The importance of semantic annotation of datasets

By steingod |

NorDataNet is actively involved in the ADC-IARPC-SCADM Vocabularies and Semantics Working Group which works to:

  • Promote awareness of existing vocabularies and semantics initiatives to increase effectiveness and reduce or eliminate redundancy
  • Coordinate vocabularies and semantics development activities across the polar information community
  • Enable and organise regular communication within the community
  • Help members of the community connect to useful and interoperable vocabularies
  • Inform the polar community about broader activities (e.g. ESIP, RDA), and act as ambassadors from the polar community to other initiatives


The purpose of this activity is to improve the ability of data management systems to provide the correct information to data consumers when they search for data, but also when they access and use the data. Important utilisations of controlled vocabularies, thesauri, taxonomies and ontologies are e.g. to translate between discipline specific knowledge domains, trustworthy identification of variables/parameters of a dataset and how to interpret e.g. URL's (Internet addresses) embedded in dataset descriptions, but also at the use level to convey information about units of variables, content of variables etc. All these aspects would increase the performance of user oriented services on top of published data.

In this work it is important that the scientific community is engaged in order to make sure that information content develop in a form that supports the scientific work flow. If you have comments or questions in this context please contact NorDataNet through the contact form and we will initiate a dialogue.

Within geoscience some important resources in this context includes:


In here terminology used to describe the content of variables and more is found. These vocabularies are used in different contexts, but the primary purpose is to address the I (Interoperable) and R (Reuseable) in the FAIR Guiding Principles for scientific data.