What is a Knowledge graph?
A continually changing informational structure that mediates between a human, the world and a computer
Growing the graph is based on automated reasoning and crucially, collaborative human thinking and creativity.
What is a Knowledge graph?
A continually changing informational structure that mediates between a human, the world and a computer
Growing the graph is based on automated reasoning and crucially, collaborative human thinking and creativity.
What is a Knowledge graph?
A continually changing informational structure that mediates between a human, the world and a computer
Growing the graph is based on automated reasoning and crucially, collaborative human thinking and creativity.
Unlike traditional databases, ResearchSpace knowledge graph represents data in a network of meaningful relations
- As your research evolves it is represented in an expanding knowledge graph in a reflexive process.
- Knowledge patterns capture the different ways in which events, actors, and things connect and relate across time and space.
Unlike traditional databases, ResearchSpace knowledge graph represents data in a network of meaningful relations
- As your research evolves it is represented in an expanding knowledge graph in a reflexive process.
- Knowledge patterns capture the different ways in which events, actors, and things connect and relate across time and space.
Unlike traditional databases, ResearchSpace knowledge graph represents data in a network of meaningful relations
- As your research evolves it is represented in an expanding knowledge graph in a reflexive process.
- Knowledge patterns capture the different ways in which events, actors, and things connect and relate across time and space.
Flexible semantic expressions,
instead of a predetermined model
The knowledge graph is made up of interconnected patterns the nature of which can be continually expanded using a real world ontology – like the CIDOC-CRM.
Why an ontology?
ResearchSpace uses an ontology as a framework for representing knowledge in structured information. Databases use artificial categories responsible for narrowing what can be said about the world and using conventions that don’t reflect the way we think. An ontology, instead, is concerned with existence, being and becoming, it represents reality.
Flexible semantic expressions, instead of a predetermined model
The knowledge graph is made up of interconnected patterns the nature of which can be continually expanded using a real world ontology – like the CIDOC-CRM.
Why an ontology?
ResearchSpace uses an ontology as a framework for representing knowledge in structured information. Databases use artificial categories responsible for narrowing what can be said about the world and using conventions that don’t reflect the way we think. An ontology, instead, is concerned with existence, being and becoming, it represents reality.
Flexible semantic expressions, instead of a predetermined model
The knowledge graph is made up of interconnected patterns the nature of which can be continually expanded using a real world ontology – like the CIDOC-CRM.
Why an ontology?
ResearchSpace uses an ontology as a framework for representing knowledge in structured information. Databases use artificial categories responsible for narrowing what can be said about the world and using conventions that don’t reflect the way we think. An ontology, instead, is concerned with existence, being and becoming, it represents reality.
