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https://github.com/rreusser/graph


https://github.com/rreusser/graph

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README 

        
The goal of this project is to allow visualizations of large

networks in the browser. 



We implement query processing on the gpu, to allow users to interact

with graphs far larger than before. This allows to see structure and 

substructure of the graph in realtime, for hundreds of thousands of edges.



Previous javascript based graph visualization libraries do not support this,

and are not dynamic at scale.



By computing dynamic position and layout on the cpu, you must

choose between realtime response times, and 



This system is designed specifically for longitudinal networks, and sparse

matrices. Both of these data structures do not play well with conventional 

analytics techniques. Visualization can help analysts understand these data

structures better.



circular by degree

edge weighted + springs

radial tree

orthogonoal

inverted self organizing map

kcore decomposition



https://msdn.microsoft.com/en-us/library/system.data.dataview(v=vs.110).aspx



relationships, transactions/trade, protein interactions, 

network traffic

events + meta data

To answer your questions, at Periscope I've seen:

1. A line graph of amplitude over time. You should see the frequency emerge clear as day. If you want to calculate frequency explicitly, you could overlay a second line with its own axis. Again, super simple, but gives you the answer directly.

2. I've seen a lot of fancy graph visuali

zations, but nothing that makes me happy. Depending on what you want to know about your graph, maybe a simple table with a structure like:

  [node name][node name][weight]

Or:

  [timestamp][node name][node name][weight]

A pivot table on top of this data, transoforming the second node column into the table's horizontal axis, can also be useful.

3. OK, obviously I think Periscope is a great choice here. Loads of data analysts use it to visualize time series data on many tens/hundreds of billions of data points.

That said, other good choices are: Excel, R/Stata/Matlab, gnuplot, Apache Pig. And for the data storage itself, IMO Amazon Redshift is unparalleled.

https://networkcube.github.io/networkcube/web/demo.html?session=0&datasetName=demo_scientists

https://rreusser.github.io/smoothly-animating-points-with-regl/

http://www.visualcomplexity.com/vc/project_details.cfm?id=925&index=925&domain=

http://flowingdata.com/category/visualization/network-visualization/

http://crunchbase.linkurio.us/demo/

http://www.informationisbeautifulawards.com/showcase?award=2016&page=1&type=awards

http://www.complexification.net/gallery/

http://www.trustlet.org/downloaded_epinions.html

https://www.fastcodesign.com/3068474/the-real-difference-between-google-and-apple

https://codepen.io/mikola/pen/BRQdEa

https://cscheid.net/2016/09/12/hashedcubes-simple-low-memory-real-time-visual-exploration-of-big-data.html

https://gephi.org/

https://en.wikipedia.org/wiki/Graph_drawing

https://netlytic.org/home/?page_id=2

https://medium.com/@Elijah_Meeks/interactive-applications-with-react-d3-f76f7b3ebc71

https://github.com/regl-project/regl/blob/gh-pages/example/graph.js