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Using graph as a fundamental representation for data modeling is an emerging approach in data management. In this approach, the data set is modeled as a graph, representing each data entity as a vertex (also called a node) of the graph and each relationship between two entities as an edge between corresponding vertices.
Graph-tool, a free Python module for manipulation and statistical analysis of graphs. NetworkX, an open source Python library for studying complex graphs. Tulip (software) is a free software in the domain of information visualisation capable of manipulating huge graphs (with more than 1.000.000 elements).
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
Activity diagrams [1] are graphical representations of workflows of stepwise activities and actions [2] with support for choice, iteration, and concurrency. In the Unified Modeling Language, activity diagrams are intended to model both computational and organizational processes (i.e., workflows), as well as the data flows intersecting with the related activities.
The Resource Description Framework (RDF) is a method to describe and exchange graph data. It was originally designed as a data model for metadata by the World Wide Web Consortium (W3C). It provides a variety of syntax notations and data serialization formats, of which the most widely used is Turtle (Terse RDF Triple Language).
Attributed graphs are, by their versatility and expressivity, the best-adapted for this type of modeling, where graphs which can rightly be called cyber-physical do not merely capture weakly structured about a physical system, as would be the case with a knowledge graph, but attempt to directly capture the structure of a physical system, as ...
A meta model is a model of the constructs of a modeling system. Like any model, it is used to represent and reason about the subject of the model - in this case IDEF1X. The meta model is used to reason about IDEF1X, i.e., what the constructs of IDEF1X are and how they relate to one another. The model shown is an IDEF1X model of IDEF1X.
UML class diagram of a Graph (abstract data type) The basic operations provided by a graph data structure G usually include: [1] adjacent(G, x, y): tests whether there is an edge from the vertex x to the vertex y; neighbors(G, x): lists all vertices y such that there is an edge from the vertex x to the vertex y;