Live online training meant to teach you how to develop a small Proof-of-Concept that utilizes the power of Semantic Technology and GraphDB.
The idea behind the previous training-related blog posts – What Will You Learn & What is a Successful Semantic Technology PoC – was to introduce a more detailed look into the upcoming training Designing a Semantic Technology Proof-of-Concept. This blog post examines the role of Ontotext’s leading experts in the training.
When we were conceptualizing the idea of the training, in the beginning, we went over a few setup scenarios. All of them recognized the need of dedicated individual time as essential to providing targeted guidance and feedback in the process of developing a small but effective Proof-of-Concept. For the upcoming training, we will offer 15 individual consultations to the first people to request them.
The individual consultation takes about an hour. It is a chance for the participants to go over their project’s specific objectives and scope and discuss Semantic Technology implementation as well as data challenges with domain experts.
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 others.
Below are some of the many Semantic Technology professionals who had a leading role in Ontotext’s major business cases such as AstraZeneca, BBC, Financial Time and Babylon Health. You will have a chance to talk to them after subscribing for this training.
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.
Todor has multiple successful projects behind his back in data integration for life sciences, including highly scalable sequence repositories, semantic meta data integration of biomedical entities, interactive visualization of data. He participated in the specification, implementation, deployment and the support of the first National Health Portal and Integrated Personal Health Record in Bulgaria.
Project lead: KConnect
Other projects: LarKC, Linked Life Data
Ivelina has experience in various projects for semantic textual enrichment and document classification. Her main expertise is in the area of information extraction such as named entity recognition, event recognition and relation extraction with state-of-the-art natural language processing techniques.
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.
Projects: Financial Times, IET, QTLeap Project