Podcast Interview with Dustin Cote, Luther College

I have called to him before, but I am going to do it again: thanks to the wonderful Bryce Merkl Sasaki at Neo4j, I have had the pleasure of talking to sooooooo many wonderful guests on the podcasts. People that I would otherwise probably never have talked to, for all kinds of reasons. Another one of these folks is my guest on the podcast today - Dustin Cote. An active graph enthusiast in the heartland of the Midwest - and a great knowledgeable database engineer at that, who I really enjoyed talking to. Here's our conversation:
Here's the transcript of our conversation:

RVB: 00:02.617 Hello everyone. My name is Rik Van Bruggen from Neo Technology and here I am recording another podcast session for the Neo4j Graphistania podcast. Tonight, I'm joined by someone from the beautiful Midwest in the USA. I've got Dustin Cote from Decorah, Iowa on the Skype call. Hi Dustin. How are you? 

DC: 00:25.316 Hi Rik. I'm doing great. How are you

RVB: 00:27.268 Very, very good. Thank you for joining me. It's always great to have people from different parts of the world on this podcast. I've read some of your work in the communities and in the GraphGist, Dustin, but most of our listeners probably haven't yet. Do you mind introducing yourself to us and telling us who are, what do you do, and what's your relationship with the wonderful world of graphs? 

DC: 00:53.085 All right. My name is Dustin Cody. I currently live in a northeast corner of Iowa in a small rural town by choice. I work for Luther College. It's a small, private college and just started last year. Prior to that, I was working at the University of Wisconsin-Madison and worked there for seven years as a PeopleSoft programmer analyst with emphasis in database design. Before that, I was a data warehouse administrator, and before that, I was doing stuff with databases and before that, I was learning to program in seventh grade. I've been around for a while, well seasoned as they say. That's what I'm working on, mainly because of my experience with ERP systems. Seems like no one wants to work on old technology, so there's always a niche for that. 

RVB: 01:45.121 The world would stop turning without old technology, I think. 

DC: 01:49.133 It would, believe it or not. 

RVB: 01:50.191 It would, I absolutely do. Dustin, what's your relationship with Neo4j and graph databases? How did you get into them? 

DC: 01:59.511 Very recently, there was a competition for GraphGist on Neo4j and I thought, "What a great to finally finish one of my project ideas." It had a deadline and basically, it was the only thing I needed to finish the project. I put together a conference data model, because I was going to a conference and I wanted to know different things from the booklet they gave you, but because it's in a certain order, you can't find out certain things. I knew that a graph database would be the perfect way to query on different angles and different ways of looking at your data. Before that, I would say back in 2008 when one of our companies moved and I was worried about competing against 25 Java developers, unleashed onto the town for jobs, I went back to school. Even though it turned out not to be an issue being reemployed, I continued to go back to school and get my masters. It was then that I was doing a research paper and one of the papers I was doing was to debunk over-hyped technologies. One of them was the Semantic Web. 

DC: 03:03.407 I heard of the Web 3.0 and thought to myself that this has been over-hyped. I've heard about it for years and I haven't seen anything about it. So while researching it, I realized that this is exactly what I had been looking for to solve so many of my own database projects. For example, I had some projects where I was saving just spare data. So, for instance, when you save music, MP3s or songs, it's usually saved as artist, album and song name. Well, if you talk to classical music enthusiasts, they care about orchestras and maybe the conductor, or the original composer. They look at different things, but it's the same item almost, and you still have to store it. You know, by the time I was done designing all the different kinds of genres, there was just no database for relational databases that could handle it well. And when I looked into Semantic Web, I realized that this was the solution. And back then, there was a NOSQL movement. I would say Semantic Web - since it saves as tuples or triples - I believe it's based on graph databases, a little more formal perhaps. And so my natural-- so all of the uses I found for Semantic Web I also find useful for Neo4j. And at the time, when I was choosing which graph database to use, Neo4j was the one that I had heard the most. It had the best reviews at the time. And so I decided to spend the little time I had with raising two kids to learn a new technology. And so that's why I picked Neo4j. 

RVB: 04:40.390 Interesting, yeah. It's very much related technology, and that we could talk for more than what we have in this podcast about the differences between Semantic Web databases and Neo4j, because they are quite different. But [chuckles], we'll take that off-line. But they are different but related technologies, I would say. What did you like about graph database then? What problems was it solving for you? Why was it such a good fit for some of the things that you had found problematic in other databases? 

DC: 05:18.521 One of the things I've always liked is how you can make non-obvious connections. You might have two different graft sets that are unconnected at the moment, but some time in the future if you're still collecting data you might [inaudible] two nodes together, and then suddenly your same query would return different results, and, in fact, maybe solve a problem. I think one of the examples I saw long ago was perhaps besides the NASA and CIA kind of examples, would be different language authors, and they might have a different name in one language than another. You might be following him and you suddenly make the connection and realize that they have all this other body of work. So I like those kind of solutions that the graph database is continuously growing and making connections for you. 

RVB: 06:08.085 Yes, like inferring new paths between different parts of the graph. Is that what I'm hearing? 

DC: 06:15.632 Well-spoken. Yeah, exactly [laughter]. 

RVB: 06:19.269 Yeah, well. I mean that is a-- that's one of the examples that I always give. It's like the path finding. I've got these two things and how are they connected to each other, and show me those connections. Whether you're talking about a [BR?] data set or a social network or recommendation engine, that's one of the most powerful use case-- those hidden connections as you call it. 

DC: 06:41.392 Right, and with database design, when you're working in large company, you have to spend so much time, ahead of time, designing things. And then once it's approved, and then once it's implemented, many months or years can go by and once it's done, you're pretty much nail in the coffin, and you really don't want to change it again because you don't know what you might change. With graph databases, sometimes you can add a whole new set of features or properties, and it won't affect the past data you had. It'll actually just enrich the data you have in your new applications that can leverage it. That's very powerful. 

RVB: 07:16.441 That's such a powerful point that you're making there, and I think it's also why it's like a perfect storm now for graph databases because of the whole agile developing paradigm as well. You know, people don't develop waterfall systems anymore. You know, they try to take a much more leaner approach to software development. You don't know what you don't know when you're developing a new system. It's a great fit for that, I think, as well. Dustin, where do you think this is going? Where do you, personally, want to take this? I'll put some of the links to your work on the blog post with this podcast recording, but where do you see it going? What do you want to do with it? Where do you see the industry taking it? 

DC: 08:04.811 Where I personally want to take it is, perhaps, more projects that can help categorize interests. I've been an internal description, is my industry. I'm might be interested in homesteading or something. There are podcasts out there that are in the 2,000 episode range and it would be great to be able to categorize those and find exactly what you're looking for, maybe even the author or the interviewee. Some day, maybe you'll have 2,000 interviews here. 

RVB: 08:33.387 Oh my God [chuckles]. 

DC: 08:35.375 You never know how you can tie all those people together. People bring such great resources from their work. You know, [hack the plans?], it's more like categorize the plan. I think graph databases is good for that. As far as the world's future, I think this is a tool that's generic enough and powerful enough that someone out there that doesn't even know anything about this yet is going to come up with an idea, use your project and platform, and come up with something new. It's just that kind of technology that you're creating and it's really going to be anyone's imagination really, something that we haven't even thought of yet. 

RVB: 09:18.040 Like a platform for innovation, basically? Like doing--? 

DC: 09:20.356 Absolutely. 

RVB: 09:22.665 Super relevant. I really like that perspective. I really do. I think, for example, in the past couple of months, we've seen at Neo4j when some of the Panama Papers research was published and stuff like that. That was for us fantastic validation. That would never have happened ten years ago and now it's happening because of the small contribution that we're making, I guess. 

DC: 09:49.082 Absolutely. I like your ramp up time to test out Neo4j with that web interface you have, where you can start importing right away. It's a great tool. 

RVB: 09:57.583 Very cool. Very nice. Thank you, Dustin, for spending your time with me on this recording. As you know, I like to keep these things short and snappy and digestible for everyone. We'll put some of the links to your work with the transcription, but for now, I want to thank you very much for coming online. I hope to meet you in person, face-to-face, at some point [chuckles]. 

DC: 10:21.682 It's my pleasure and keep up the good work. 

RVB: 10:23.838 Thank you so much. Bye. 

DC: 10:25.481 Bye.

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All the best

Rik

Podcast Interview with Iian Neill, The Codex

A couple of months ago someone pointed me to this great Neo4j application called The Codex - which is like a semantic application mapping out an "atlas for history". Its author, Iian Neill, recorded a great video about it, and triggered me to want to learn more about it. There's been some other Neo4j projects (like for example Historiana, which Paul worked on) in this domain, and as you will see from the interview below - there's a lot to be said about it. So let's get cracking!

Here's the transcript of our conversation:

RVB: 00:02 Hello everyone. My name is Rik, Rik Van Bruggen from Neo Technology, and here we are again recording a long-distance podcast all the way from Australia. This is actually the second week in two weeks-- the second episode in two weeks that I'm recording with [chuckles] someone in Australia. And tonight I have Iian Neill on the Skype here. Iian Neill in Brisbane. Hi Iian. 

IN: 00:25 G'day Rik. 

RVB: 00:26 Hey, thanks for coming online. I know it's early for you and it's late for me, but this is a great time for us to chat, right [chuckles]? 

IN: 00:34 Absolutely. It's certainly my pleasure. 

RVB: 00:36 Very good. Ian, we got to know each other a couple of weeks, months ago. At least I started following your projects a little bit, but it will be good for you to introduce yourself to our podcast listeners because most people probably don't know who you are yet. 

IN: 00:53 Okay. My name is Iian Neill. I'm an ASP.NET developer. I have a bit of a background in computers and arts. I've got a Bachelor of Arts in Art History, but I work in IT. I also work for a non-profit art foundation called the Art Renewal Center. But basically, yeah, I've been passionate about art history and been looking for a way to data mine it and hence Neo4j. 

RVB: 01:23 And then we should also immediately mention one of your coolest projects, I think. This is how I got to know you: the Codex, right [chuckles]? 

IN: 01:31 Yes. That's right. Yes. The Codex is something I've been working on for a few years. It's kind of evolved a bit, but it's basically a way-- it's a project I built out of ASP.NET and Neo4j using the C# Neo4j client, and it's a tool that I'm building to sort of-- I call it an atlas of history. It's sort of trying to map history out, and the connections between people and events and places and things like that. 

RVB: 02:03 Okay. And then tell us a little bit more about that. I saw there's a lot of information about like Italian Renaissance, Leonardo da Vinci, Michelangelo, and stuff like that that you're trying to map out what they're doing or what they did, right? 

IN: 02:18 Absolutely. I kind of think of it as being a bit like a Facebook of the past or in some ways even a little bit like a time machine. There was TED talk on someone doing a project a little bit like that on Venetian history.

But what I really wanted to do was to be able to put myself back in the past and say, "What was happening on a certain day?" So if I saw a certain painting, and what's the context around this painting? Who were the people? What was going on in Florence when this painting was being made? And from that, I started to build the data structure and say, "What else can we find out about this? Can we use the system to abstract out some information? Can we see connections that we might not see if we were just reading a book in a linear way?" And that's kind of what's attracted me to Neo4j. 

RVB: 03:18 Tell us a little bit more about that. What's the relationship between the Codex and Neo4j? How do you use it? 

IN: 03:24 Oh, it's completely dependent on it. A few years ago I had an idea for breaking down a person's biography or life into a series of events, and you can think of it as being a verb phrase. So X meets Y at Place Z, for example. And that's just a data structure. I mean, you have two people, you have a place, and you have a time. And that data structure can be quite powerful for representing sequence of events and connections. And you could then use Cypher to sort of query that, and say, "If I know that X was at this place, at Florence, who else was there at the same time? If X had these friends, do these friends know the other person's friends?" You know? And you can sort of-- once you start down that road, you can sort of keep expanding that with the graph, basically. 

IN: 04:18 So I started in that fashion, but then I found that it was a little bit restrictive and a little bit time consuming to take written text and break it down into that kind of atomic way. So instead, I put a different model on top of that, so I put in the event, you know, somebody's diary event for a day in 1478, let's say. And then I could annotate who was there and what was-- the places, and everything that was mentioned. Those are all nodes in Neo4j. And then I put, if you like, subject tags on top of that. So it's a little-- like you would tag a photo or a Twitter post, a hashtag, you might tag it with a description of what's happening. So if you can sort of forgive the macabre example, a popular pastime in the Renaissance was hanging people. 

IN: 05:08 So for example, you might read somewhere that somebody was taken to the public square and they were hung that day. So I started by saying, "Let's put that in there." So I would create a tag for hanging and associated it with that event on that day at that place. And then I thought, "Why not bring a taxonomy to that tag?" So what I mean by that is putting that tag in a hierarchy. So I'd ask the question, "Well, what is a hanging? Well, that's a kind of public execution, and that's a kind of death," or something like that. And I thought, "Well, that could be an interesting scholarly tool for understanding history." So you've got the text of the event, you know who was there, what they were doing, and then you can use the graph and step out by sort of degrees of separation. 

IN: 06:00 You can say, "I'll start with a specific subject like hanging and then I'll go to all kinds of executions, which could be--" they were very creative back then, so you're bringing back lots of events. And then I have followed this procedure for every tag in the system where I can. And probably the last extension I've done to that is I thought, "When you put a tag in the system, why not record a numerical quantity with that?" So if three people were hung, you could put "hanging three." And then I thought, "That gives you chartable information for three." So you have an event, you have all the people there, you have the subject of the activities, and then if you have numbers, you have information that can be visualised as charts. So it occurred to me to bring all these things together. That's [crosstalk]-- 

RVB: 06:52 It sounds a little bit-- it sounds a little bit like a semantic application, doesn't it? You know, like-- 

IN: 06:57 Yes. 

RVB: 06:56 --triples and those types of things. Is it related to that in any way? 

IN: 07:01 Yes, absolutely. Many years ago when I did my postgraduate IT degree I did a course called "Ontology and the Semantic Web", and that's kind of where it all came from. It was about ten years ago and we used a language called OWL - I think O-W-L - as a modelling language. And I thought it was amazingly powerful for expressing real relationships. And then I was really disappointed to see that there was no practical database out there that could do that kind of thing. It was just sort of SQL. And I sort of failed to translate the Owl model into SQL in an efficient way, and I kind of put it aside. But then a few years ago I came across Neo4j and that seemed a good time to pick it up again. 

RVB: 07:49 Well, that's a perfect segue for my second question. It's, why Neo4j? Why did you use a graph database for this particular project? And then what's so good about it? Any comments on that? 

IN: 08:06 Well, I mean, originally it just started as a side project. As I said, I started with that sort of data structure, that X meets Y at a place. And originally, I just wrote it as a kind of MapReduce-style thing and JavaScript just using JSON, and just querying it through lambdas and so on. And it was always going to be temporary; it's just a in-memory JavaScript. And I started looking around, thinking, "Is there a database that can do this?" And I heard about NoSQL document databases, and I looked into Mongo and RavenDB. But what I found when I looked into Mongo - I read an interesting post; I will try and dig up the link later - is, it was by somebody who had used Mongo extensively and I think they thought that Mongo would be a relational kind of system for them, that it would have some of the power of-- the relational ability of SQL databases. And they realised that it didn't really have that. And I thought, "That's great. I won't go down that road." And then somebody in the comments recommended Neo4j, so I started looking into Neo4j. And it seemed to me the perfect intersection of the power of representing things in a document style and a graph style and then having the relationships as well that make it incredibly fast to query and update. 

RVB: 09:28 Very cool. So it's kind of like what I've heard many people on the podcast say: it's a combination of good modelling fit and then on the other hand, there's also just query power, right? Query possibilities that match this domain really well. 

IN: 09:45 Absolutely. And just to quickly round that up, but I was saying before, I was lucky enough to sit in on a talk that Jim Webber gave in Brisbane that was related to the YOW Conference in I think 2013. And I already knew about Neo4j at the point but going to the talk really convinced me. Jim gave a great description, gave lots of examples from Doctor Who (dataset is over here), which is wonderful [chuckles]. [crosstalk] you'd think.
RVB: 10:15 [chuckles] Yeah. Yeah.
IN: 10:17 And then he gave me a copy of the book as well, on graph databases, and it really went from there. It was absolutely decided that I was going to do that with Neo4j. 

RVB: 10:28 It's so funny. I mean, two weeks ago I spoke to two fellow Australians from Melbourne, and they as well got inspired by that tour that Jim did in-- 

IN: 10:40 Yes [chuckles]. 

RVB: 10:40 --2013 in Australia [chuckles], so it's been a productive visit, that one [chuckles]. Very [good?] [crosstalk]. 

IN: 10:47 Absolutely. 

RVB: 10:48 So the last question I always ask people, Iian, is what does the future hold? Where do you think this is going? Where is your project going and where do you see graph databases as part of that project going? Any perspectives? 

IN: 11:05 Sure. I've got a few plans with Codex. I want to continue-- I want to add the ability to put in more, what you might call, arbitrary data sets. So rather than just having events - you know, what people were doing - I want to be able to put in things like if somebody gave me a record set of births and deaths, or disease, epidemiology figures, or something like the spread of a plague or something, I think it would be possible to integrate that into the system so you could switch between data sets, you could be looking at somebody's life story but then also looking at more official statistics as well. So that's kind of where I'll be taking it in the next few months. One thing I've discovered working on Codex is that-- one thing I didn't expect from Neo4j was that it's such a good tool for modelling that in a way, you can almost-- in most domains, you have one database for one domain. 

IN: 12:12 You have a shopping cart and you have an art gallery collection or something like that, and you sort of think about them as being two separate databases. But with Neo4j, I've found that you can think about it as being one database. You can have multiple domains that if you define points of where they interface - certain commonalities like time or space or location - you can easily take the domain you started with and add other domains to it, so it becomes kind of what I think it was being, like an integral or universal database in a way. I don't know if that would be appropriate for every solution, but I think it's something that Neo4j offers that I think would be very difficult to do with another database. 

RVB: 12:58 Very cool, very cool. Well, thank you so much for talking about all of this. I really appreciate it. As you know, I try to keep these podcasts quite short so that they are digestible on everyone's commutes, you know what I mean? So we're going to wrap up here, but I really want to thank you again for coming online. Good luck with the Codex and all of your projects, and hopefully we'll get a chance to meet each other at some point. That would be great. 

IN: 13:28 That would be fantastic. And thank you, Rik. 

RVB: 13:31 Thank you. Bye-bye.

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Rik

Podcast Interview with Jesus Barrasa, Neo Technology

Over the past couple of months, we have been doing a lot of work at Neo4j to try to better explain the value of Neo4j to our prospects and customers. This has been a true team effort, with lots of engineers, marketeers and sales folks participating in articulating how complex technology can be used to add true value to business processes. And as we did that, we added some really talented people to our team. One of them is the person that I am interviewing in this particular podcast episode: Jesus Barrasa. Jesus has a lot of experience with graphs and even (a particular kind of) graph databases - so going in I knew it was going to be an interesting chat. And guess what: it was. Listen on:

Here's the transcript of our conversation:

RVB: 00:00 Hello everyone. My name is Rik, Rik Van Bruggen from Neo and here I am again recording a Neo4j graph database podcast and my guest today is all the way in the UK. Jesus, hi Jesus. 

JB: 00:13 Hi Rik. How are you? 

RVB: 00:14 Hey. I'm always scared of pronouncing your name in the wrong way. I'm sorry. 

JB: 00:19 You did great. You did great [laughter]. I've heard much worse than that so that was brilliant. 

RVB: 00:24 Okay [chuckles]. Okay, Jesus, you just joined Neo a couple of months ago as a pre-sales engineer but you have a long-standing history with graphs. You did a PhD on the subject if I'm not mistaken, right? 

JB: 00:37 That's correct, yeah. It all started probably more than ten, nearly 15 years ago, so quite a while yeah. 

RVB: 00:43 Yeah. 

JB: 00:43 And you're right. It all started in the semantic technology space, in the RDF space, so that was the first time I was exposed to modeling data as graphs and yeah. That's been a long story. After the PhD I did work for a company in London called Ontology where we did use graphs to best resolve problems in companies, mostly in the telecommunications sector and yeah. As you say, two months ago I joined the field engineering team in the London office. 

RVB: 01:18 That's super. What was your PhD about exactly then? 

JB: 01:21 Well, at the time… I did model-- I mean, I formalized a way of translating relational schemas into ontologies. Ontologies is the way you represent metadata in the RDF model. I don't know if we will have time to talk about that but yeah, it's actually an automated mapping between relational schemas and ontologies. That's what I-- 

RVB: 01:45 There's a lot of people looking at that I think, still today, I get that question quite often. 

JB: 01:50 Absolutely. 

RVB: 01:51 So another question because you've been working so long in the RDF world, what's the difference between the RDF semantic technology space and the property graph model of Neo4j - what's the key difference for you? 

JB: 02:04 All right. I'd say you can answer this question from two perspectives because obviously RDF is a presentation paradigm and there's the different implementations, the triple stores that you can find in the market but as a model I think the main thing they have in common is the fact that they both represent data as a graph. And that makes them very, very close to each other. The difference I would say is RDF is simple as it can be. It's only based on the notion of URIs to identify resources or nodes if you want to establish the properties with a property graph but there's this element called triple, subject, predicate, object. And that's all the constructs that you have to model your domain. And of course I think that's the biggest difference because in the property graph model, you have nodes with properties, you have relationships with the properties and they have this brilliant thing that's this white-board friendliness, this excellent thing that's the way you conceive it, the way you model it in your head, in your whiteboard, is exactly the way it's represented and stored physically, whereas in RDF there's still this gap where you have to translate that into triples, things that may sound simple like giving a weight to a relationship so there's a connection between Rik and Jesus because we work together. You want to give weight to this relationship. That's something that's completely natural in the property graph but it's not something you can do directly on a triple, so you have to model this relationship probably as an intermediate resource. There's a bit of a gap and I think that makes it sometimes less intuitive, sometimes a bit less humane if you want. So that's the difference. 

RVB: 04:06 Well [crosstalk] actually that was sort of what I was hoping you would say because I've always been told that the difference is really on the predicate, the fact that it's so difficult to qualify a predicate in the RDF model. 

JB: 04:20 That's [crosstalk] exactly. Then there are other interesting things in RDF, the whole idea of being able to use the model itself to represent the metadata, the ontology and that gives you in certain cases some interesting powerful things you can do like querying all the data and the metadata at the same time. But I would say the biggest thing is more what they have in common and it's the fact that they look at data as a graph, a set of connected nodes. 

RVB: 04:49 What attracted you to the graph in the first place? Why did you get into this field in the first place if you don't mind me asking? 

JB: 04:55 Well, yeah, sure. I think there's two things. One was this incredible flexibility. At the time when I started we didn't talk about NOSQL. That's a concept that was coined later. It's the idea of being able to start storing data without having to model it up front. I thought that was brilliant and that gives you an incredible flexibility, this thing of schemaless model or at least implicit schema depends on how you talk about it but this flexibility was one of the things and the other one, I'd say the possibility of infering new knowledge based on the information on your graph, you identify patterns and you can enrich your graph with new knowledge based on the data elements that you have. So I think probably these two things attracted me to this world and I find them unbelievably useful and powerful. 

RVB: 05:51 You know, as your couple months at Neo, what do you think is the most interesting use-cases that you've seen so far? Anything that jumps out? 

JB: 06:01 Sure. Well, I'm amazed-- the thing is the great thing about Neo is how you can use and update your graph in real time, at what speed you can not only read it and query itbut also keep it up to date and how it's possible to identify fraud rings for example is one of the cases that I like the most, being able to pick up the status of your accounts, your users, their information, the transactions that they're carrying out, and at the same time be able to pick up, detect the patterns that identify a fraud ring is one of the ones that I enjoy the most. 

RVB: 06:43 And do that in real time you mean? 

JB: 06:44 Exactly, the real time is the key thing and that's pretty impressive yeah. 

RVB: 06:48 It's not like with my experience a couple of weeks ago with my Amex card, I get a fraudulent transaction on Friday and I get a call on Monday [laughter]. 

JB: 06:57 Oh yeah, just in time right. 

RVB: 06:59 Just in time [laughter]. Didn't really work. Very cool. So where do you see this going, Jesus, where's the industry taking us do you think? 

JB: 07:09 Well, I think adoption is growing. It's amazing the number of different organizations and companies that we talk to. I can't think of a single vertical, a single sector that would not benefit from scenarios where modeling data as a graph adds incredible value, so I think adoption will definitely grow and that's one of the things, and then the other one that I think is going to be key as well is about integrating the graph with the rest of the data architecture. These days there are so many alternatives to represent data and some of them adequate for certain scenarios. I'm all for peaceful co-existence with all the other approaches. So integration I think is going to be the other important one and I think being able to expose the graphing in ways that make it easy to inter-operate with other stores, sometimes not all of the information is going to be in your graph but the extremely valuable information in your graph will need to be combined with some external information. That's one case where you will want to visualize it in different ways using BI tools, well you name it, there's so many elements now in data architectures that integration I think is going to be the other important aspect that we'll see developing in the next few years. 

RVB: 08:22 There was one thing that I wanted to ask you and I obviously forgot. I'm so good at this podcasting thing [chuckles] is actually you've done a lot of work on virtualization of data, right and then [crosstalk] integrate and that links to that integration story I suppose. 

JB: 08:36 Exactly. Exactly. I did work in the data integration space with a data virtualization company in the couple of years between Ontology and Neo and yes, I'm particularly interested in that and it's a way of integration data virtualization that's based on this idea of wrapping the sources and make them look as if they were relational even though they're not so they're not copying the data into centralized stores. You leave the data where it is and you define the logic to extract it and combine it and I think that was a powerful paradigm for new ways of representing data like the graph and make it easy to integrate them with other technologies and other types of stores and yes. 

RVB: 09:27 So in a case like that the Neo4j would be one of the sources of virtualization? Is that what I'm--? 

JB: 09:32 That's correct [crosstalk]. One essential one, that's the thing because the importance in the end is what value is there in your source? Neo can be perfectly, for example, in an MDM scenario. It can be the core. It can be your master model. And you can link it with the different rest of it and provided the detailed information about the entities but exactly, it would be one of the sources and the data virtualization will expose it in a way that's easily consumable by say for example BI tools in analytic scenarios or that's one of the-- 

RVB: 10:05 Are there any examples of that yet? You know, like open-source virtualization tools that integrate with Neo [crosstalk]? 

JB: 10:10 Well, there's not much to be honest. There's one quite limited community edition of one of the vendors called Denodo which is the one I used to work for. There's another one from JBoss but I'd say there's not much, Rik, available in there. I mean, JBoss would be the obvious option. I'm actually now trying to work a little bit with it and try to build some integrations with Neo and yeah. That's what you can find. 

RVB: 10:40 I think this is kind of like community call for help, you know [crosstalk]. 

JB: 10:45 Yeah [crosstalk]. I definitely really hope to be publishing something soon, at least in some idea, some small examples that can inspire people to look at these. 

RVB: 10:55 That would be great. Cool. I think we're going to wrap up here. I think we like to keep these podcastsquite short and snappy but thanks a lot for sharing your perspective. I think that was very interesting although because of my limited presentation skills a little bit chaotic [laughter]. 

JB: 11:13 Right. No, it was great [chuckles]. Great to have this chat with you Rik. 

RVB: 11:15 Thank you, Jesus. And I'll see you soon yeah. 

JB: 11:18 Lovely. Cheers. 

RVB: 11:19 Bye. 

JB: 11:20 Bye now.

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