Networks

From Impure Wiki

basic network structures: Node, NodeList, Network, Tree

Networks are complex structures, at least more complex than Lists or Tables. But they are extremely important. Neurons, genes, phones, people are structured in networks, not by lists.

One issue when working with networks is that it´s not easy to find network data, in opposition to numerical or text data. Major data repositories (see Where to find interesting and specific data? below) offer data in table formats such as .csv. Formats for networks, instead, are rare. We expect the arise of social networks and apis for services such as Facebook, will make data networks standards more common.

In the meanwhile impure allows you to load the most common and simple network data formats: .gdf and grapML.

But what is much more interesting is that impure comprehend several ways to create networks. First of all, when you download a RSS feed, the generated data structure is a Network instead of a table or a list. The nodes of this Network are contents and tags. From this Network you can create a new Network of contents (creating relations whenever two contents share tags) or a Network of tags (creating relations whenever two tags share contents).

Two lists define a network (relations between pairs).

With a table with two lists and a NumberList that somehow express the proximity between the pairs of the list you can build a Network with weighted relations.

From a NumberList it´s also possible to create Networks: comparing each pair of NumberLists and calculating its statistical correlation or its distance, and creating relations when these values overpass a given threshold. In general terms, when you have a distance criteria for certain type of elements you can build a Network from a List of these elements.

Nodes are very dynamical structures, they are different from the the other structures in many ways.

Their main properties are: id (String), name (String), description (String), weight (Number). They have other properties such as url (String).

Relations are Nodes, and they have two nodes associated that defines a relation beteen them.

You can visualize the properties of a Node with the NodeVisualizator or the NodeListVisualizator.