Once access to the data has been ensured and the data quality has been described and improved where necessary, the next step is to model the data. Modeling linked data is often a very time consuming task, but it makes the data more widely understandable and usable both within and across organizations. When creating linked data, one should employ proper engineering practices in order to create datasets of high quality that possibly make use of existing resources on the Web rather than creating them from scratch, and express the intended semantics correctly so that others (both machines and humans) can properly understand and reuse the datasets being built to extend the web of data. In this respect, the following process should be followed for producing high quality linked datasets.
The term linking data is sometimes confusingly used, particularly because one can create “links” in multiple ways. It is also important to notice that “links” between datasets can be done at several steps in the process of data modeling. Different types of “links” can be made: ontology links and data links. We will highlight three different options to link datasets during the process of modeling data using italics.
While modelling you should put aside immediate needs of any application and be sure to test the assumptions in the schema with subject matter experts familiar with the data. It is not necessary to define the ultimate model of the data at once. More the contrary; the philosophy of linked data offers you the possibility to start without modelling the data, do it later or not, or go for a step-by step approach. Tools that help you model the data include Topbraid Composer and Protégé.
We will now elaborate in more detail on two types of ontology linking: the reuse of standard vocabularies and the creation of new vocabularies.
De activiteiten van Platform Linked Data Nederland (PLDN) worden mede mogelijk gemaakt dankzij het Kadaster, TNO, Big Data Value Center (BDVC), ECP, Forum Standaardisatie, Kennisnet, SLO, Waternet, Taxonic, MarkLogic, Triply, Franz Inc., SemmTech, Rijksdienst voor het Cultureel Erfgoed (RCE), Beeld en Geluid, EuroSDR, de KVK en ArchiXL
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