Knowledge Graph
Explore scientific knowledge as a connected graph
NeoPhi helps you move beyond isolated lists of publications. Visualize the concepts that connect scientific articles to each other and identify new research directions.
What is a scientific knowledge graph?
A scientific knowledge graph is a structured representation of research information in which publications, concepts and other scientific entities are connected through meaningful relationships.
Instead of presenting each paper as an isolated search result, a knowledge graph makes it possible to explore how different elements of a research field relate to one another. It can help researchers identify influential publications, connected topics, recurring concepts and potential research paths. NeoPhi transforms the selected scientific corpus into an interactive map that supports exploration while preserving access to the underlying publications.
The graph works hand in hand with the rest of the platform: build your corpus with semantic search, then turn the connected corpus into a cited synthesis.
See the connections
Understand how publications relate to the wider research landscape
- View related publications together instead of one result at a time
- Explore connections between scientific concepts across the corpus
- Place individual papers in a broader research context
- Navigate between related areas of research
Follow research paths
Navigate between scientific concepts
- Start from a publication, concept or relationship and follow the most relevant connections
- Explore the literature progressively rather than restarting a new search for every question
- Every exploration remains connected to the scientific sources used to construct the graph
Identify patterns
Reveal clusters, central topics and underexplored connections
- Inspect groups of closely connected papers and recurring concepts
- Spot relationships that may deserve further investigation
- Use the structure of the corpus to form better research questions
Context without losing traceability
Every connection remains grounded in scientific publications
- Open publications associated with any graph element
- Review the bibliographic information behind each connection
- Move from visual exploration to direct source verification
- Use the graph to enrich your corpus
NeoPhi is impressively efficient and an excellent research tool across all fields.
List view vs. Knowledge graph
See both the publications and the relationships between them
| Traditional result list | NeoPhi knowledge graph | |
|---|---|---|
| Main view | Individual publications | Connected publications and concepts |
| Exploration | Open one result at a time | Follow relationships across the corpus |
| Context | Derived manually from reading | Represented visually through connections |
| Topic structure | Difficult to see at a glance | Clusters and related areas can be explored |
| Navigation | Return to the result page for each paper | Move progressively between connected elements |
| Verification | Open the publication | Open the publication connected to each graph element |
Main view
Exploration
Context
Topic structure
Navigation
Verification
From documents to connected knowledge
The navigable layer between search and synthesis
The knowledge graph sits at the centre of the NeoPhi workflow: build a corpus by meaning, explore its structure, then transform it into a verifiable answer.
Semantic search
Build your corpus with semantic search: full research questions in natural language.
Natural-language queries
Explore semantic searchKnowledge graph
Explore relationships within your publication corpus: concepts, papers and research directions on one map.
Connected context
You are here
Synthesis with sources
Turn the connected corpus into a cited synthesis you can verify publication by publication.
Source-grounded
See synthesis with sourcesScientific knowledge graph FAQ
What is a knowledge graph in scientific research?
A scientific knowledge graph organises research information as connected entities and relationships. Scientific concepts are represented as nodes, while meaningful connections between them are represented by the edges of the graph.
How does a knowledge graph help with a literature review?
A knowledge graph can help researchers understand the structure of a scientific corpus, explore related publications and identify relationships that may be difficult to perceive in a conventional list of results. The underlying papers must still be reviewed and interpreted by the researcher.
What can I explore in the NeoPhi knowledge graph?
NeoPhi allows users to explore the publications, concepts and relationships represented within the selected scientific corpus. The exact information available depends on the metadata and scientific content processed by the platform.
Can I open the original scientific sources from the graph?
Yes. The knowledge graph is designed to preserve the connection between the visualised information and the scientific publications from which it was derived, allowing users to return to the source for verification.
Does the knowledge graph automatically identify research gaps?
The graph can reveal patterns, clusters and weakly connected areas that may deserve further investigation. Determining whether an actual research gap exists still requires domain expertise, source review and methodological validation.
What is the difference between semantic search and the knowledge graph?
Semantic search identifies publications related to the meaning of a research question. The knowledge graph helps users explore relationships within the resulting corpus. Together, they support both discovery and contextual understanding.
Is my exploration data secure?
Yes. NeoPhi does not train AI models on user data, complies with GDPR, and offers deployment options designed for institutions with strict data-isolation requirements.
Turn a collection of papers into a connected research landscape
Search the scientific literature, explore the relationships within your corpus and continue to a structured synthesis with verifiable sources.