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Nick shares how he is seeing the search landscape change and how data will be the foundation for companies moving forward as the customer experience becomes fractured. Finally, they have a conversation about Amazon and how they are disrupting the ecosystem.

Some of my favourite moments in the conversation with Nick include:

“There’s so many different places we are finding now to interact with the web, and I think that’s the big change that we are having to deal with. It’s not so voice itself, isn’t the biggest change. It’s the fact that internet has lept out to being something contained on your laptop or your phone to be something that just surrounds us, and it will be on every billboard, every bus stop, every screen.”

“[In the EU],  there are pretty stringent controls on Google in terms of how much news, how much of a snippet, how much is fair use, how much is just taking advantage of the publisher and then taking their information. I think this is, again this is going to be the fight. It’s going to be the fight that the affiliates have had for years. They have been dealing with this for a very long time, they have been producing the content, they have been doing the work and they have a pull/push, good/bad relationship with Google where they kind of, cede some control to get more visibility. Now brands, they are kind of engaged in that same kind of you know, fight with Google, you know, how much can we give Google, how much can we still retain control? This will be something that we will have to think about a lot, and this will feed into the whole data issue if you lose control of your content, you also lose control of the data surrounding your content.”

If you’d like to listen to this interview in Podcast form, check out Connecting the Digital Dots, Interview with Nick Wilsdon on Spreaker or search for it on Google Podcasts. Enjoy the conversation!

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Martha: Hi and welcome to Schema Stories. It’s Martha Van Berkel, the CEO here at Schema app and I am delighted today to be joined by my friend Nick Wilsdon. Welcome Nick.

Nick: Hello Martha, I am glad to be here as well. Thank you.

Martha: Nick and I had the pleasure of speaking at Tech Retail in London, U.K in September and had many fun conversations out of where we thought this world of structured data was changing and how it played a role in data architecture and thought we’d share some of that conversation with everyone today. So, Nick, to start off, why don’t you introduce yourself and tell us a little about what you do in this area of SEO?

Nick: Yeah, absolutely Martha. My background is primarily SEO. It’s been about 20 years nearly in this field. My current role is cross Vodafone Group. So, I work across all markets globally, 27+ markets. In terms of search products any kind of project or innovation project around search and SEO.

Martha: Excellent. So, today we’re going to talk a little bit about the changing landscape and specifically the roles that the structured data is going to play and maybe a little bit of background on sort of Nick, your journey with structured data sort of when did you first learn about it, and start using it.

Nick: Oh, that’s a very long time ago. Yeah, it’s hard to put my finger on when it all started.

Martha: I know it was like 2012-2013 when we were starting to deal with it. So, I imagine you were in the same boat.

Nick: Yeah, must been around then. It was very interesting idea the fact that we could then markup certain bits of information, to give that information away in a way Google understood and I remember back then, Yandex back then was looking at it in Russia . So, it makes sense, but I don’t think we looked at it initially for locations, for addresses I think if I had to guess, my first usage of Schema would be for addresses and business names. It seemed to make a lot of sense and I think we saw initially really though something where you get clear advantage in SEO over your competitors because your information was marked up in that clearly understood way by the search engine. So, it’s very much search engine optimization in the very traditional sense.

Martha: And do you think about it differently now? Was 2018 an interesting year? In fact, I was talking to someone who would reach out to us his past year you know 2019 is going to be the year of Schema Markup and structured data and I sort of chuckled, I said “I was thinking 2018 was going to be the year of structured data and Schema Markup!”. How did you see things change from when you first started using it and as it accelerated like this past year ? Could you talk a little about your perception of that and its relevance to the business?

Nick: Absolutely. It has certainly changed. It’s gone from being something where you are sort of marking something for advantage in Google, to where organizing data and organizing your information. Now that’s sort of a dramatic change. I think we’ve seen that especially really with things of voice coming into the picture where we are starting to see how to mark up specific information for voice. Schema is going to take a much wider usage really, I think across websites, across all information – it is now information management technique, categorization technique. Now Linking between those different entities and make sure they make sense to search engines. So, taking on a much wider appeal. And it’s certainly crossing many more fields from just location pages and store pages to something that you use across entire site for products, for any kind of information you can think of really the way that it’s expanding.

Martha: So, it kind of brings me to a question I often have which is like, is structured data really just an SEO strategy now, right? Like with in Vodafone like who else is involved in these discussions because of the changes it has started to make?

Nick: Yes, not just an SEO thing at all, it is sort of becoming a proxy CMS really for data isn’t it. It involves many many different teams now in terms of getting that Schema implemented and these are requests I’m seeing coming from the development side as well because they want to write semantically and the ones right in a way that makes sense. So, it’s not questions that are only coming from SEO teams. I think SEO is still primarily the driver of Schema because you need to have sort of value proposition behind schema and certainly, we will understand that it’s making website information more understandable to Google. That’s great, you need to have a kind of business aspect to this as well and I think SEO kind of gives you that in a sense we have added this to our websites we will get kind of more visibility and more traffic. Actually, not just more traffic, but the better kind of traffic, because we define our information in a better way.

Martha: Yes, quality traffic!

Nick: Exactly it’s quality. I think SEO still kind of drives schema adoption, but certainly, it has a wider appeal now than it used to.

Martha: One of the topics you and I spoke about at tech retail that was a little disruptive to the people who attended was I made the blank statement, “You’ve lost control of the customer experience.” Let me clarify. What we are talking about was how people are finding answers in search right or going through other channels like voice. As a result, people are getting some of the information they are looking for without ever getting to your website.  This makes me think of schema as a data strategy, right? I think about sort of the change in search, sort of almost like supporting that it is a data strategy which then leads to the next big question of like, are websites relevant? Or people are just going to consume the data with context and understanding,  through those different channels or through the channels they choose?

Nick: Yeah, now you are right. I think this is kind underlines the dilemma that publishers have really with Schema. How much do I mark up my information and just give it away to other services, give it away to Google?  Because once I have marked up everything in a way that Google can understand, they can simply take those snippets and put them into the SERPs and then no longer need to send traffic to my website. This is the dilemma that all people have if I  categorize too much have I given everything away to third-party platforms. This is a dilemma for a lot of publishers. But I am in a similar boat to you Martha, I think you can’t really think in that way because SEO is about being discovered in lots of different mediums and ways and not only search results. Speakable markup, it very much in line with that. You need your information data to be found in many other places. It needs to be portable and this portability provides the value so you can’t hold on to, too tightly to the fact that people aren’t going to come to your website. You need to be focused entirely on am I getting the sales, am I getting the conversions that matter. If I am getting these conversions through partnerships with third parties, who are taking part of my data, somehow the sale is still coming through to the business and that’s what really matters.

Martha: Revenue becomes the ultimate measure, right? And a lot of these other things really truly becomes vanity metrics, right?

Nick: Absolutely, it has to be revenue, has to be about being discovered in all these different platforms and mediums, you know from voice to all forms of search. Yes, it has to be revenue and not simply traffic.

Martha: It comes back to SEO kind of getting tough on those ROI numbers, right? Because the actual endgame is key. We mention voice and you know, Amazon has kind of, come in like a ten-ton truck, right, into the voice base. They are also owning the distribution channel from a retail space which I think is also interesting. When we started thinking about how you are ordering through your Alexa that revenue is going through that one channel. How do you think about Amazon? Amazon doesn’t necessarily have a search engine, although have been partnering with Bing. How do you see Amazon disrupting the search landscape?

Nick: They are certainly leading in terms of product discovery and I think when we’re seeing surveys from Jumpshot (survey last year), the majority of product searches actually carried out on Amazon, they are not carried out on Google. And that doesn’t really come as a surprise when you look at Google’s products’ offering is clearly inferior to Amazon’s. So, I think product discovery happens on Amazon, and I think that is the way they can really disrupt this with voice. They dominate at the moment for a voice tech, they clearly have the most distributed devices. Even though, you know, Google has technically more, because they have the phones thrown into those numbers.  Amazon is way ahead. So, I think Amazon is going to disrupt search a lot because they are going to be focused on the product and if they focus on the product, that’s where the money is. If anyone knows how the web develops, you follow the money. So, that’s the threat really that Amazon has. But I can see that they’re incredibly interested in Schema, they are incredibly interested in owning a knowledge graph around products and they can probably do that in a better way than Google can. At the moment they have got far more data to work with, far more historical data to work with.

Martha: Yeah that’s interesting, we’ve seen them hiring, semantic intelligence and knowledge engineer. Since we play in that world. So, it’s interesting starting to see more people who are knowledge engineers coming from the Amazon side. I think it will be really interesting, right now we don’t see them necessarily publishing a lot in how do I adopt structured data more around skills. Can you see those worlds, merging or do you see Amazon starting to publish more about how they are using it?

Nick: They are using a lot of data in different places. Amazon is an incredibly exciting company at the moment,  they fascinate me. I think they are looking at the crossovers between these. I mean, I saw something literally the other day something that I thought was brilliant. Amazon was releasing advertising for relaxing sounds and relaxing sleep albums that they have now released because they can sense there is a demand for them. I find it absolutely fascinating that it coincides with the demand that you can clearly see in terms of the top skills for relaxing sounds and for sleep-related skills that are available in the ecosystem. You are kind of left wondering whether one is informing data on the other.

Martha: Is that circle.

Nick: Yeah, it’s that circle. It like what they are doing with the skills. They have done this before in terms of sales. When something sells particularly well on Amazon, Amazon then releases it as an Amazon product so you can find the Amazon USB cables and all these things available because Amazon can clearly see as a need. And then they are very commercial company and they step in to fill that need. So, I think they will do that in a much better way, and it comes back to the point about the kind of following the money. Amazon is very good at following the money. That’s kind of where they are quite a big threat to Google, who would probably do this more for a sort of wider, more educational kind of piece or…

Martha: … or to make money in ads

Nick: I shouldn’t give them that much credit…yes money in ads, exactly, Martha.

Martha: I believe they follow the money too. It will just be really interesting how that business model gets disrupted with these new channels consuming information. So, the question I like to ask is you know, will websites be relevant in three to five years?

Nick: Yes, I think they will. They’ll still be there but there will just be one place you update your data to. But I think websites themselves will more likely to follow a kind of methodology, being more database driven. So, all of your data is held in central CMS (ie. headless CMS). You will concentrate more on the data and the website will just be one place,  one container, that you port your data to. But you will have your data in a fluid way that can really be ported around every other screen that will be there – from our voice tech to your screen that will be around different rooms or in the back of your car. There are so many different places we are finding now to interact with the web, and I think that’s the big change that we are having to deal with. It’s not that voice itself, is the biggest change. It’s the fact that internet has lept out to being something contained on your laptop or your phone to be something that just surrounds us, and it will be on every billboard, every bus stop, every screen. It’s just going to surround us now the internet. I think when you have an environment like that, your data has to be portable to survive in that environment.

Martha: … and control how it’s understood, right? I think that’s a lot how we look at it. How do you actually build in those control points to add context, especially as it becomes globally relevan?. And the portability is also really interesting from the standpoint of licensing. So, that’s something else we’ve been looking at is, when it stops becoming just like the primary place, people are consuming and if Google is then reusing that data in different ways, how do you also put control points in sort of understanding who can license it and who can use it.

Nick: Yeah that’s the issue that the EU is having, particularly only. So, there are pretty stringent controls on Google in terms of how much news, how much of a snippet, how much is fair use, how much is just taking advantage of the publisher and then taking their information. I think this is, again this is going to be the fight. It’s going to be the fight that the affiliates have had for years. They have been dealing with this for a very long time, they have been producing the content, they have been doing the work and they have a pull/push, good/bad relationship with Google where they kind of, seed some control to get more visibility. Now brands, they are kind of engaged in that same kind of you know, fight with Google, you know, how much can we give Google, how much can we still retain control? This will be something that we will have to think about a lot, and this will feed into the whole data issue if you lose control of your content, you also lose control of the data surrounding your content. You are not collecting that data on the users who are engaging with your content and often that’s the biggest value that publishers have.

Martha: Understanding that audience.

Nick: Reselling that data.

Martha: Absolutely. Nick, this has been awesome. Thank you. We will leave it at that sort of scary thought of the future and Google or Amazon friend or foe and how do you take control of your data. Nick if people want to follow you or find you online, where do they look?

Nick: Yeah, absolutely. I am on Twitter a lot. So, feel free to follow me on Nick Wilsdon on Twitter or you can find me fairly easy on LinkedIn or NickWilsdon.com.

Martha: Excellent. Thanks, so much Nick. Hope you have way less snow in the U.K. than we do here in Canada today and look forward to continuing the conversation.

Nick: Brilliant, thanks Martha. Take care. Cheers.

At Schema App, one of our core values is to always be learning and teaching. That’s why we love talking with other structured data experts!

The post Interview with Nick Wilsdon – Data Portability & Google/Amazon Friend or Foe [Podcast & Transcript] appeared first on Schema App Solutions.

The post Interview with Rob Bucci – Keywords to Topics appeared first on Schema App Solutions.

Martha: Hi and welcome to schemas stories. My name is Martha van Berkel and here we interview people who are thought leaders in the schema markup and structured data world and today I’m absolutely delighted to welcome my co-founder Mark van Berkel. Welcome Mark.

Mark: Hi Martha.

Martha: So, let’s kick off and talk a little bit, have you start by just telling us a little bit about yourself, a little bit about your background.

Mark: Sure.  So, I started off as a developer and spent a few years doing custom development. In 2005 started Master of Engineering. So, there I started to learn about semantic technologies way back in the day. I was 13 years ago and did a proof of concept for SP research labs which was really interesting and that kind of whet my appetite for getting into it, but we were a little early even in those days of course with the tools that were available. Spent a few more years doing consulting and other kind of IT projects and then 2012 started Hunch Manifest and started rolling through some different ideas and eventually landed on the Schema App idea. So, yeah, I guess my background; developer first and I was into a technical team leads architecture really interested in the information architecture especially and kind of the interplay between semantic technologies and the rest of the world.

Martha: Fantastic and so tell us why did you build schema app? Where did that come from?

Mark: Good question. Well, while we started the business in 2012, I hadn’t yet determined, or we hadn’t determined what we’re going to actually build and sell and what was going to take off, so we had tried a couple of ideas. One of the ones was in 2013. I had built a kind of a little gadget which would help some of our marketing clients to help get found on the web and it was specifically very narrow. We were looking at home and construction businesses and this is back in 2013, so we were trying to create the kind of templates for schema markup and sort of put it in the hands of those people who need help getting found online. So, that was a very early days and it was just kind of an interest of mine, but it was about a year later when I was at SEMTECH BIZ conference in San Francisco where there were a few different thought leaders again in kind of the intersection of semantic technology and SEO. I believe J Myers from Best Buy was there, Barbara Starr and some other person on the panel and I’m forgetting who it was at this moment but it was kind of an interesting intersection because they were even articulating how few people there were that lived at that intersection. So, coming from the semantic technology background was like “Oh well. This is something that’s very interesting to me and something that we can work on”. So, it was from that I started to—I introduced a JSON-LD schema generator. So, this was in 2014 but it was still a bit premature. So we were at a conference later, probably a year later after that first one, I met Aaron Bradley at the conference and he’s like “Oh.  That’s a great little tool” and he wondered though if Google was using it to reward companies with Rich Snippets and the answer at that point was like “No. I haven’t seen evidence of that actually yet.” But, so, we were a little early with the JSON-LD product but from there it was just kind of like—Google then did support it and then it was like “Okay well, it’s game on. Let’s really get this schema product and schema vocabulary into the hands of a lot more people. So, for me it was just how can I make it a lot easier for adoption; Where marketers who maybe don’t have the IT resources to build into their site how do we kind of start getting some robust schema markup into their hands and then also for the experts. How do we enable them to do the more complex things but at a scale that is otherwise quite difficult to achieve? So, to us that’s really where I think you know we’re providing a lot of value and where we continue to kind of build out our products.

Martha: Now you kind of skipped over the fact that you also built it for you to use, you know, as we found ourselves as a digital marketing agency. Do you want to talk a little bit about sort of the challenges when you first started schema markup and then we’ll transition to talk about like some of the biggest challenges of doing it at that scale?

Mark: Yeah. So, we had a period of two years roughly where we were a marketing agency providing kind of SEO and email marketing strategies and services and where this was something that we often recommended clients to take a look at. We did want to include schema markup among their kind of tactics and so for me it was kind of a productivity tool. How can I generate the schema markup a little quicker. So, at the time, there was no generators out there and there was one actually by Raven Tools, but it was very limited in its scope. So, I wanted something for the whole vocabulary, so I could more well describe all those businesses that we were doing marketing services for, so describing all their services and all the products with their additional attributes and properties and all those things is where like the juicy details live, where you can actually really articulate something and again Google was moving quickly—they’re introducing new features. So, for us it was a productivity tool, so how can I generate it and then also maintain it. That’s a big part that I think is overlooked. It’s great to generate and copy and paste code in but what happens next month when the rules change or the vocabulary changes like what do you do to go back and update all that stuff and I’m not really interested in doing a lot of maintenance as my co-founder can attest in terms of like doing work over and over again. I’m really happy to figure out how to solve it once for a bunch of people so that now with kind of this database generating tool we can then actually query the data, update the query or update the data on the fly and kind of make the maintenance a breeze rather than having making it a pain and actually overlooked.

Martha: You talked to me a little bit. You talked a lot about maintenance as being one of those big challenges when you’re starting to do schema markup more and more detailed as well as that scale can you talk a little bit more about sort of other challenges you’ve seen working with sort of global clients around doing schema markup at scale and perhaps how you ever come though at those challenges.

Mark: So, I guess primarily there’s a bit of a divide between marketing and IT – like marketing wants to adopt all these tools, all these features so that they can get the latest from—the latest features from Google and yet IT wants to be in control of the technology. They want to be the ones calling the shots and the implementing and sometimes there’s a bit of a tension between the want to go fast and while also maintaining, you know, maybe the stability of the system and kind of maintaining like that which IT does often and does well. So there’s a bit of this tension and that’s kind of one thing that we often deal with is how do we kind of speak to the IT team with how they can and are still playing a role among the roles and the different ways in which they may want to think about this. There’s a whole lifecycle approach to this—like you know there’s probably four different steps to the lifecycle of your schema markup. There’s one about determining what’s your strategy; what are the things you’re going to mark up, what are kind of the content things that you may want to adjust in your HTML,  secondly there’s the generating part—like how do you actually map the data that you have into the schema markup, then there’s also a reporting kind of aspect to this. A third step, so like how do you know that and how do you measure that it’s been implemented. How do you know like the depth or the breadth of your content and schema on your website. And then there’s also the reporting and then leveraging this, so once you have all this schema markup you can then repurpose it for analytics or repurpose it for chatbots. There’s always so many things they’re going to add on and this kind of expansion opportunity that IT doesn’t look at. So, they [IT] look at like the second step. Marketing might look at the first step which then marketing might say okay here’s what we want to mark up and then IT says okay well here’s your generated code but then they wave their hands and they’re done. So you know, how does marketing kind of keep on top of the quality of that content – is it meeting the needs they want and are they actually then repurposing it to kind of make the best use of all this rich information. So that’s kind of like I guess overall like we see that over and over this kind of pattern or maybe limited thinking in terms of the lifecycle but more specifically like microdata for a long time has been the kind of method of choice. So, adding properties within HTML elements has been a great way for templating those repeated data items within a web page but the challenge with that has been the maintenance again so like designers might go in and adjust the display of the image and they might forget to retain the item prop and you know there goes your image feature for Google and you know while marketing may also be wanting to get things in there you know the kind of interplay of like the developer and the designer and the marketing team like kind of like there’s too many hands in the pot with my core data so it also has some challenges with all of those changing requirements and kind of the busy landscapes and simpler smaller teams like maybe that’s not a challenge maybe that person is all one in the same and you know everything’s hunky-dory. Also, JavaScript implementations are quite popular in the last year as well but they’re also not a golden bullet I would say. Basically, it’s just you take JavaScript there’s a couple of different approaches you could use. I think predominantly they use like data scraping so you use JavaScript to inspect elements on the page to determine you know for some ID or some class within the HTML that’s unique to the page you grab that and then you pull it in to the name of the product or the name of the article or whatever the case may be. But again, this is sensitive to changes in design so if you’re having a team that’s maybe a bit distributed and either maybe the designers adjusted something again or perhaps it’s a third party that you have on that site which does reviews, and they put in widgets for all the reviews that thing has generated or the aggregate score if they change something that can throw off your JavaScript. So, again there’s quite a bit of maintenance to it so that’s one of the challenges with JavaScript and then there’s also kind of like the moody structured data testing tool that like month to month maybe works and maybe doesn’t and so like you have to really know whether or not your JavaScript implementation is valid so check them to see if it’s compliant with the Google Bots. oh that’s a Chrome version 41 so like making sure that like there’s no JavaScripting in there that’s going to have a problem with that. It’s going to help you to be assured that the Google is actually going to pick it up and then there’s other ones like the other consumers don’t see it so Google is great to be supporting a render JavaScript but being in some of the other ones do not provide that kind of level of quality for JavaScript support. So, this is also kind of one of the challenges with JavaScript but it’s great to often let’s say bootstrap things because it’s pretty—if you have a tag manager—it’s pretty easy to setup and pretty easy, pretty quick to get done. The other solutions, I don’t know, maybe templated JSON-LD. Like if you have some sort of template for products or for articles then you may want to have the developer create schema markup in a JSON-LD block. So at least there you’re taking out the design of the page you’re just kind of you have that information layer they translate and see a markup and you maybe have the marketing person who’s asking for questions for changes in that schema markup and that can take a couple of weeks though, or months of time before you have those cycles where the development team actually gets the changes implemented. You know they’re also, as a developer myself, I also had to learn the lesson that I’m not a schema expert so even asking a developer just to put schema markup in there, it doesn’t mean it’s going to be right and it probably won’t be unless if they also had their hand and the schema markup pot for a while to understand some of the best practices.

Martha: And so, I’ll just interrupt you here to say like does schema app solve some of those problems like as part of the reason you built it to try to look at the best of those worlds. Can you just speak briefly about that since I want to also talk about schema ownership as another topic?

Mark: Yeah. So, yes, we solved a number of those things. So, especially the IT challenge so we provide marketing team the tools to be able to markup these things without having to touch a line of code so yes so like the time to change is much faster. They’re able to deploy markup on a whole site within a couple of hours. Even for big sites if it’s templated. So, yeah, our highlighter does quite a bit of the work for these large sites and then also our editor is quite robust as well at creating the detailed markup that they may want to do but then we also provide some of the add-ons that kind of bootstrap—get you up to it kind of a minimum level of quality for all your schema.org vocabulary on your site so for WordPress you can install our plugin or for Shopify or add-on and things like that and that’s kind of like getting you to at least I’ll say like table stakes and then after that we kind of want you to optimize even further yet. So, we give them that flexibility. It’s not bulletproof by any stretch of the imagination like maybe the designs could have an impact you to how we roll out our schema markup, but you know as long as it’s in single hands or single control of one person then I think it it’s at least something that can be solved.

Martha: Can you talk a little bit about schema ownership and this is something I think that’s starting to evolve in the market as we you know even see the datacommons.org or come out and talk about clean reviews and even some of the releases we saw today about talking, about how you can, you know, like have your site crawl their URLs for job postings or tell Google which sites have job postings if you talk a little bit about schema ownership how do you see that today and then where you see that going?

Mark: Yeah. The recent stuff is all around the SD publisher and SD license—structured data I don’t know why they abbreviated it but its stands for license structured data publisher I think it is and so those are attributes you can put into your schema markup to say I’m the owner and I license anybody under the Creative Commons you know XYZ license to use this data so this is definitely useful for instructing those consumers like Googlebot or Bing or you know Yandex or Schema App or whoever to kind of like give them the instructions for how they want to be used. So, I think that would allow you to kind of open source your data so if you want it to be kind of like really like shared through the data Commons you can include that publishing license to say like yes that’s great like put all my data or put certain parts of my data into this kind of you know broader web repository and I think that’s just it’s a very practical step for actually acknowledging their license of which you’re sharing this information so there’s that kind of ownership of that data but even within an organization I think there’s ownership like to questions sometimes like around who has the responsibility for that schema markup? Is this a question of like is there a data architecture team or is there a marketing function like who owns that that schema quality and that schema you know like quantity even like who’s responsible for the site wide maybe it’s segregated by sub-site and I don’t know if people really have a clear sense of who takes ownership for that and some businesses like I think often it comes to and falls to marketing but like it’s not really like a question we hear very often.

Martha: Very cool! Thanks for sharing.  So, one last question and we’ll be at a time. So, where do you see this evolving? Where do you see this going you know over the next? I’ll say one, two, maybe five years.

Mark: So, where are things going? Um – good question. So, I guess with the segway from the last one is that data Commons is kind of an interesting possibility so today that has the claim review and you can download all this basically schema markup from the data Commons and you can then kind of do what you want to, use it to do some analysis to determine whether or not the claim reviews should be true and when they’re actually stated as false and going to do some interesting add-ons from that and I would say like this is probably an early signal of what is to come. So, I do really think there’s the opportunity is hidden these kind of add-ons and other ways in which you can kind of look at your data like I have kind of a list of things that I’m thinking about or things that I think we’re starting to see emerge and you know some things are not even new likes just like maybe reimagine ways of doing things because now you have a common vocabulary for a lot of things in a lot of sites so like it could be their spins from talk for a couple of years around augmenting your analytics data with your business information or semantic analytics so like how do you kind of segment your data for your blog posts on your site by author or by tag or by category and to kind of provide additional insight as to which is the best performing types of content like this is its I still don’t think that’s got enough legs yet and so that’s got a long way to run because it’s still kind of difficult to get set up and what else like there’s still things like if you have a knowledge graph like let’s say if you’ve done a good job your schema.org markup on your site. What else? Can you do that like you could think of this as a data repository for informing a chatbot for instance like this would be a very common one – I think that people can look at. So, there’s lots of interesting actions in the vocabulary. So, maybe there’s a potential action to read a white paper. For instance, like if you have all your white papers or those downloadable things in a vocabulary then you can then provide that over to some sort of chat bot or just translation into some other consumers for that list of all the white papers or it could be other forms like contact forms like there’s a bunch of different actions I take a view actions and watch actions like for different tools and like we see a bit of the Google assistant stuff helping you to link up with podcasts and you can play like a podcast based on the schema markup so why couldn’t it be a good TV show or a video object and you know why does it have to be limited to Google when Alexa is also coming around doing similar things and you know or there’s maybe your own experience like you could just repurpose that same information and into your own internal assistant services or chatbots like maybe through the Facebook chatbot infrastructure and other things I’ve thought about are like different browser extensions like ways in which like consumers can just kind of like leverage the schema markup or maybe on-site search of the AdWords custom targeting I haven’t seen I personally haven’t seen too much of that implemented but I’ve heard people talking about it and I think that is kind of an interesting opportunity. Otherwise like I should just mention generally of the schema.org community like that vocabulary will I’m sure it’s going to continue to expand like we continue to see like two or three releases per year so we’re going to see more and more specific classes and enumerations and maybe we’ll see more extensions like the gs1 or maybe we’ll actually get a definition of Google’s own extension for the things that they keep putting out but it’s I think that can also be motivated by these other add-on so let’s say the strategy could be driven by this kind of augmented analytics so like knowing which content articles perform the best can inform your content strategy and so maybe there’s just a way to segment the data that you could expose with schema.org but it’s not in the vocabulary so you may want to just create your own extension and so I think that that’s probably got a long way to go but this is a good place to start. Yeah, otherwise I think I’d have to just add one more thing. Google’s adding so many things that are interesting lately that it’s going to be a lot of fun to see where Google continues to expand their feature set.

Martha: Lots to think about. I feel like we could have almost a podcast or an interview on like each of those add-ons sort of exploring you know how else can use your schema markup. So, thank you Mark so much for joining us today. If people want to find you online where should they look?

Mark: So, I’m semi-active in a number of communities including the Google+ semantic search marketing group from Aaron and Jarno so I participate there but I also I’m on Twitter too @vberkel and I’m on LinkedIn Mark Van Berkel, pretty easy to get and yeah through schemaapp.com that’s our main website so and somewhere in there you’ll find my handywork as well.

Martha: Yeah Mark at schemaapp.com, it’s easy to find him. Thank you, Mark, for joining us today and for helping us understand where this is evolving to and for sharing where schema is started. Thank you for joining us and have a great day.

At Schema App, one of our core values is to always be learning and teaching. That’s why we love talking with other structured data experts!

The post Interview with Schema App Creator Mark van Berkel: Schema at Scale Now and in the Future appeared first on Schema App Solutions.

In this interview Bill Slawski we discuss he shares what insights he has gained reading Google patents and being an advanced SEO practioner.   He talks about how entities have been a common theme in his blog posts resulting from his research on Google patents and how he is seeing the role of entities evolve.  My favourite part of the interview is when Bill describes entity IDs. Why? Well, because it is a tangile node in the knowledge graph, and a centering point for defining things. It gets me thinking about who else can contribute to these IDs, will they become a standard, and if not, what will be the standard for entity IDs?

“If you do a search at Google Trends for an entity like Chicago Cubs or something like that, if you see a type that something other than a search type if you see like Chicago Cubs you look for it and it says baseball team, so it’s a type. So, it’s recognizing Chicago Cubs as an entity. If you look at the URL the last few letters and numbers of the URL are the machine ID number. So, that’s using Google Trends to help track entities. Google did a blog post on reverse image search where they say their using machine IDs to track entities and images so when you do a search for an entity as an image of an entity, it’s using machine ID numbers to help it find that which ties into the Google lens use of schema to find entities.”

Listen to this on “Connecting the Digital Dots” Podcast on Google Podcasts or Spreaker.

Enjoy!

Martha

Martha: Hello and welcome to Schema Stories. My name is Martha Van Berkel. I’m CEO at Schema App and I’m absolutely delighted today to bring you an interview with Bill Slawski.  Welcome Bill!

Bill: Thank you.

Martha: Bill, I love reading your articles, how you get so, so deep into the patents and try to connect the dots for those of us that aren’t reading those technical documents. I’m really excited for you to share your view on Schema Markup today and sort of where you think the search is going.

Bill: I started looking the patents because I was curious about how things worked, and I wasn’t getting answers from most things I saw on the web. Sometimes we do see some only in-depth detailed information from Google’s developer pages and sometimes they promise those things and we don’t see them. For instance, when they first introduced google lens at the Google IO 2018 Developers Conference, they mentioned that they would be putting more information on developers’ pages about how lens uses schema after it recognizes objects in pictures. It would tell us if the picture was a picture of band. It would look for a schema markup that might be event-based and might tell us where the band was performing next. But we haven’t seen that from the developers pages yet. So, I’ve been relegated to looking for patents that might include that

Martha: Love it. That’s awesome. Well, why don’t we start by tell us a bit about yourself and what you do in search.

Bill: Okay. I’m I’ve been working in different agencies and as a solo practitioner since 1996. I worked in-house for a company that helped people incorporate in Delaware for a number of years. I started getting into forums, administrating and moderating forums and kept running into  the same questions over and over and over again. How do I increase my page rank? What goes into page rank? Why can’t Google read pictures of text? Now they probably can, but it’s just something they don’t do. It’s too computatively expensive for them to do. So, if you don’t write something in the text, don’t include your address on your page. If you take a picture of text, you design a logo that has your address in it that isn’t text. Google doesn’t know where you are at.

Telling you more about myself. I work with an agency called Go Fish Digital. They’re looking at the East Coast and the West Coast, and I’m sort of like satellite exploring but we do have some clients on the West Coast. I don’t get to spend too much time going face to face with them but it’s good to be in the same time zone and they know they can catch up to me at the same time of day if it’s later in the afternoon or so on, which makes it convenient for them and for me.

Martha: Excellent! And can you tell me like in your journey around searching in your career when did you first come across the Semantic Web or Schema Markup? How did you sort of first come across be introduced to it?

Bill: I read something I wrote in 2013. I had gone through my previous post to see how often I mentioned certain topics and noticed that I’d mentioned the word “entities” in about 20% of my posts. So, something I’ve always been writing about. The Internet of Things and instead of Strings, right?

And I think a lot of that’s because I do write about patents and there have been a number of patents from Google who all talked about entities and named entities and so on. The people I’m working with now in the East Coast I met at an SEO meetup. One where I was talking about named entities, which is kind of funny. It’s been useful for some of the projects we’ve worked on.

For instance, we worked with an apartment complex in Northern Virginia that was only four pages long. They were trying to sell apartments,they hadn’t been having much luck. We started working with them, improving their site, bringing up things on their pages that they didn’t include, like the fact that if you took an elevator down to the basement it opened up to the DC metro. Which allows you to commute everywhere in Northern Virginia, DC and Southern Maryland. You go to 31 different Smithsonian Institutes which don’t charge admission. So, if you have kids and need things to do in the weekend and you live in these apartments, you can bring kids this was Smithsonian’s for pretty much the cost of hopping on the subway on the Metro.

Martha: Amazing!

Bill: Yeah.

Martha: Can you talk to me? Some people listening may not know what an named entity is. Can you maybe to find that a little further for us?

Bill: Sure. Okay, an entity is a particular person, place or thing. A named entity is when you’re talking about a specific person, place or thing. So, if you are talking about restaurants, those are entities. You talk about the restaurant down the street from you, it’s a named entity because it’s specific entity. When Google talks about local search, they’ve pretty much created a search that’s based upon semantics, based upon entities and schema markup. You don’t need to use schema markup on your pages. You don’t even need to have a website to have listing in Google Maps. But it’s probably smart to. they’ve been using schema more and more and schemas been growing a lot too. They’ve been including new things in it. There is an extension process for Schema Markup where people can submit new topics and expand, have schema cover what it covers how it works and so on. They’re using it new ways. One of the things I saw recently was CNBC suggesting, stating that they received notification from Google that they could create how-to advertisements where they could describe how to do certain things and pay for the right to have those published. So, that’s opposed to people receiving featured snippets they would receive how-to advertisements.

Martha: Very interesting. You spoke about extensions, I know the IOT extension is something that was in the last four release of schema.org. This is all changing and it’s changing fast, as you said those new examples of how it’s being used in paid search that you brought up and actually and I had brought up got brought up in a conversation I had with I’m someone from Google Canada this week. Where do you see this going, and  more importantly what are you most excited about in the evolving area search?

Bill: Okay. One of the typical things we think of when we think about how a search engine crawls the web, like Googlebot, is it follows links from page to page indexes the content of those pages and the anchor text of those links and where the links go if they redirect so on. An alternative to that something that it’s been referred to as open learning on the web is that Google reads pages like it was a person. It tries to understand what’s being talked about, what topics are being covered. We used to have DMOZ which used to be a starting point for focus crawls on the web when search engine wanted to crawl the web and learn about different topics because they can follow categories from DMOZ and to links to pages and that would give them coverage for the search engines so they would cover lots of topics instead of just being very focused on a few things. So, with this open learning on the web it’s something that was developed by a company called Wavy, which was at the University of Washington and headed by an AI researcher by the name of Oren Etzioni. I think I pronounced his name right, I’m not sure. He works for Paul Allen’s AI Institute at this point in time, but Google acquired the technology from them. They’re doing more crawling of facts on the web, which they issued a paper in 2014 called Biperpedia which talks about how they might use query streams to learn about what people are searching for when they search for different topics, and they’re extracting information from crawling of facts on the web based upon what they’re learning from these query strings. So, it helps them build ontologies about different topics on the web that they can use to answer questions when they do question-answering, when they try to show featured snippets. And we’re moving in that direction where the web is becoming a big database.

The very second patent Google filed with the United States Patent Office was one Sergey Brin wrote.  He came up with an algorithm called Depra. It doesn’t have quite the ring of PageRank it’s not Brin-ranked, like he didn’t name it after himself like Larry did with the first patent, but it was a list of five books, their authors, their publishers and their publication dates. And he said if we crawl the web find these five books listed and information about them like we have here for these books, we can crawl all the other books that are in the same location collect information about them and then keep on repeating that. The next thing you know we know all the books on the web are.

Martha: How is this going to change, how as an organization you manage your data? Do you think it will have an impact in how we explain who we are and what we do and the knowledge we have in our organizations?

Bill: It changes around the way search works because it looks to properties of entities, information about them that people can search for. Entities include local entities like businesses so we can search for something like a Chinese restaurant near a bookstore and so we can go find something to read and something to eat on the same lunch period.

Martha: I always talk about it’s like how it’s crawling the graph and connecting those dots so it knows that the bookstores at this address and knows the Chinese stores at this address. So therefore, the bookstore sells books and the Chinese sells Chinese food and therefore can connect those dots across.

Bill: All right. So, I did have a job in the courthouse where my supervisor liked to go on shopping trips and sometimes asked me to make maps for her using Google so that she could tell how to get it from one shopping center to another to another. That’s something Google does easily. Sometimes, they made that a little bit easier to do than other times. They’ve changed that around a few times. It is interesting, you know, the other types of queries we are seeing based on semantic approaches or things like what was that movie that Robert Duvall said “I love the smell of napalm in the morning” and that’s not necessarily asking for a webpage. They chose the names Robert Duvall or that quote or whatever but it’s asking about facts and properties and what movie was acted in by Robert Duvall which included that quote from him and the search results showed two video clips from Apocalypse Now at the top of the results with Robert Duvall in them saying “I love the smell of napalm in the morning”. I bring up Robert Duvall because he lived about a half an hour north of me when I lived in Virginia a few years ago and he was really involved in charities and things like that.

Martha: Very cool. Also that result is interesting because it doesn’t necessarily give the answer but a video, right? So, there’s a whole other inferring going on there around, you know, the content of the video and the entities and the properties within that video, right, which is sort of taking it to that next step.

Bill: So, I got into doing stuff with entities because I was working on the Baltimore.org website and we were trying to rank pages for things like best bar in Baltimore, Black History in Baltimore was one they wanted to rank for we tried it and there were too many well-done black history Baltimore-based websites to rank well. We weren’t getting past a hundred or so on Google’s written rankings. So, I sent a copywriter I was working with an instant message, saying “Could you write something that describes a walking tour of Baltimore from one place to another to another that mentions the famous historic churches, the colleges, the people, there’s the…

Martha: The entities, right?

Bill: Right. There’s a nine-foot tall statue of Billy Holladay in downtown Baltimore There’s a seven-house mansion from Frederick Douglass as he aged. Originally he started out life as a slave and he escaped. He made lots of money he moved back to Baltimore, bought a lot of property there and did well. You can visit these places, you can see them and that was the purpose behind Baltimore.org website to get people in to travel to Baltimore and see it. So, by creating the page that had about 5000 words on it about different entities who you could visit in person as you came to Baltimore. We were helping them fulfill the mission of their site.

Martha: Awesome, which actually kind of leads me into my next question and I always asked, like, in a couple sentences or maybe two sentences – can you articulate what you think the value is to organizations or companies for doing schema markup, like what do you think the tangible outcomes are?

Bill: If you use structured data, you’re presenting more precise information to search engines, using data in formats that that they expect people to use the search for like you would with keyword research. Okay, schema means schema like in a database schema how the database is organized so if you’re using the right words as determined by people who make schema who are subject matter experts, you’re most likely using terms that people will search for that they expect to see on pages that they find which is really helpful.

Martha: We… I’ve been talking to a couple customers recently about how schema.org vocabulary is actually insight into what the search engines want to know about different entities and that you can use it to understand that dictionary that you’re talking about.

Bill: Right.

Martha: But actually so, you actually think of it as input into your content planning. It can be really insightful and also helpful with performance and understanding as you go through that content development process.

Bill: I’ve tried to explain it to copywriters too.

Martha: I had a couple of people click last week so I was I was excited to kind of see them how they think it’s more than just technical SEO right, but how it really can play a role in the planning and strategy stage. So, let’s talk a little bit about the future because, you know, you have these insights into sort of how Google thinks through your research and reading and experience. In my last interview I talked to Steve Macbeth at Microsoft and he was talking about how in his role and AI, they’re thinking about using schema to connect virtual reality with reality similar to what you’re talking about earlier with Google lens, you know? Do you see any new consumers coming up, sort of, beyond the organic search or assistance or now, these sort of virtual reality? Where do you think that sort of that next consumer of schema markup is going to come from?

Bill: are you familiar with machine IDs?

Martha: I’m not. Tell me more.

Bill: Okay. When Google acquired Metaweb, they acquired freebase and freebase would give entities machine IDs. So, Arnold Schwarzenegger, for instance, had one long string of letters and numbers that stood for Arnold Schwarzenegger. So…

Martha: This is like the wiki data number that we have like sort of came from freebase.

Bill: It’s like the Wiki data number that came from if you do a search at Google Trends for an entity like Chicago Cubs or something like that, if you see a type that something other than a search type if you see like Chicago Cubs you look for it and it says baseball team, so it’s a type. So, it’s recognizing Chicago Cubs as an entity. If you look at the URL the last few letters and numbers of the URL are the machine ID number. So, that’s using Google Trends to help track entities. It’s used in… Google did a blog post on reverse image search where they say their using machine IDs to track entities and images so when you do a search for an entity as an image of an entity, it’s using machine ID numbers to help it find that which ties into the Google lens use of schema to find entities.

Martha: And are these two things like the entity nodes within the knowledge graph from Google’s perspective or are these like more global standard entity IDs that can be used like from a sort of more data comments or a sort of open data stance?

Bill: They are sort of like a shortcut Google is using for, you know, they’re doing search engine optimization too but they’re actually optimizing the search engine they’re trying to make it quicker for them. So, if you search for Arnold Schwarzenegger they say oh that’s this string of numbers and letters, so that’s all mentions of Kindergarten Cop, all mentions of the terminator, all different roles that he’s played. They know that’s the same person the same entity.

Martha: And is that something you think that brands can control. So, if I know Kellogg, could I actually start sort of helping define that if I’m managing my schema markup in knowledge graph?

Bill: Okay. So Google I/O 2013, they came out with something they called the invisible same as which meant that they could use a link element instead of an anchor element as something you could use to show that an entity you’re talking about is the same as something that maybe you see in Wikipedia or something. So I had a client who was an app developer who came up with a payment app they were started by Sprint Verizon and AT&T. So, they were on most of the Android phones in the US because those are pretty big carriers. They were putting a link, okay? So, the company we worked with them, their name had changed the were originally known as Isis, which maybe you don’t necessarily want to be known as a company because it sounds a lot like a paramilitary group from the Middle East, okay? I started to do an audit for them and one of the things I suggested was they use this invisible same as which was described at the Google i/o conference by a couple of Google developers. I figure Google wouldn’t have a problem with that because it’s something they came up with. So every time on the website they would call themselves Isis they would use the same as link to their Wikipedia page which shows that they’ve changed names from Isis to the new name okay which meant they weren’t the paramilitary group. Google could distinguish them from the guys in the Middle East. So they never implemented that because Google bought the company two weeks before… two weeks after I sent them the audit. So, I missed the chance to go that would them.

Martha: But now, we actually see that in answer the general schema markup right where you can use same as most people use it for social media but how you can also use it for stronger relationships right? So, if you’re changing brands you know who you were and what it is as well as alternate names etc. right?

Bill: Right. You can and they remark that you can use it in Json, to have it show on your knowledge panel.

Martha: Exactly. Well, one last question and then we’re going to wrap up because we’re out of time. So now, I Iook to you in a lot of your articles to stay on top of things that are changing, especially again looking at, you know, some of the things that we don’t see. Sort of publicly and in some of the public documentation from the search engines, you know? Who are people you follow and watch to stay on top of trends or that are inspiring you serving your work?

Bill: It’s a good question. I tend to, I have a very large SEO list on Twitter and I read through that usually a couple of times a day because you never quite know what people might post from there and their SEO is from around the country, around the world. I’ve made a couple of other lists like that. I have a machine intelligence and a deep learning list and a search engine list. I find that it’s helpful to look to those and see what people are talking about because people do announce a lot of new things there.  

Martha: Yeah. I absolutely love following the conversation especially again for thought leaders sort of around the world and in different areas of specialty and you know and it’s always fun, also sometimes when they throw in non-search related things really, so you get to know them as a person as well.

Bill: That does make it fun. Yeah.

Martha: So, Bill, thank you so much for your time. If people wanted to find you online, what’s the best way for them to find you?

Bill: They can find me on Twitter (@billslawski, @seobythesea). I spent a lot of time there. I do blog at my own website which is SEO by the Sea. I blog at the Go Fish Digital website. I had been doing some writing for some other sites. I don’t do that quite as often because the Go Fish Digital site and the SEO by the Sea site keep me busy enough.

Martha: Excellent! I’ll put those links in for our listeners and for the people watching the interview, and again a heartfelt thank you for spending time with us today and sharing your insights. I look forward to continuing to see you in the Twitter-dom as well as reading your ongoing articles as you go deep into sort of how things are changing from a machine learning and a semantic web. So, thanks so much for your time today.

Bill: You’re welcome. Thank you!

At Schema App, one of our core values is to always be learning and teaching. That’s why we love talking with other structured data experts!

The post Interview with Bill Slawski – Google Patents and the Future of Search appeared first on Schema App Solutions.

Martha: Hello and welcome to Schema Stories. My name is Martha Van Berkel and I’m the CEO at Schema App and I’m absolutely delighted today to be joined by Steve Macbeth at Microsoft. Welcome! Steve.

Steve: Hi, thanks for having me.

Martha: No problem well let’s jump right in. Tell us a bit about yourself and how you got started with schema.org?

Steve: I am a long-term Microsoft employee I run a small incubation engineering team right now but I’ve been with the company since 2002. Most of my work has been in the AI space natural language speech and I started in search which at the time with MSN search in 2006. I went to China for three years to start a Development Center there. During that time we supported many search features primarily in structured data and so I got a lot of experience kind of being a consumer of structured data and at the time there wasn’t very good structured data on the web and so we had to build a lot of technology to convert largely unstructured data into structured data in order to power features like vertical search. So that was kind of my introduction and then when I came back from China I ended up running the Bing core relevance team. That was when I wanted to try to solve the structured data problem more systemically than scraping the web and converting unstructured into structured data. That’s kind of a bit of a background on me.

Martha: And so you were there right at the very beginning right in the inception so what I understand?

Steve: Yeah Guha who was the original founder who works at Google he came to visit Microsoft 2009, and basically proposed this idea of having Bing and Google and Yahoo at the time, collaborate on building a schema that we would endorse and it was aligned with work I had been doing already and I think of addressed a number of challenges we were seeing and so the opportunity to do that at an industry level and partner with Google and Yahoo seemed like a great opportunity. We weren’t and aren’t the leaders in search and so I think whenever you’re not the leader and the leader wants to do standards work it’s always beneficial to dissipate.

Martha: In those very early days were there any kind of key areas of schema.org that you were really passionate about and really pushed forward to be included in the schema.org vocabulary?

Steve: Well when we originally started we took a very kind of noun focused perspective which was you know how do we capture a bunch of the nouns that people are searching for movies and locations and things like that and books and products and provide some structure around them. For me I’ve always been very interested in the kind of action side of the web and I particularly been starting to look a lot at mobile search and the relationship between how actions get linked to in the mobile space and so the whole action extensions we did. This was probably two years after we had originally launched the original schema.org work we started to add actions and that was the area that I would say I was most interested in and I still see the most opportunity. Although I don’t think we’ve ever made as much progress there as we have in the mountain space but I would love to see more progress.

Martha: One of the drivers we’ve been talking about especially enterprise looking at actions is that if you define them on the website a chatbot can then understand the action it can do on the page. So as a business driver for looking at defining those actions I don’t know if you have any thoughts on that?

Steve: I think the struggle with all of this kind of market is that there’s a catch-22 which is that publishers have limited resources they’re only gonna mark up where there’s value and marking up and consumers of markup will only build features where there’s lots of markup and so if there’s no markup in an area and no one builds features and there’s no features that’s markup and this has always been the biggest struggle I think in this space. So I think the more people can think of ways to use the existing markup this is always this is always better. So I love the idea that you bots are starting to you know consume some of the existing markup and use that be smarter and to drive value.

Martha: Love a very broad question you know the Semantic Web is something you know those of us that are sort of semantic technologists get really excited about but especially as you sort of look at the AI components of things like why are you passionate about the Semantic Web and kind of where do you see it going?

Steve: Yeah, I think there’s sort of two aspects one is like personality-wise why am I  interested I’m a an order a person you know I like things to be orderly and you know the non-Semantic Web is a very you know disorganized place you know unstructured text is very disorganized The you know the organizer in me likes the idea of you know clean lines and well connected lines and lots of semantic meaning in relationships. That’s kind of like my personality is predisposed to wanting to organize things and I think you know semantic markup an outlet for that kind of I don’t know if it’s a personality flaw or a strength but.

Martha: We love it you know our mission is to you know translate the world content to be understood by machines otherwise is like we want to organize the web right we’re right there with you we follow it.

Steve: And then I think from a like a practical perspective my work, I’m not in the Bing team anymore I don’t work directly on search and more in the broad AI space and in fact there was just a big re-org today at Microsoft that changes my team’s Charter slightly into more of the AI perception space. They’ve been merged with a number of other teams doing things like vision and speech and my team is doing computer vision and I definitely well there’s not a direct relationship right now. I do think longer term AR and VR and how they interact with the Semantic Web is super important and it provides this opportunity as you view or interact with stuff in the real world you know the ability to connect to semantic meaning around that information I think becomes super important and I think there’s a lot of rich experiences that could be built. If you could connect an item, you see in the real world with the digital counterpart to that item and its relationships and its actions.  I think this is very nascent area for the Semantic Web.  The interesting thing now is really how to connect the digital world in the physical world and I think this is no semantic meaning. I think maybe is the fabric in which we can connect those two things and you see this already with mapping you know like yeah Maps didn’t have latitude and longitude you couldn’t connect in maps in the physical world but maps are deeply semantic you know in their designs and so they’re very easy to stitch together with the real world. Most data on the web because it doesn’t have that kind of semantic backbone it’s much more difficult to connect to the real world and so we tend to use the map as the mechanism to connect it. I’m looking at this restaurant not because I know that this is the restaurant but because I know that on the map has this restaurant and in real world, I am at that location so the map kind of acts as the interface between the real world and the digital world. I think we need more interfaces between the digital world and the real world.

Martha: Yeah, it’s interesting it’s almost like we’re seeing today around images and connecting the images to the knowledge graph, let’s call it. Your saying take it a step further and make it so it’s actually more like our human experience connecting to our knowledge graph.  I love how you are painting the next step and why we should be building this foundation. We’ve talked about Bing and there’s been lots of conversation about Bing and that it is recently consuming JSON-LD which it has taken a bit longer than Google to consume or show evidence of supporting JSON-LD. Can you talk a little bit about how Bing uses schema.org and entities. I know that’s not your primary team but maybe we just make some comments on that?

Steve: Yeah no let me let me first start by giving you the caveat which is anything I say might be incorrect and if it is I apologize because I am not as involved day to day with that work as I used to be. I think there are a few areas where Bing consumes the data but mostly it’s from our object repository. So we have an entity repository called Satori. I think this is public knowledge. That is a place where all of the entities Bing knows about are stored and that entity database is used obviously to drive many features in Bing. Relevance features, Ad components to that there’s rich like vertical search features that leverage that data to do rich captions and filtering and these kinds of features. But more and more other products are starting to take advantage of that too.

You know enterprise functionality is starting to look at, how can I take a customer’s catalogue and then bind that to the web graph and again this is I don’t think this is any different than the conversation we had earlier which is you know finding these connection points. Like if I have a catalog and in that catalog is a bunch of product how do I bind that to sentiment on the web. In order to do that I need to find some connective tissue that says okay well this product in your catalog is the same as this product people are talking about on Twitter or Facebook or Instagram or wherever you know or writing reviews on the web. So for us Satori is this kind of connecting fabric that says, we know the names of things because people search for the names of things we know the canonical web address of things and then we have all this structured data about those things. So we can use natural words and you know well-known IDs as that connecting fabric. So, the main way that Microsoft consumes and uses structured data is through Satori.

Martha: Got it! So, would  Satori be the equivalent to Google’s knowledge graph?  I think that’s a great way for people to kind of connect those dots and speak Microsoft language instead of always the Google language.

Steve: But a much sexier name.

Martha: Yeah and you’ve put me in contact with the Satori team some of you get them on here to have a similar conversation. Talk to me a little bit about AI so you’re sort of in the VR space you talked about like of that connecting pieces like do you see any other sort of AI experiences emerging in the near term?

Steve: Well that is a very broad question. Yes, we have a event at Microsoft called tech fest which is just ending. Our tech fest is a three-day event where researchers generally showcase the work they’ve done and then anybody at Microsoft and some press can come through and see it. It’s kind of like a science fair and so it’s always a good opportunity to kind of see what’s going on. I would say the majority of the booths at tech fest this year were AI related or leveraging AI or making it easier to build AI. So, there’s a I think there’s a huge focus in the company and in the industry on how can we use AI to make software better. I think AI is kind of there will be come a time where nobody talks about AI because you know AI in some ways is like object-oriented programming. Nobody talks about, “are there more object-oriented features coming” because it’s a tool to build real-world things. Right now it’s novel and so it’s a way to differentiate, like object-oriented was 15 years ago.  I think in another  5 years and maybe less people will stop talking about AI in products because every product will have some aspects of AI.

Martha: Is there something that was that Techfest set that stood out to you that kind of got you excited?

Steve: It’s all proprietary so I can’ really share. I think there’s a lot of stuff in the VR space I like excited about personally.  I went to ready player one last night and so I kind of loved VR in the VR space there was and is working in haptic feedback which I think is really exciting and so you know I think for me that area is super exciting. The overlap between AI and semantic data like we talked about and AR, I’m a big believer that in the near future maybe 10 years everybody will use some form of augmented reality through glasses or contacts or something like that.

Martha: Excellent! well thank you so much for being part of today and sharing that vision especially as though that I’ll say like that bleeding line between you know reality and sort of the connected graphs of things to me that was a new idea of how to see the evolution. If people want to get in touch with you or to sort of follow your thinking or the work that you’re doing how do they get in touch with you?

Steve: I mean they can just email me I’m on LinkedIn Steve Macbeth if you just search for Steve Macbeth Microsoft on LinkedIn you can find me. But my email address at Microsoft is just Steve. Macbeth and so if anybody wants to reach out let’s do that. I think I’m in my stuff’s also on that schema.org website somewhere.

Martha: I think that’s where I found you.

Steve: I think we had talked about one other question which you I think didn’t answer but I had an answer for go for it. Which  could people who are doing semantic markup do? The thing we talked about earlier which is create connection points is like the most important because semantics is better than no semantics. Semantics without the ability to connect to other data is almost as valueless as no semantics. I mean semantic data only valuable in my opinion when it can be bridged to other data.

Martha: I love that yeah, we talked about islands of code versus actually building a graph. Is that what you mean?

Steve: Exactly, and so, I think the more you can think about okay I’ve just marked up this entity on my page or this action what is the mechanism that can be related to other things and so I think Wikipedia forms a very nice backbone for canonical IDs. Very early in the in the formation of schema.org we made a strong decision which was not to support canonical IDs and I think it was an important thing because it would have been very politically contentious at the time to support it. Because we basically would have had to pick somebody’s ID system to have canonical IDs. I think the time has come for canonical ideas I would love to see schema.org or some other organization take on canonical IDs but the more you can think about like what is the canonical ID for this entity. Is it Lat and Long? is it binding back to Wikipedia which I think can form this is kind of backbone of canonical ideas. You know ISBN can be that for certain types of data but like just thinking about what is the mechanism that this can be connected to other IDs and then I think for the future like how can it connect to the real world and so I think like QR codes in semantics  seems like a really weird idea I think on the surface but I think will become more and more important because it’s the mechanism in which you can basically allow people.in the physical world interact with your semantic data in the same way that I think lat/long allow that. I just wanted to kind of throw that last bit.

Martha: At Schema App we are true believers in connecting your data and defining it wherever that definition is right . There are more groups coming out whether it be data commons or open data defining those things for different groups or different entity themes. How do we continue to encourage people even at a very basic level, if you’re a small business defining your city by the wiki data entry for that city etc. There’s very simple ways that you can start making those connections. We’ve been marching that with you Steve trying to get even the earliest adopters of schema.org to be thinking about that connections or paths sort of between things to make sure that they’re connected.

Steve: Excellent!

Martha: Well thank you I love that that last thought thanks for adding that in and again you can find Steve on LinkedIn also share his LinkedIn and email sort of within the post and so people can find him there again thank you for taking the time I know you’re a busy man and for your continued support in schema.org have a good day.

Steve: Thanks for having me.

At Schema App, one of our core values is to always be learning and teaching. That’s why we love talking with other structured data experts!

The post Steve Macbeth from Microsoft: Connecting Virtual Reality through Schema.org appeared first on Schema App Solutions.

Aaron Bradley shared many insights, with his key takeaway being:

What the introduction first of Rich Snippets and then later of the Google knowledge graph really introduced into the search engine world is, as encapsulated by Google’s famous marketing phrase for the knowledge graph “from strings to things”, is that prior to the search engines weee essentially indexes of documents. So when you search for something, if you were looking for blue widget, you really weren’t getting results for things that were blue widgets, you were getting webpages that described or use the string the best blue widget.

Whereas now, and especially since the interaction of the Google knowledge graph but also fueled by structured data, what we now have is a web of things kind of one of Tim Berner Lee’s great visions for the web, so that rather than being an index of documents, Google is increasingly becoming an index of things, and facts related to those things. You can’t possibly have that without those sort of linked data technologies working in the background including ontologies, schemas, taxonomy solve that sort of thing.

To get started on this journey in the Enterprise, Aaron suggests three steps.

1. Start with fundamentals. If you’re a webshop, look at search engine optimization with schema markup.
2. Then look at the possibility of bringing that data into your analytics.
3. Connect all of the data points across the enterprise.

Martha: Hello and welcome to Schema Stories! My name is Martha van Berkel and I’m the CEO at Schema App, and I am delighted today to be joined by Aaron Bradley. Welcome, Aaron!

Aaron: Hey, how’s it going, Martha?

Martha: Excellent. Well, not only am I excited because you’re Canadian and we get to geek out on structured data together, here over the 49th parallel but I’m also excited because you bring a really unique perspective in your role and within the enterprise. Let’s start by having you tell us a little bit about yourself.

Aaron: Sure, I often say I’ve had three careers, that inevitably led me into the place that I am, I was a technical services librarian for about a decade. Following that I was a web designer for about a decade and now for slightly more than a decade I’ve been a search engine optimization specialist, though like most SEOs, my role has enlarged and deviated. So, to encompass other realms of digital marketing and particularly the creation and distribution of digital content across platforms, and right now as I have been since 2014, I work for Electronic Arts where I’m a web channel strategy manager and have a great team that work on these issues alongside me.

Martha: Excellent! Tell me a bit how you got started like within those kind of three careers, when did you first get started using schema markup or exploring structured data?

Aaron: It was in and around 2008 when I was working for a jewelry e-commerce site called ice.com and I first encountered Martin Hepp’s Good Relations ontology for e-commerce. I was very excited about it I think maybe because of my librarian bent and having worked with controlled vocabularies in the past I saw this as an interesting and exciting way of informing search engines and other data consumers about what products were about on a webpage, and began kind of exploring it then.

This is of course well before the release of schema.org. Back in those days, you had microformats were the main structured data type.  I can’t recall yet whether datavocabulary.org which is a precursor to schema.org had yet been released. So the search engines and even though good relations was a well-developed ontology, the search engines weren’t doing much with that or anything at all, but following on that Jay Myers of BestBuy began marking up all of their product catalog and RDFa using in good relations. So, just ever since then I’ve been kind of keeping my finger on the pulse of those developments that eventually led to schema.org and the birth of well, Rich Snippets so predated schema.org I believe started to roll out in 2009 and incrementally we saw after that that Rich Snippets were being filled increasingly by search engine sanctioned structured data.

Martha: Very cool! So for those that aren’t semantic technologists that are listening, in kind of layman’s terms, like how would you describe an ontology?

Aaron: An ontology describes the types of things that you can talk about and the relationships between them in a highly structured way. So, for example an ontology might define a person like Aaron and it might describe a relation, for example Aaron knows Martha van Berkel and those are all highly structured relationship descriptions of classes so that there’s certain attributes associated with those. So kit enables data consumers to have a very precise view of what you’re talking about and applications since we’re just talking ontology is more generally and they are the building blocks then of taxonomies. Most notably the simple knowledge organization systems (SKOS). It rests on various standards including the RDFS so that there’s ontologies behind all of that and schema.org is sort of a de facto ontology of people arguing whether it’s an ontology or content schema, but like other ontologies, provides precise descriptions of things and the relationships between them. From that in and in modern parlance most ontologies are compatible with linked data, that is to say that they reside at your eyes that are de-referenceable, that means both humans and machines can go and then look up information about that class or those relationships at that URI. That’s something that people I think, kind of, don’t necessarily understand kind of more traditional SEOs about schema.org is that when you say a person has name or the name property Aaron, that person is schema.org/Person and name two is a relationship schema.org/name so that it creates a graph.  That’s what you know obviously the biggest example of that is the Google knowledge graph.

The really big picture point that I love everyone to take away from this and really what the introduction first of Rich Snippets and then later of the Google knowledge graph really introduced into the search engine world is, as encapsulated by Google’s famous marketing phrase for the knowledge graph “from strings to things”, is that prior to the search engines were essentially indexes of documents. So when you search for something you really you know if you were looking for blue widget, you really weren’t getting results for things that were blue widgets, you were getting webpages that described or use the string the best blue widget.

Whereas now especially since the interaction of the Google knowledge graph but also fueled by structured data, what we now have is a web of things kind of one of Tim Berner Lee’s great visions for the web, so that rather than being in index of documents Google is increasingly becoming an index of things, and facts related to those things. You can’t possibly have that without those sort of linked data technologies working in the background including ontologies, schemas, taxonomy solve that sort of thing.

Martha: Love it. So with this movement from strings to things in your role at EA,  how do you see this evolution playing out in the enterprise. This may be a different than how we often talk about this, as like doing SEO for solution for different companies or within agencies. How do you see that application within the enterprise and how can they benefit?

Aaron: Certainly, it’s a crucial and key component in personalization and especially personalized content delivery. In order to deliver at scale-personalized experiences you need to know two things you need to know something about your user and you need to know something about your content, and the more model that is, the more rich you can make those experiences and the better the relevance of the content that you can present to a user. Now, to give you an example, so we might know that say a user plays Battlefield One, one of our games and in our own systems that’s linked to a taxonomic term which is the genre first-person shooter described on ontology and other games, then, are described by that same structure. So, therefore, we might say that Star Wars Battlefront 2 might be of interest to that player because they’ve expressed an interest or we know that they play Battlefield 1 and therefore we might want to surface content in, you know that very kind of play an example about Star Wars Battlefront 2 because it’s also a first-person shooter and you can infer that through having that structured universe. So, if I have a Star Wars Battlefront 2 article that I’d like to surface for a player it’s not necessary for me to label that, tag that and sort of typical content parlance first-person shooter that can be inferred by making a query to the system, “Okay, I know that this player likes Battlefield 1, show me all other games, content about all other games that are also of that genre so as long as we know that that that that piece of content is correctly associated with the game Star Wars Battlefront 2, we also know it’s a first-person shooter, we also know it’s playable on Xbox 1 and PlayStation 4 and PC. So, there’s all these attributes about games that then we can associate with content and then we can provide that data to players. That’s a high-level and very simple example, but I think you can see how that’s sort of inferencing can start to be really powerful in recommending content across the enterprise.

Martha: Absolutely! And I love how you sort of used to “ask the question to the data” right you know I think that’s something that I’ve seen in other interviews with you is where you say to think about what would you ask could Google assistant. In the enterprise you’re saying what kind of questions would you want to ask your data.  Often we sort of ask that question around Semantic Analytics. we ask what do you want want to get from your analytics and can you sort of use some of that structured information to gain insights.

Aaron: Querying is really core to any sort of many of these processes, right, whether you’re querying your analytics or whether you’re querying your content or where whether you’re querying user events. If they’re described in the same ways, that starts to really present powerful possibilities of joining one with the other and when you’re dealing with data, you always have to think from it think of it from a machine data consumer perspective, right? So you’re not going to be able to get answers to questions that your…your data isn’t aware of, right? So it has to be structured in such a way that it supports those queries, and in building a lot of the systems that are worked on, that’s really where a lot of the MVP (Minimum Viable Product) requirements start with, its can it satisfy this query and this query and this query and if not, then you modify your architecture in order to satisfy that.

Martha: Which is a good lead-in to the next question around, “I work in on enterprise, for me I put on my hat from my Cisco days, and I want to know, how do I get started doing this right? If I want to move in this direction, while also sort of thinking about the search applications, what would you recommend to people sitting in an enterprise as a first step to help them get started or to get thinking about this?

Aaron: Excellent questions to which I don’t necessarily have a ready answer. I think, you know, familiarising yourself and starting to use schema.org is a good lightweight way of starting to be introduced to these technologies. I would actually go the extra mile, I’m just such a big-linked data guy…

Martha: Yeah, yeah…

Aaron: I think and I think to truly understand something like schema.org you do need to know a little bit about link data and how it works. What we would call the Semantic Web but link data is now more of the term. There’s a couple of canonical documents about that if you. Anyone watching this, go ahead and google Tim Berner Lee’s work.  I forget the year but it’s called Link Data Design Issues in which he provides the five rules of link data. If you understand those 43 words, you’ll really, really understand linked data and the Semantic Web.

Aaron: Manu Sporny who’s actually one of the pioneers along with Gregg Kellogg and Markus Lanthaler of JSON-LD has an excellent series of YouTube videos on various introductions to the Semantic Web, JSON-LD, things like that. So that’s where I’d start in terms of knowledge and then, I go ahead and put this into practice by starting to apply schema.org schemas to existing content. At least if you’re in a web environment and seeing how that’s structured and what the outputs are and what the results are.

Martha: Excellent! Yeah, I’m a big believer in start with some of the standards and then extend because it’s you can move a lot faster, right? I understand sort of getting started from the technicals perspective, right, so will sort of include a lot of those resources. You obviously have great executive sponsorship and the work that you’re doing since you’d be doing this, yes since 2014, and sort of getting really deep into it. How do you translate this into the business value, like how do you tell that story,  you talked a bit about personalization. Anything else with regards to sort of the business outcomes that get the executives excited about investing in this?

Aaron: Sure. I mean obviously you need to point to in any sort of digital marketing efforts do you do need to point to business value and I think that there’s a number of ways of doing that and I’ll give three examples.

One obviously from a search perspective if you start using structured data mark-up you will start to see rich results surfacing in the search engines and you will absolutely and unequivocally see a rise in engagement and CTR from those results because their information is provided to the users directly in the SERP, about that they tend to have higher click-through rates. You’re providing the search engines with really explicit information about the things on the page that are represented there, so you’re more likely to show up in query results for relevant queries and this should all at the end of the day translate into a better bottom line, particularly if you’re looking at you know the typical and correctly, so web metrics of a conversion rate optimisation and revenue.

You touched a little bit ago on and extending that another example is analytics and I think still one of the underutilized promises of schema.org is using it to tie in weather as Google Analytics or another platform so that you can start to slice and dice that data as well by the things that are represented in the content rather than by the strings that identify it. For those that work in Google Analytics at the end of the day Google content groupings are rather blunt instruments but if you’re already marking up your content particular using JSON-LD, then you have at your fingertips the capability of then exposing that information within your analytics and being able to make some really interesting and useful queries against that data to then extract business value.

Finally, if you’re looking this, you know, to truly enterprise skill if you’re a large company with, whether it’s a single domain that’s highly focused or an e-commerce site, if you start to build linked data applications you can start to use these same technologies to bootstrap your efforts particularly. That’s what we’ve done at EA  as we built out our initial ontology for games is that we use schema.org to bootstrap that. It’s a very useful all-purpose sort of vocabulary that you can then locally extend but it tends to cover kind of most use cases that are most common, that are most common in across businesses.

So to recap them

1. Start with fundamentals. If you’re a webshop do the search engine optimization.
2. Start looking into the possibility of bringing that data into your analytics and start to think about.
3. Pie-in-the-sky, connect all of the data points across the enterprise in some sort of semblance of order.

I think properly framed, you get executive support and buy-in from that and particularly if you follow those incremental steps because you’re going to show literal business value by those first couple of steps. It will lead to an increase in conversion in revenue.

Martha: Love it. Two more questions and then we’ll wrap up today. How do you know, who do you follow or what are you watching to stay on top of the trends, like in this space, especially around the enterprise?

Aaron: Yeah. In the schema realm, I follow the schema.org mailing list but more importantly these days is the schema.org github repository. That’s where most of the development work and discussions around it takes place and it’s great because you get to work with the people that actually built that the vocabularies and working on. Aside from that, it’s a broad spectrum of people. I actually have Twitter list that’s open, called Semantic Web where kind of everyone that I’ve ever been able to find that works on link data is there. I also you know go to conferences. I’ve been to the last couple of taxonomy boot camps in London. I spoke at Semantics 2017.  For those that maybe aren’t that heavily into those sort of more extreme applications of link data but you know the search people, obviously I’ll promote my own community group that I moderate along with my friend and colleague Jarno van Driel Google+ Semantic Search Marketing which is a great starting point, particularly if I have any questions about structured data markup. We’re a very active and responsive community.

Martha: I love the debates in that, thank you, yeah. I think there’s a new joke (2.22) that I come in and weigh so that the business questions or applications, You can ask early technical questions, you can ask business-relevant questions, you can be a beginner or advanced and you guys are so welcoming to everyone. So my last question is – if you could wave a magic wand and change one thing about schema.org, what would that thing be?

Aaron: Yeah. Hard to say because it’s not especially lacking. Should point out too that schema.org really benefits from the experience of a lot of people that worked on the project from the early days that have been involved with it most importantly, Dan Brickley, who along with Libby Miller developed the first really broad scale web ontology which was friend-of-a-friend vocabulary for just grabbing people and the relationships between them. So, it’s really solid stuff and you have lots of luminaries of that space like Martin Hep and Kingsley Idehen who are involved in that space. So it’s it’s quite solid. I think if I could do one thing, I would vastly extend the number of examples and the clarity on schema.org. There’s probably for many practitioners too many pages where there are no examples or too many pages where the examples are a little esoteric when it should start with a straightforward display of information about that particular type and get more esoteric after that. So I think it has the potential to confuse some kind of novice webmasters there. In terms of the vocabulary itself, I don’t see any major holes and as those are identified, they are being filled.

Martha: Awesome! Yeah, we try to help our customers with those examples or like changing the definition. So you can actually understand if you’re not a semantic technologist what it means. Well, thank you so much for your time today. If people want to find you, where can they find you online?

Aaron: Oh, I’m everywhere. So Twitter is the easiest, twitter.com @aaranged.  I don’t blog enough but I do blog sometimes, that my blog SEO Skeptic and as I said Semantic Search Marketing, the community I run Google+ Semantic Search Marketing.

Martha: We use it for that search community if nothing else. Well, I hear you’re scheming NINJA tshirt today. Maybe you can give us a flash of your T-shirt just for fun.

Aaron: Ninja!!!

Martha: …with awesome JSON-LD on the back describing how you are indeed a ninja. Thank you again for joining us and have a great day!

Aaron: Thanks a lot, Martha, you too!

At Schema App, one of our core values is to always be learning and teaching. That’s why we love talking with other structured data experts!

The post Interview with Aaron Bradley – Schema Markup & the Enterprise appeared first on Schema App Solutions.

At Schema App, one of our core values is to always be learning and teaching. That’s why we love talking with other structured data experts!

The post Schema Story: Jarno van Driel The future of schema markup appeared first on Schema App Solutions.

Martha: Hi and welcome to Schema Stories my name is Martha van Berkel and I’m here today to interview Mark van Berkel. Schema Stories are all about bringing real people’s stories to life that are working in the area of schema.org, semantic search to make it more real more than just technology. Mark Van Berkel joins me is the creator of Schema App and also my co-founder of Hunch Manifest. Mark welcome.

Mark: Hi, thanks for having me.

Martha: Mark please tell us a bit about yourself and a bit about your background.

Mark: So, I suppose I started working in 2001-2002 as a programmer and spend several years as a consultant and doing some enterprise software and then 2005 started a master’s degree in, basically semantic technology and about half the credits were going toward ontology design engineering as well as doing a proof-of-concept or recipe research labs and so that’s where I got the familiar with semantic technology and spend then spent a couple more years in the industry and 2012 started the company and just quickly figured “how can I now apply semantic technology because the application of the software and technologies had gotten to a point where it was productive use for for business and for industry. When I was studying at the university it was still fairly theoretical. The tools weren’t there weren’t ready to support it. So yeah, long history consulting, as well as technical product design.

Martha: So a lot of people know you most as the creator of Schema App, although they hear my voice and see my face, but you’re the one came up with the idea so tell us a bit about why you created Schema App and how it came to be.

Mark: The Schema model basically, the Schema.org group had published all of the recommendations as this kind of graph model, so rdfa which is just and a way to structure the actual classes and properties and how they all relate together. So this is coming from the semantic technology world so that the kind of, the graph relationship and I’ve been working in that technology, as I mentioned, productively in 2012, and onward. And so it’s 2014, I believe, it was the summer, I put two and two together, we were doing a digital marketing consulting at the time, and I figured that there’s probably ways we can consume this model and put it to good use.

So, because I had familiarity with the graph database, and did some transformations – and I can plug it into this tools and I’m using and so I was able to figure out, “okay well I can create this generator and this way of creating and managing your schema data”  and it was around that time that the schema group decided to adopt a JSON LD as the format which played right into the tool because then you’re not mucking around in the HTML. The JSON LD format is  nice and clean so I can then export. So there was just this opportunity to get this generator going in and do the work for our clients. Created it for myself originally, and basically whenever google get on board with a JSON ld, then I made it public and so let’s fast forward to today.

Martha: I still remember when you went and spoke at Semantic Technology & Business Conference and people were excited about what you had created but everyone kept saying that really, you’re too early.

Mark: Yeah, that’s right. So, I had conversation with Aaron Bradley at SemTech. I reached out to him ahead of the conference because I wanted to show him and basically he said “Well have you seen a rich snippet yet?” The answer was no, so Google hadn’t been rewarding that format and syntax yet.  So, a little early, but you know, there were some other uses for it so I didn’t didn’t kill it yet and then we figured that that that format was coming down the pipeline as something that would be more broadly accepted for the rich snippets. So now today JSON LD is the preferred format for google. So all the bells and whistles are there with JSON LD, especially when you talk about email actions.

Martha: Since you first started thinking about semantic technology back in 2005, a lot has changed both in the landscape of the application and how useful it is to everyday folk. I don’t think you back then would have ever thought you would have a conversation with a marketer about semantic technology and we’re continuing to watch it. What are you most excited about, the changes going on in the semantic and schema world?

Mark: Um well the semantic technology is just a huge conversation because it’s got such broad applicabilities.

Martha: So maybe, how do you define semantic technology?

Mark: Yeah so even that’s loose, but I particularly going to the is going to the NoSQL group of databases that drive the technology. So primarily I think about the graph relationship, with the property model kind of relationship databases, so they underlie a lot of the technologies that the semantic technology we built on because of their flexibility to describe the relationships between things. So, semantics is all about figuring out what’s the meaning behind the words you need a really flexible way to describe your concepts, such as in schema.org, they had provided some flexible ways to describe the relationships between all the things, all the properties, and so that’s kind of one area of semantic technology.

There’s other areas where you talk about neuro linguistic programming, where you’re trying to pick up the meaning of words, and try to pick out maybe people, places and things out of unstructured data and there’s some other areas of semantic technology but what I’d like to kind of steer the conversation towards is this semantic search marketing or a little more the schema.org kind of structured data part of the semantic technology. So we built Schema App with semantic technologies and the scheme part is something that sit into it. So from that vocabulary and from that area there’s still a lot of opportunities so schema.org started with like Rich Snippets. So at first you can provide i information about a recipe or event online. And then there were products and little stars and then it kind of got interesting where google acquired metaweb, I think that’s what it was called, the creators of freebase so they were also born out like that same era, and they were also very early, 2007 I think they were created, and acquired 2012 roughly, where they just had this giant database of concepts and relationships between those and things. And it was popular in the industry. So that is then really interesting where then Google consume this as part of its knowledge graph and so then, in the couple years since then, we see Google just pouring so many serp engine results pages from their knowledge graph. So where did you get the knowledge graph? From freebase, from Wikipedia, Wikidata but also from schema.org.

So originally schema marketing was geared towards creating rich snippets but now we have the knowledge graph so that was kind of the second, and this is like a fairly well untapped, let’s say at this point, you know most marketers see the low-hanging fruit of the rich or rich cards today, but marking up the rest of your content whether it be certain types of events, getting into maybe certain services and things that don’t generate a rich snippet but, you know, telling someone that you’re a consulting company, you have five lines of business and there’s services that you offer, can be very important to get Google to understand what the concepts in your business. So, just providing schema, just other concepts outside of the those google features is that is a big area that has yet to be well tapped. But, in addition we got some other things like those open data is a more open data as just has a lot of government and other types of industries where they’re publishing data sets about the things that they’re doing or within cities maybe it’s the sidewalks and all the geographic locations of sidewalks more might be around like forestry or whatever like just sixty four thousand open data sets, that I saw, the tool that last week of  things available in all across like a lot of Western countries, especially now.

So the UK heavy on open data. For the United States government and then in Canada bunch of cities that are doing open data. So to kind of bring this around, like they’re all like siloed chunks of data which might be fine if you’re like really interested in a narrow niche but how can they better describe those those datasets with schema is kind of the question I’m interested in the next year two. Because schema is a vocabulary that they can unambiguously declare like what the data says about and in the roads and all the concepts so why not use this existing vocabulary to describe all that open data and then there’s a bit of a bit of work already being done in the UK around the job postings, they’re open data group has approved scheme.org job postings as the vocabulary of their open data. So we can see that becoming more and more importance in the months and couple of years to follow.

Martha: So are you thinking that, as they standardized how they markup their open data, that open data then gets connected with the overall knowledge graphs and then all of a sudden you have this behemoth knowledge graph?

Mark: Well, yes. So the knowledge graph I mean it’s not singular, it’s not one knowledge graph, like google has their knowledge graph, they have an api, but there’s lots of other companies that have knowledge graphs. So Microsoft and Bing have their knowledge graph, Yahoo has their own separate knowledge graph, like I don’t know, probably many dozens of companies have their own knowledge graphs, like especially around their specific domain that go very, very deep. They would, I’m sure, like to consume some of this other data and if it’s more readily available to the world with the common colabular it’s easier to consume. So, that can feed into the knowledge graph of many companies including  Google.

Martha: So one thing we’ve heard with our Schema Story with Mike Arneson and also some other conversations with Aaron Bradley and about semantics analytics. I know you spend a lot of time thinking about semantic analytics.  Can you talk a bit about what you are excited about, where you see the possibility there?

Mark: So it’s an interesting area, so primarily, it’s let’s take Google Analytics and extend it with your data. So right now is it’s kind of an almost completely anonymous data. I’m talking about generic concepts that every website has like a user has certain characteristics, like their location or maybe what application they are using to browse it or what kind of what phone or whatever and then there’s like the sessions and the length of things. That’s all generic stuff.  So semantic analytics is taking that semantic data, that structured data, schema.org is primarily what we are talking about, and injecting that into Google Analytics so that you have a more rich description of things that are driving revenue, or in like keeping people’s attention or have more social shares. Whatever your goals are. In the world of publishing or news, you start dissecting reports based on the author.

Obviously you would like the author to have that kind of report in Google Analytics, but they don’t make that available, or out-of-the-box. So how do you start customizing for the categories of pages for posts, or customize the keywords or length of blog post. Wouldn’t it be interesting to see at what point of a blog length does it have a material impact of the success of that campaign? Does it require twelve hundred words compared to 800 words. What are the comparisons there? All sorts of different things are made available on schema.org. As long as you have that in your markup you can now bring that into Google Analytics and create custom reports based on your business data. There are ways to get around that in the years past, but I am really excited about providing that super simply. So, as you are onboarding with Schema App in the next several weeks and if you are into ecommerce or you are in the content industry, you get a bunch of data that can come from your website automatically through Schema App, into Google Analytics and you can start dissecting. And then products that world like you can start thinking about all the different reports you can generate such as segment by the colour of your widgets, or segment by price or segment by the manufacturing or whether or not there’s a video associated, or whether or not there’s more than ten images.

There’s lots of ways you can slice the data so that you can better inform your future product marketing. I’m excited about the possibilities, how simple this can be for users and marketers, how with the click of a button and maybe five minutes of time, they can then have all these reports readily available in the Analytics. That’s the exciting part. Another thing that I don’t hear much talk about in the area of schema data where the structured data you provide for your content can also be used in other ways – like an in app search. So if you think about in WordPress, for example, there’s a fairly rudimentary keyword algorithm for ranking the blogs and articles in the out-of-the-box WordPress search but if you can also consider that all of these articles also have the author, the length, the number of comments, maybe some ratings, the pictures, all the different things you can put in schema.org, can also be made available in search filters. So you can do some more faceted search just based on the schema data. The way in which you are interacting with these sites and services can be improved just by reusing schema in these different ways.

These are just a couple of ideas that are emerging, there’s lots more that can come out. Like, schema can also be used  for competitive intelligence. So there’s companies that have product pricing intelligence so lets say if you have a certain line of products, that they will monitor the prices of all the competitors. Now it’s fairly easy to consume schema.org data, so you can think of how many applications there are in that area, and I think it just goes on. So making it available to the public means you are making it available for other, new types of use cases that have yet to emerge. With the internet of things, I think there’s opportunity. Because it’s a common vocabulary you don’t have to map any of the concepts. Yea, it’s an exciting time with all those different uses and it all started with a rich snippet for a recipe.

Martha: Mark, if people want to get a hold of you or ask you questions or debate and discuss where they think schema.org is going, how do they best get a hold of you?

Mark: So I am on twitter, I am pretty easy to get a hold of me there @vberkel, by email at mark@hunchmanifest.com and my sites at hunchmanifest.com and schemaapp.com. I’m behind there somewhere, but twitter is probably the quick way to get a hold of me.

Martha: Thank you so much for joining us today and sharing your thoughts on where you think schema.org is going and how you came up with Schema App. Thank you for joining us for today’s Schema Story.

At Schema App, one of our core values is to always be learning and teaching. That’s why we love sharing our thoughts and insights about schema markup!

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