Other meanings of Linked Open Data
Semantic Web
Linked Open Data (LOD) is a method of publishing structured data so that it can be interlinked and become more useful, building on the principles of the Semantic Web. It combines the idea of Linked Data—using Uniform Resource Identifiers (URIs) and Resource Description Framework (RDF) to make connections between data—with the requirement that the data be openly licensed and freely accessible. By following a set of best practices, LOD enables data from different sources to be queried and integrated in ways that are impossible with isolated, siloed datasets.
Linked Open Data is a subset of Linked Data that is published under an open license, making it freely available for anyone to use, reuse, and redistribute. The core principles were articulated by Tim Berners-Lee in 2006: use URIs as names for things, use HTTP URIs so that people can look up those names, provide useful information when a URI is dereferenced, and include links to other URIs to discover more data.1 These principles are often referred to as the "Linked Data rules" and are the foundation of the Semantic Web vision.
The technical stack of LOD relies on standard W3C specifications, including RDF for representing statements as subject-predicate-object triples, SPARQL for querying RDF datasets, and the HTTP protocol for dereferencing URIs. Datasets are often published as RDF dumps or through SPARQL endpoints, and they can be interlinked by using shared vocabularies such as Dublin Core, FOAF, and Schema.org.2 The Linking Open Data community project, started in 2007, has been instrumental in creating a cloud of interlinked datasets, now known as the LOD cloud, which includes contributions from government, libraries, and scientific communities.
LOD has been adopted in various domains, including government open data initiatives, digital humanities, and life sciences. For example, the U.S. government's Data.gov publishes many datasets as LOD, and the European Union's Open Data Portal follows similar principles. In the life sciences, the Bio2RDF project integrates over 30 biological databases using LOD techniques, enabling complex queries across genomic, proteomic, and pharmaceutical data. Libraries and museums use LOD to link their catalogs to external resources, enhancing discoverability and enabling new forms of scholarly research.
Beyond the well-known LOD cloud, there are several niche applications and historical nuances. The term "Linked Open Data" was popularized by Berners-Lee's 2006 design note, but the concept of linking data predates the web, with early hypertext systems like Xanadu. A lesser-known fact is that the LOD cloud diagram, maintained by the LOD project, is itself a dynamic visualization that has evolved over time, with datasets being added and removed. Another edge case is the issue of data quality: because LOD is open, it can contain errors or outdated information, and there is no central authority to correct it. This has led to research on data provenance and trust in LOD. Additionally, some datasets are published as "Linked Data" but not "Open" due to licensing restrictions, highlighting the distinction between the two terms.3
This article focuses on the method of publishing structured data as Linked Open Data, distinct from other uses of the term.
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