I wanted to see which programming languages are linked to the largest number of programming languages around today. Someone with a better understanding of programming languages – could you tell me more about how the color coded groups are structurally different from one another? I have a vague idea but don’t want to spout nonsense here. I had no idea about the importance of Haskell until I did this so I am glad I took the time to create this map. The node size represents the number of connections. The bigger it is, the more influence it has had. This does NOT mean these languages are “better” in any way. It simply means languages with large nodes have more connections to other languages than languages with smaller nodes. As always, be careful in your interpretation. I’ve also noticed that some nodes should be different colours – but one has to draw the line somewhere. There are also some problems with graphings things like this as there will be ambiguity.

Again – this is not accurate! I’m just demonstrating how information can be visualised. A more accurate graph could be drawn from better, more complete information.

Order of operations:

1. Went to http://dbpedia.org/snorql/

2. Entered:



SELECT *

WHERE {

?p a

<http://dbpedia.org/ontology/ProgrammingLanguage> .

?p <http://dbpedia.org/ontology/influenced> ?influenced.

}



3. Touched up here: http://meyerweb.com/eric/tools/dencoder/

4. Imported into excel, further formatting. Export .CSV. Used a combination of Force Atlas and Fruhterman-Reingold layouts.

5. Export in Preview (click to enlarge).

Update: Since I made the last two graphs, I have done another showing the various language paradigms using the information available on Freebase. Click to enlarge or click here for dynamic zoom (recommended).

Again, keep in mind the limited dataset – this is only an exercise in exploration!