanced concepts exposed in this course will be explained in sufficient detail.

Ivelina Nikolova, PhD.

Individual Consultation

The training can be followed by an individual 1-hour consultation (included in the price) to turn the acquired knowledge into a practical solution to a specific business case. We will be able to offer only 15 spots for individual consultations for each training.

As part of the consultation, we will:

    • review your custom project goals;
    • help you draft a possible implementation plan that makes a practical use of Semantic Technology;
    • outline potential challenges of implementation;
    • define a strategy for success.

Get a chance to address your project’s specific requirement with our experts in the domains of Life Science, Healthcare, Publishing & Media, Natural Language Processing, Text Analysis, Ontology and Vocabulary Management and more.

Training Instructors

Georgi Georgiev

Georgi is a leading expert in technical programming, technical architecture, linked data, cognitive technology, and text analytics. He is the author of more than 60 research and industry publications on today’s hot topics of machine learning, algorithms, linguistics, big data, analytics and Semantic Technology.

Vladimir Alexiev, Lead of Data and Ontology Modeling Team

Vladimir’s experience includes ontology engineering, metadata standards, vocabularies and thesauri, RDF, RDFS, OWL2, SHACL, SKOS, SPARQL, LOD, mapping, R2RML, ETL, semantic web applications, project management, business analysis and requirements specifications. He has worked in various business domains, from Customs and Excise,to Personal Finance workflows, to Legal Procedures and Statistics, to Cultural Heritage and Digital Humanities.

Ivelina Nikolova, Senior NLP Engineer

Ivelina has over 10 years of experience in natural language processing. Recently she has been focusing on the application of NLP techniques for enhancing semantic technologies, which is also the topic of her Ph.D. thesis. Her expertise in semantic annotation and information extraction is the result of numerous research and commercial projects in domains like news & media, financial, biomedical and cultural heritage. In these areas, she sets to solve problems related to named entity recognition, relation extraction, and event modeling.

Vladimir Alexiev, Lead of Data and Ontology Modeling Team

Alex has an MSc in Computing from Imperial College London and is currently a Ph.D. candidate, with a focus in Computational Linguistics and, more specifically, Word Sense Disambiguation with neural networks. He has worked on information extraction and machine translation projects, as well as on building lexical semantic language resources (such as a Bulgarian version of WordNet). He also has a strong background in Theoretical and Applied Linguistics.

What

Live, online training tailored to meet one single goal – to help you deliver a successful Proof-of-Concept that uses Semantic Technology and a graph database for your business case. Teaching time is 9.5 + 1 hours including:

  • Pre-class assignments: 3 hours of video tutorials + 2 hours of practical assignments;
  • A live class session: 4.5 hours;
  • An individual consultation session (optional and limited to 15 people): 1 hour.

When

  • Online, self-paced course: Thursday, June 21-29
  • Live session with hands-on demonstrations:
    • Option 1: Wednesday, June 28 | 9:00 GMT – 14:00 GMT
    • Option 2: Thursday, June 29 | 15:00 GMT – 20:00 GMT

Price

  • Business or private: € 390;
  • Academic staff (students, researchers, professors, teaching assistants): € 240;
  • Groups of at least 3 participants from one organization: € 340;

 

We had undergone an excellent training on introduction to semantic technology, and this gave a deep insight to RDF, ontologies and GraphDB’s behaviour and semantic technology.

Sreejith K, Team Lead, Impelsys

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