A couple of days ago, I wrote a graphgist about creating a true Knowledge Graph for the Neo4j ecosystem. Based on the fantastic
Awesome Neo4j resource created by our friends at
Neueda/
Neueda4j. You can access it in a separate window
over here.
In this post however, I will go into a bit more detail about how I went about creating that graph.
Google Spreadsheet is my friend
I mentioned already that I started from the awesome
Awesome Neo4j github resource. And while it's a great idea to manage pages etc collaboratively on Github, I can't help but feel like there should be other and nicer ways of structuring that information. So I spent a couple of hours converting that information into a spreadsheet (which is
publicly accessible over here):
This sheet contains
- info about the resource (name and comments)
- the URL where you can find the resource
- info about the author (individual or organisation) that created/manages the resource
So it's a very, very easy graph model:
So all I needed to do was import that sheet into Neo4j. Easy...
Importing the Google Spreadsheet with Load CSV
As we know by know, it's really easy to
download a Google spreadsheet as a CSV file, and then it is pretty darn easy to import that CSV into Neo4j with
Load CSV. I have two versions of that load script:
The result is not a very big graph of course:
And now we can do some nice querying on it - just for fun!
Querying the Neo4j KnowledgeGraph
Obviously there are many different queries that we could run on an interesting graph like this. I have put a couple of them
on Github as well. Here they are:
//Find some Authors, Resources and Tags
MATCH p = ((a:Author)--(r:Resource)--(t:Tag))
return p
limit 25
Gives you an initial sample of the graph:
Then we can explore a couple of specific graph neighborhoods:
//Find some Authors, Resources and Tags connected to Rik or Max
MATCH (t:Tag)--(r:Resource)--(a:Author)
where a.name contains "Rik" or a.name contains "Max"
return t,r,a
this gets us this one:
And then we can also "recreate" a spreadsheet-like view of the graph:
//find some resources and authors
MATCH (r:Resource)--(a:Author)
where a.name contains "Rik" or a.name contains "Max"
return distinct a.name as Author, r.name as Resource, r.url as URL, r.comments as Description
order by Author;
This gets us (pitty that the url's don't get hyperlinked like they do on the graphgist):
And then finally, let's look at some pathfinding - always interesting:
//find some paths between books and blogs
match (t1:Tag {name:"book"}), (t2:Tag {name:"blog"}),
p = allshortestpaths ( (t1)-[*]-(t2))
return p
limit 10
So there you go. A first attempt at creating another graph-based knowledge repository for all things
Neo4j. Hope you guys enjoyed that. I know I did :))
Cheers
Rik
Countdown has begun! Two weeks from now we'll be bringing together the entire European Graph Community in London again, for the annual Graphconnect Conference. Every year, it's something to really live up to, to rally our customers and users to attend as we really believe in the "power of relationships" that are formed and strengthened at conferences like this.
