Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

June 11, 2014

Network Data (And Merging Graphs)

Filed under: Data,Graphs,Networks — Patrick Durusau @ 7:20 pm

Network Data by Mark Newman.

From the webpage:

This page contains links to some network data sets I’ve compiled over the years. All of these are free for scientific use to the best of my knowledge, meaning that the original authors have already made the data freely available, or that I have consulted the authors and received permission to the post the data here, or that the data are mine. If you make use of any of these data, please cite the original sources.

The data sets are in GML format. For a description of GML see here. GML can be read by many network analysis packages, including Gephi and Cytoscape. I’ve written a simple parser in C that will read the files into a data structure. It’s available here. There are many features of GML not supported by this parser, but it will read the files in this repository just fine. There is a Python parser for GML available as part of the NetworkX package here and another in the igraph package, which can be used from C, Python, or R. If you know of or develop other software (Java, C++, Perl, R, Matlab, etc.) that reads GML, let me know.

I count sixteen (16) data sets and seven (7) collections of data sets.

Reminded me of a tweet I saw today:

Glimpse Conference

It’s used to be the social graph, then the interest-graph. Now, w/ social shopping it’s all about the taste graph. (emphasis added)

That’s three very common graphs and we all belong to networks or have interests that could be represented as still others.

After all the labor that goes into the composition of a graph, Mr. Normalization Graph would say we have to re-normalize these graphs to use them together.

That sounds like a bad plan. To me, reduplicating work that has already been done is always a bad plan.

If we could merge nodes and edges of two or more graphs together, then we can leverage the prior work on both graphs.

Not to mention that after merging, the unified graph could be searched, visualized and explored with less capable graph software and techniques.

Something to keep in mind.

I first saw this in a tweet by Steven Strogatz.

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