Using ontologies
What is data structuring?
Data structuring is a crucial process in connecting (integrating) data in source systems to the DataHub infrastructure. Data structuring consists of creating data element mappings between two distinct data models and is used as a first step for a wide variety of data integration tasks, including:
- Data transformation, or
- data mediation between a data source and a destination.
What is an ontology?
An ontology is a way to represent your knowledge on a specific topic that also allows you to share information using a common language. Think of it as a set of standard categories for data so our digital tools know what type of data you stored. To connect and compare data sets, they need researchers to use the same categories. In our federated data catalogue DISQOVER you can see the result of working with ontologies. If you want to read more about ontologies, we suggest reading some chapters of Semantic Web for the Working Ontologist.
Disqover
If you work with data of Maastricht UMC+, we advise you to use the ontology SNOMED Clinical Terms. This is the ontology for medical data that other researchers within the Maastricht UMC+ and researchers of other institutes use. Maastricht UMC+ data
How DataHub can help
This service is highly specific of nature, as every source system is unique. Therefore, we cannot offer a standard service and rely on one-on-one consultancy.
The power of semantic web
- Read some chapters of Semantic Web for the Working Ontologist
- Next to The Dublin Core Metadata Initiative there are a lot of domain specific ontologies
- Working with data of Maastricht UMC+ we (advise you to) use the ontology SNOMED Clinical Terms
- Our ingest webform uses the NCBITAXON
- Our federated data catalogue DISQOVER shows you some of the results of working with ontologies