- Improved consumption of data assets
- Increased efficiency by encouraging data consumption and reuse
- Constant quality improvements
The Goal
A leading STM publisher needed to make available its data assets by exposing them to consumption for internal and external customers. Their aim was to become a data authority and enable the creation of diverse applications, by encouraging data consumption and reuse.
The Challenge
The required knowledge platform had to be able to store the data as RDF documents and to allow easy ingestion of data. It had to support a long list of functional and operational requirements such as:
- Efficient data import
- Semantic data modeling and integration capabilities
- Rich data consumption interfaces, including full SPARQL support and SOLR connector
- Very high service availability and replication to multiple data centers
- Excellent cluster stability
- Processing of daily updates and quarterly major data source releases efficiently
- Easy system setup and deployment automation
- Minimal operation support and system administration efforts
- High-quality developer support
The Solution: A Knowledge Platform Powered by a Highly Scalable RDF Database Engine
Ontotext GraphDB successfully covered all the project’s highly demanding requirements and was chosen by the STM publisher as the best RDF database engine to power their knowledge platform. On top of that, Ontotext provided their migration service to ensure a smooth transition and delivered high-quality operational and developer support during the system setup, performance testing, and system acceptance tests. It also optimized and fixed the compliance of all system SPARQL queries.
Business Benefits
- High availability of services
- Rich data consumption interfaces
- Superior semantic data modeling and data integration
- Easy update and maintenance
Why Choose Ontotext?
Ontotext GraphDB and data publishing services helped the STM publisher to prepare, organize, enrich, and publish datasets and associated metadata via a single, standard-compliant interface. This approach enabled wide data use and reuse, further enrichment, extension by linking with other datasets, and constant quality improvements.
