# Graph-based Data Structure

A Graph-based Data Structure is a data structure that can contain graph data (which represent a graph).

**Context:**- It can support Graph Data Structure Operations, such as:
`add_node`

,`add_edge`

, ... - It can range from being a Directed Graph Data Structure (such as a Tree DS) to being a Undirected Graph Data Structure.
- It can be used to represent a Tree Data Structure, such as a Decision Tree Data Structure.
- It can range from being a Labeled Graph Structure to being an Unlabeled Graph Structure.
- It can be managed by a Graph Data Management System.

- It can support Graph Data Structure Operations, such as:
**Example(s):**- an Acyclic Graph Data Structure, such as a lattice data structure, and a text graph data structure.
- a Makefile.
- a Graphical Statistical Model Structure.
- a TensorFlow Graph.

**Counter-Example(s):****See:**Graph Data Pattern, Graph-based Knowledge Representation System, Hypergraph.

## References

### 2017

- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Graph_(abstract_data_type) Retrieved:2017-6-8.
- In computer science, a
**graph**is an abstract data type that is meant to implement the undirected graph and directed graph concepts from mathematics, specifically the field of graph theory.A graph data structure consists of a finite (and possibly mutable) set of

*vertices*or*nodes*or*points*, together with a set of unordered pairs of these vertices for an undirected graph or a set of ordered pairs for a directed graph. These pairs are known as*edges*,*arcs*, or*lines*for an undirected graph and as*arrows*,*directed edges*,*directed arcs*, or*directed lines*for a directed graph. The vertices may be part of the graph structure, or may be external entities represented by integer indices or references.A graph data structure may also associate to each edge some

*edge value*, such as a symbolic label or a numeric attribute (cost, capacity, length, etc.).

- In computer science, a