This webinar is recorded and available on Youtube.
The RDF data model is perceived as a powerful data model for sharing meaning. Yet, the task of generating good models is complex work, where the users should agree over reusing consistent identifiers, which is an error-prone process. With the new features of GraphDB 9.4, we aim to lower this effort by introducing important usability improvements and tools to help novice users or advanced data engineers to transform various data formats into RDF models without writing code or misspelling the ontology types or properties.
This webinar will teach you how to quickly transform various data formats like CSV, JSON, or XML into RDF without writing code and guided by the currently loaded ontologies in GraphDB. The demonstration will cover the two supported processing data flows:
- Interactive data flow – where the user controls the data cleaning, reconciliation, and transformation into RDF, which happens into the OntoRefine user interface;
- Batch processing of large data using the data transformation made by the interactive flow.
All these features are available in GraphDB Free!
What you will learn:
- About all new features in GraphDB 9.4 that help you generate RDF data from various data formats;
- How to clean and reconcile data using the OntoRefine interface;
- How to batch and process large scale data using the GraphDB Mapping API.
Who is this webinar for:
- Any novice or advanced RDF users;
- Users who want to produce RDF data from various sources quickly;
- Data engineers who want to automate data processing.
Expected duration:
- 45 minutes presentation
- 15 minutes Q&A session
About The Speaker
Vassil Momtchev
CTO
Vassil has more than 15 years in software development in various domains like life sciences, pharmaceutical, health care and telecommunication. In the past 10 years he’s mostly engaged with the development of complex enterprise knowledge management solutions that features natural language processing, text analytics, reasoning, semantics, ontology design, linked data, conceptual model design, implementation of formal grammars and graph databases.