Data structure and knowledge representation · BEGINNER LESSON
Knowledge graph
A knowledge graph is a structured way to represent knowledge as entities, relationships, and attributes in a network. It is used so people or computers can query and reason over connected information.
What it is
A knowledge graph is a structured knowledge representation made of entities, relationships, and attributes. Entities are things such as objects, events, situations, or concepts; relationships connect them; attributes add details. In the sources, knowledge graphs are also described as nodes for entities and edges for relationships, which makes the structure easier to store and query.
[1] Application scope of knowledge graphs in nursing - PMC [2] pmc.ncbi.nlm.nih.gov › articles › PMC13180881Research information systems and knowledge graphs: a review [3] 3 Results
What it is measured or used for
A knowledge graph is not a physical object measured with one single instrument. Instead, its usefulness is judged by what it can represent and support: semantic query, reasoning, comparison of research content, integration across sources, and, in some systems, machine-actionable access. In biomedical text work, it can help capture interactions from literature as structured statements.
[1] Application scope of knowledge graphs in nursing - PMC [2] pmc.ncbi.nlm.nih.gov › articles › PMC13180881Research information systems and knowledge graphs: a review [3] 3 Results
How it works
Knowledge graphs work by linking pieces of information into a network. In research systems, they can connect publications, datasets, identifiers, methods, variables, and results across different databases. In biology, a knowledge graph can encode subject-predicate-object statements, where the predicate names the relationship. This supports more specific queries than simple metadata links, such as asking which method gives the highest accuracy for a condition.
[2] pmc.ncbi.nlm.nih.gov › articles › PMC13180881Research information systems and knowledge graphs: a review [3] 3 Results
Mechanisms and construction
The sources show several ways knowledge graphs are built. Some are made from ontology design, entity and relationship extraction, and data fusion. Others use shared ontologies, schema mappings, persistent identifiers, REST APIs, OAI-PMH harvesting, SPARQL, and GraphQL endpoints to connect data across systems. In scientific text mining, language models can extract statements from publications and encode them in Biological Expression Language, or BEL, which uses a subject-predicate-object structure.
[1] Application scope of knowledge graphs in nursing - PMC [2] pmc.ncbi.nlm.nih.gov › articles › PMC13180881Research information systems and knowledge graphs: a review [3] 3 Results
Limitations
The evidence in nursing is still exploratory, with most studies focused on construction or usability rather than controlled tests of real clinical effects. The sources also note data incompleteness, lack of standardized terminology, semantic differences across systems, and difficulty separating the effect of the knowledge graph itself from teaching methods or novelty. Because of these issues, many claims about practice impact remain unverified.
[1] Application scope of knowledge graphs in nursing - PMC [2] pmc.ncbi.nlm.nih.gov › articles › PMC13180881Research information systems and knowledge graphs: a review
SEE THE IDEA
How a knowledge graph organizes information
A thing being represented, such as a gene, method, publication, or concept.
A link showing how two entities are connected, such as affects, describes, or compares.
Many linked entities and relationships together.
Questions and inferences that use the connected structure.
Entities are linked by relationships to form a network that supports querying and reasoning.
This simple flow shows how separate items become connected knowledge rather than isolated records.
TRY IT YOURSELF
Test your understanding
Choose an answer, then check the explanation.
PUT IT TOGETHER
Match each concept to its meaning
Drag a label onto its description, or select a label and then select a description. This also works with a keyboard.
4 pairs to match
Sources and further reading
This general lesson was generated from public source material. It explains a concept; it does not interpret a private paper or provide medical advice.