Linked Open Data refers to a set of best practices for publishing and linking data on the web, so that it can be easily accessed and reused by machines and humans alike. The goal of LOD is to create a global network of interconnected data that can be used to facilitate data integration, data mining, and knowledge discovery.
Examples of Use in Practice:
- Using LOD to create a knowledge graph of biomedical research that combines data from various sources such as PubMed, ClinicalTrials.gov, and Gene Ontology.
- Utilizing LOD to create a linked data platform for providing access to diverse data sets such as geospatial data, economic data, and social data.
- Using LOD to create a semantic web-based platform for data integration and data analytics in the field of e-commerce and retail.
- Follow the LOD best practices in terms of data modeling, URI (Uniform Resource Identifier) assignment, and linking.
- Use standard vocabularies such as RDF (Resource Description Framework) and OWL (Web Ontology Language) to facilitate data integration and knowledge discovery.
- Make use of existing LOD tools such as RDF stores and RDF inference engines to create linked data applications.
- Use appropriate licensing terms (e.g. Creative Commons) to ensure that the data is open and reusable.
- Continuously monitor and update the linked open data sets to ensure that the data remains accurate and up-to-date.