Developing an ontology involves time, effort, and niche knowledge; it can also add significant costs. One way of bringing this down is by reusing ontologies in part/on its own or with/without embellishments. However, reusing ontologies calls for conceptual relevance. Kingsley Uyi Idehen, Founder & CEO of OpenLink Software, describes different and improved ways of accessing siloed data from within domains of specialization and across different domains of specialization.
Reusing ontologies is possible in fields where there is a crossover. This is achieved by applying linked data principles to any domain to create a semantic web of linked data. A good example of this crossover can be found in the bioinformatics industry. The industry is making rapid strides by putting computational biology at the forefront of artificial intelligence, machine learning, and others. As a result, access to siloed data within and across domains has become a reality.
However, one has to look beyond a conventional single-model RDBMS that only supports SQL to make this happen. In fact, it is not even marginally achievable via the new genre of single-model DBMS projects under the “Graph Databases” banner. What is needed is a multi-model RDBMS that understands and takes full advantage of the fundamental, technological essence, which makes both the World Wide Web, and the semantic web enhancement of the linked data possible.
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