Tuesday, 14 January 2020

Graphistania 2.0 - Episode 3 - This Month in Neo4j

Happy new year everyone - although it actually seem like the holidays are already very far behind us! But great times were had, at least in my family, and so I feel super energised to make 2020 another great start to a decade of graphs :) ... Here's to that!

It also means that we are continuing to see all these awesome community stories pop up left right and center in the Neo4j "This week in Neo4j" developer newsletter. And so on our Graphistania podcast, we are going to continue talking about these on a monthly basis. So that's what we're doing - and I have again invited my friend and colleague Stefan Wendin to join me.

From the newsletter, we always select a few stories that we think will be more interesting and/or meaningful to discuss. This month, we found a number of them, and the interesting thing was that the graph-stories seemed to play at very different scales... The Personal, Corporate, and Society levels. Here are some of the ones we liked:

At the Personal scale
At the Corporate scale
At the Society scale, we saw some amazing posts:
So I think you agree that we had plenty of stuff to talk about. Let's get into that!


RVB: 00:00:00.732 Hello, everyone. My name is Rik, Rik Van Bruggen from Neo4j, and here we are again recording another Neo4j Graphistania podcast. It's been a month or so, and we've got the third edition in the making here of our new Graphistania podcast v2 where we basically take a look at all the wonderful things that have been happening in our Neo4j community, in "This week in Neo4j", the TWIN4J newsletter. And we're kind of mesmerised about that. And to do that, I have my wonderful guest on the other side of this call, and that's Stefan Wendin. Hi, Stefan.

SW: 00:00:42.600 Hi, Rik. Nice to be back again. A new decade, right? Let's make things--

RVB: 00:00:46.642 New decade.

SW: 00:00:47.705 Yeah, very excited. So still a little bit slow in the head but what's better to start things out than thinking about graphs. So yeah, super excited.

RVB: 00:00:58.755 Super. Thanks for joining. Well, as last two times, we've got some amazing stories that have come up in the TWIN4J, the This week in Neo4j newsletter. And I'll post all of them on the blog post that goes with this recording, but it's basically three types of stories that we're going to cover and there are different scales, right? The first one's going to be at a personal scale. The second one's going to be at the corporate scale. And the third one is going to be at the society scale. And that's where we'll cap it off. Intergalactic scale, we'll do next time. Is that okay?

SW: 00:01:41.385 Yes [laughter]. That's the one I'm looking for. Why didn't we start with that? That was better. Let's retake everything and start over. No, let's post it for next time. Now, we have a cliffhanger also. Those kind of things.

RVB: 00:01:51.856 Yes, exactly. Exactly. So we'll start with a very small and personal story. There was a guy called Alex Woolford who was doing some cool stuff with Neo4j analysing his home network and also doing some event-driven parenting [laughter]. That was really cool, wasn't it?

SW: 00:02:11.440 Yeah. Yeah. No, I like Alex and the way he kind of put his YouTube videos together, it was super simplified. It was technical on a good level but also very easy. You can really see. I think one of the interesting part is when he start to add for the cluster - I'm not going to give away everything here - but when he added Louvain, for example, as a brilliant way of clustering things. And the speed and the clarity of how easy it is, it was one of the things. And it really comes alive in the video. So I thought it was a really good and interesting way of seeing those algorithms at play and how it really helps and how it usually unfolds in colours instead of the-- I think it was the blue he used for that, yeah.

RVB: 00:03:00.609 For the next example [laughter], right? And I love how in that little video with his boy [laughter], it's got very little to do with actual graphs and Neo4j but how he would, as a real engineer, basically manage his boy's PS4 time based on his grades and stuff like that. I love that. I don't know if it will work with my kids, to be honest.

SW: 00:03:32.841 I think it was good because it also reminded me of this old story. I just came to think of it now as we were speaking, this Mats, Ibelin. I don't know if you know this World of Warcraft player that died a couple of years ago.

RVB: 00:03:47.205 Yeah, I've heard of that.

SW: 00:03:47.522 And he has this degenerate muscle disease, right? So his parents was very-- in the beginning, going like, "Oh, don't go gaming online. Why don't you go out and see the real life?" What every parent say to all the kids. What did we say in every generation, right? But then at the funeral, a lot of friends showed up. And the parent kind of rethink because he was living a whole other world in this other world. So I think this is a beautiful reminder. And it comes into a little bit of a graphic thing because we always say that powerful insights comes from multiple sources, right? So now, it's only the PS4, which is connected to the grid, but then if you add other things to it, you start having smarter insights. So it's also kind of a reminder of if you just have this kind of binary on-and-off kind of thing, it will become very stupid. But imagine how it would be if we added other things like how much he moves and basically, a tonality of what he writes with friends, scripting his messages. Maybe that's a little bit too much digital parroting going on there, but you could just imagine how you can enrich this whole thing. And very easily, it becomes a very smart thing, right? So I think this is also kind of cool.

RVB: 00:05:04.089 Kind of cool, absolutely. It's something to read up on. And let's take it to another scale, Stefan. There was another series of articles where people were talking about how they're using Neo4j in their companies, right, at the corporate scale, right? One of them was talking about in the IT department, how they were managing some certain infrastructure components, VMware services, stuff like that. But there were also some business stories, right, around analysing customer journeys and using augmented reality and stuff like that. What did you think about those? How about those use cases?

SW: 00:05:41.011 Yeah. No, the IT one I saw, and this is something I come across a lot. But I was more interested in this kind of online customer journey thingy and then using, of course, AR and VR to it. Again, using graphs, it really changed the way I look upon this. So this is very much what would have been in my domain for a very long time. And I always come back to this idea that a lot of marketing and these kind of things are based upon personas. Personas that say very little about you as a human being. But instead of looking on the way I interact and the way I interact with others, that would tell the story. So basically, this idea of emergent theory, right? So the creation of sophisticated behaviours and functions which is formed by interaction of large groups of simple elements. And maybe this is a little bit of a stretch calling humans simple elements but if you think about it, one human compared to thousands of humans or millions or whatever you want to do, it becomes much smarter, right? So I think this is also interesting to kind of map how we interact based upon others instead of looking upon I happen to be a white male living in Stockholm and wearing a black turtleneck and then being able to visualise that in 3D or AR/VR, which is also kind of interesting. So yeah, this is also something I see a lot of, the struggle or something, a really strong need from companies and organisations to look into.

RVB: 00:07:06.371 Yeah, got it. What did you--?

SW: 00:07:09.285 What did you think about this and did it--?

RVB: 00:07:10.333 Yeah. No, I was really-- so first of all, graphs are always so nice to work with, not just because of the structural element but also the visual element, right? I mean, I've always thought that that was a fantastic quality of graphs and graph databases is that you can just look at these links, their associations, relationships explicitly in the data. It's just a very natural way for people to interact with things. And then if you start to apply that in these journeys but also-- and this was maybe another level of applying it with these digital twins, right? These wind farms and the subsea gas terminals and all of those things that you can basically look at as things connected to other things. It becomes extremely powerful. And the visual aspect of graphs, it continues to amaze me because whether we know it or whether we like it or not, it's a very powerful characteristic. People underestimate it sometimes. Especially technicians, IT people, they will say, "Well, it's just another visualisation." No, no, no, no. It's actually a great visualisation. It's a visualisation that really changes people's understanding and their insight of a particular domain. And then you can't just-- it's actually really, really meaningful.

RVB: 00:08:46.813 And actually, this is a nice segue, right? I mean, the last level of kind of applications that we saw in these newsletters was not just the personal scale or the corporate scale but it's the society scale, right? There were some really cool posts about people using graphs for things that are way bigger than themselves like this one thing about visualising breast cancer data, for example. I mean, it's a crazy story, isn't it?

SW: 00:09:26.012 Yeah. And I think this has two of the components I love working with graphs and also working at a company as Neo, enabling me to be part of this kind of almost saving the world in a sense, right? So we can all see persons and we don't have to overthink to see somebody that has been affected by cancer. I can give you, without even thinking, 10 in my very close-- and neighbour and things. So I think this is, of course, one of the things. And also thinking back on the last stuff I did in December, I was speaking at this big gala event instead of Emil that was supposed to do it, but then I took it. And at the end of that speech - I did a keynote - I got the question, "So who is the coolest companies or clients that you have worked with?" And of course, we can, but we can't also mention the one that we work with because that's also one of the best perks of Neo. A lot of it is secret.

RVB: 00:10:24.211 Yeah, exactly.

SW: 00:10:24.635 But then I was actually thinking there's a list of very cool companies that we cannot mention. But one thing that I-- and this was my reply because at the moment, we were doing, I think, roughly 20 projects helping curing cancer, some which has very, very good chance of actually removing and making you better. So that was one of the things that I was really proud of. And another kind of cool thing, this comes out of, I think, from this global graph hack challenge, right? So the simplicity and how graphs also enables other-- and I think this also comes across when you start reading this, how it also opens up for others to take part of this. And I think that was also very, very beautiful on that case. So yeah, I really spent time on it. And I really like it, so.

RVB: 00:11:12.278 Yeah, so good.

SW: 00:11:13.053 It's also one of the cool things, yeah.

RVB: 00:11:14.593 Yeah. And then there's also examples like that, right? I mean, curing cancer, if we have a 1% contribution to better cures for cancer, I mean, that's already massive, right? That's already a big result.

SW: 00:11:29.793 Yeah. That's extremely massive. Yeah.

RVB: 00:11:32.435 Exactly, right? And it's the same thing with this other story that was in the news that was around, yeah, these Twitter accounts that are pushing for war with Iran, right? Crazy story. We saw something very similar a couple of years ago when the 2016 US elections were influenced by these Russian troll farms, right? But if we can analyse Twitter data, for example, or social network data, better with a tool like Neo4j and by doing so, have a 1% contribution to having a better democracy, I would settle--

SW: 00:12:12.454 Yeah, that--

RVB: 00:12:13.281 --for that in a heartbeat, right? It would be so cool. And it feels like we are doing stuff like that. We, perhaps, are being used for the society-scale use cases that have this massive impact. And I just love that.

SW: 00:12:28.938 Yeah. Yeah, and I think it also shows that-- now, again, with this-- but it's very easy to, as you said, think of this Russian Twitter troll kind of thingy. But also, I was thinking the one that we covered a couple of episodes back about lobbying, for example, in the US. So what we start to see is this how graphs can also help kind of shape or visualise in a sense or make sense of, perhaps is a better phrasing, of what's already going on and how this is, again, one thing that should be almost mandatory for government to have a democracy in 2020, right, to be able for the people to see what is actually going on, who is influencing what, and what is it that drives decisions. So I think this is use--

RVB: 00:13:16.388 Super cool, right?

SW: 00:13:16.992 We see the beginning of something. Almost, for me, this is like the beginning of the written world, a world in a sense, right? So now, we start to see this coming to shape, and we start to see and analyse the networks of things and how they interact and influence each other. So yeah, I need to ping city hall again to make sure it happens here in Stockholm in Sweden.

RVB: 00:13:39.194 Same here. I'll do the same for Antwerp. Hey, Stefan, I think we've got so many cool things happening. It's a great way to start the millennium, the millennium, the decennium [laughter]. But yeah, some really cool stuff out there, which we'll publish in the blog post that goes with this podcast. For now, I think we've given our listeners quite a bit of stuff to read up on, to watch, to think about. And I think we'll wrap up right now. Thank you so much again for joining this podcast. I really appreciate it.

SW: 00:14:15.060 Yeah. Thank you. Let's make next time even better, right?

RVB: 00:14:21.400 That's what we'll do, for sure.

SW: 00:14:21.842 We promised something. It was the intergalactic scale next time or something.

RVB: 00:14:26.588 Intergalactic.

SW: 00:14:27.002 Let's see how we can get-- how we can get out of that one.

RVB: 00:14:30.003 Good. Let's do that.

SW: 00:14:30.645 Cool.

RVB: 00:14:31.339 All right, thank you so much, Stefan.

SW: 00:14:32.205 Nice speaking to you.

RVB: 00:14:33.056 I'm stopping here.

SW: 00:14:33.075 Bye-bye.

RVB: 00:14:34.304 Yep. Right.

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All the best

Rik

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