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serve as access points to data, establishing paths that enable users to discover enough information to help them make use of data. Let’s return to the examples previously mentioned and see how using linked data helps. In the case of ambiguous column labels, such as ‘value’, there would be a URI instead of a string. A URI is a link you can follow to get insight into exactly what it’s supposed to mean. When we come back to the second example, we apply the same procedure and use a URI instead of the string ‘London’. Then by resolving that URI, we can provide additional information, such as GPS coordinates or boundaries, which is needed in order to tell which one of the cities named ‘London’ is meant and what’s its area. As illustrated above, a key to the solution proposed by linked data is to make relationships between data and its described domain explicit by expressing them as links. For this solution to work, open availability of links and the data they identify is required. The same principles of open access should apply not only to data but also to its accompanying description. Therefore, relationships described by links should also be available under the terms of an open licence. These paths need to be openly accessible in order for the data to be open to use. This is why linked open data is important. Knowing how the web of data is related to the web of things is an essential insight for turning data into networks of actionable knowledge. Inaccessibility of relationships in data is a barrier to use. We need to tear down this barrier and open the network of relationships in data for both humans and machines to leverage.
Jindrich ˇ Mynarz is a PhD student in Applied Computer Science at the University of Economics, Prague. As a researcher in the Knowledge Engineering Group, he explores linked open data with a focus on the intersection of public procurement and e-commerce, looking into the ways in which semantic web technologies can make public sector data more useful.
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