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The Future of BIM Is Information

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Description

The productivity of architecture, engineering, and construction (AEC) is going down. Other industries' productivity arrows are pointed up, but ours is not. After 25 years of building information modeling (BIM), one would think it would be different. But it's not. There are probably thousands of reasons for that, and we would never imagine knowing a fraction of them. But we think one of the reasons, however small it is, has to do with how we work with Information today. Other industries are implementing artificial intelligence (AI) at scale. The AEC industry cannot. This inspiring talk will explore why not, will look at what we can do about it, and will provide a few examples that show we are on the right path.

Key Learnings

  • Discover the biggest hurdles for mass digitization in construction and facility management.
  • Learn how mindset and data-creation processes play together to create information value for contractors and owners.
  • Learn how to capitalize on the business potential in documentation automation.
  • Learn about accelerating our industry's transition from CAD and BIM to information technology.

Speaker

  • Avatar for Håvard Vasshaug
    Håvard Vasshaug
    I am a CPO and Co-Founder at Anker, the world's first digital construction enabler. I am also a Founder of Reope and Bad Monkeys, and have driven the development and implementation of digital workflows in AEC over several decades. Having worked in IT, Engineering and Architecture, I now dedicates all my drive to scale digital construction and through the automatic creation and validation of quality construction data.
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Transcript

HAVARD VASSHAUG: Hello, and welcome to this presentation for Autodesk University 2023. My name is Havard Vasshaug. I've been at Autodesk University many, many, many, many times before and I've given a lot of presentations, but no presentation ever felt as exciting and good as this one.

I can't wait to be in front of the actual live audience and share this with you. We're going to watch this recording later today. I'm a structural engineer. I've been working in both IT consultancy firms, doing a lot of BIM training, lots of Revit training.

That's how I got into the whole Autodesk world. I worked twice as a structural engineer, and then I worked in two companies as an architect, or in an architectural firm as a design technology manager and expert.

Before five years ago, or a little bit more than five years ago. Actually, almost six years ago, when I came home from Autodesk University 2017, after a few months, I left my boss at Snohetta.

I know that I'll be leaving and starting my own company. That company was founded in April 2018. It's now called Rio, which is a IT or BIM consultancy developer, consultancy firm in Europe. Operating out of Norway and Europe.

And two years ago, we started building a product called Anker. One year ago, we decided to branch that out into a different company, and today, that company is a company with actual, physical human beings as employees. Almost 10 people, I think going to be 9 within a month or so.

So that's been a roller coaster ride, and it all started, for me, the first time I ever saw Revit in the summer of 2005 at a conference in Barcelona. And then fast forward here we are today.

There's a big change that has been happening in the building industry, or in the AEC industry. Everything that has to do with buildings and infrastructure, engineering, owners, contractors, this whole ecosystem in the AEC industry that we are in, there's been a big change.

I don't know exactly know when that change happened, but I would say probably like between 10 to five years ago, it started in some places-- geographical places, like this hasn't happened all over the world. Not at all.

But in some places on the planet, it started like five to 10 years ago. And a lot of people in the industry are starting to hear about it, are starting to talk about it, and they are starting to feel it.

And what is that change? The number of standards and requirements that are appearing in new projects, all around the world, are going through the roof.

For a lot of people, that change becomes painful. For a lot of people, it's interesting. It offers opportunities, like for owners for instance. We'll get back to that later.

But for sure, this is happening. And so many people are talking about it. A friend of mine, in June, was in London talking at a conference. And he said that for a new company-- he was in an architectural firm --for a new project in his firm, a few months ago, he had to read through almost 5,000 pages of standards.

And that's not even the client requirements counting. There are so many standards-- and we need standards. Believe me, I'm not saying we don't need standards. But the amount is getting to a level where one human being can't really understand or comprehend the whole set of standards that a project that is starting today needs to fulfill.

And it's the same with client requirements. This started as a kind of like a secret movement in some BIM environments in my part of the world, in Norway, where I'm now.

It started with some building owners starting to publish BIM requirements, and then enforcing them into the contract of projects. So I'll talk about this today and a little bit about what that means for the industry, what it means for the different stakeholders, and the different people who are in the industry.

And I'll talk about possible solutions. I'll talk a little bit about people that I know that have developed solutions, or used solutions, and tried to solve this problem in different ways. I'll do it from different perspectives based on the different stakeholders.

And I'll show a demo of the product that we are building to try to solve this, on behalf of the industry. And look a little bit into the future at the end.

But number one, the information requirements and the standards that people have to fulfill in design and construction projects are going through the roof. Why is that happening?

I think we have to look at the Holy triangle, or the Bermuda Triangle, if you want, in the building industry, the owners, the builders or contractors, and the designers. The architects and engineers.

The designers are the creators of data, the builders are the users of data, and the owners are also the users of data, or the receivers of data. So what happened?

And I'm not really sure exactly of course, I don't know anyone who knows exactly what happened or where it started. But I'm pretty sure that some owners figured out or started talking about the value of BIM, probably five to 10 years ago, or maybe even before.

When I started with BIM, it was this small team of people hacking Revit to try to make it fulfill local standards, and so on. That's the first time I went to Autodesk University, to talk about how I hacked Revit to make Norwegian Rebar drawings.

And then it grew from there and became this massive movement. Like so, so, so many people are talking and thinking about BIM today. But it remained like a designer's tool.

So when you poke into the BIM space today and see who actually can work with BIM, it is mostly the designers. And it was a big paradox for a lot of us who started with BIM that it never went outside of the design teams.

We would make highly detailed, like super complex, efficient, and well-functioning BIM at the different jobs I had before and the clients that we worked with.

But they would always get printed on paper and sent out to construction site and drawings out to the owner and then dusted away in some basement somewhere.

And I think that some time ago, not many years ago, someone in the owner segment of this Bermuda Triangle started asking that question. Is this BIM that's going on and happening in the design space, is it something that we can use for something?

And well, all of them had like this archive of drawings. So I suppose they started asking like, yeah, where are those drawings coming from? Today, those drawings, mostly in big parts of the world, are being produced out of the BIM based design process.

So maybe we should start asking for that, the result of that BIM based design process. And not just the printed drawings, but also, actually, the process. So building owners started asking for BIM.

They started mandating them in Norway. We've had been BIM mandation since what? Almost, well, 15 years. And it's the same in other countries in Europe and around the world.

But nobody really said anything about what that BIM should be. Like some countries mandated IFC files, and some countries mandated like Revit file, and some probably something else. But that changed.

So the owners started asking, let's see your BIM. We want, at the end of the project, we want to see the drawings. We want you to hand over the drawings as built.

But we also want the BIM to be part of our portfolio of projects. And they probably are thinking that this is actually like value. There's data in the BIM that we can use for something later. And that has value for us.

So, they started asking for these things. And then they soon realized that when they buy services from architect number A, architect number B, engineer one, and engineer two, the BIM that they received was completely different.

Everyone has their own Revit library. Everyone has their own Revit template. Everyone has their own internal processes. And this just gets more and more and more complicated when you start buying services from other countries.

Is an Italian architectural firm supposed to deliver furnishing drawings according to the Norwegian standard? So this becomes really complicated for a lot of people.

And in the middle of this, the owners, and I suppose also the designers, was part of design teams really wanted to make our BIM data available for the builders, because it felt so stupid to build all this highly detailed models and print them out on flat paper.

Do the sections, the horizontal sections, the vertical sections, and then print it out on paper. No data, just graphics. Text and graphics, lines, and numbers, and legends, and whatnot. And it's dead graphics that nobody can do anything with.

So that felt stupid. And we talked to a bunch of contractors or builders, that I call them in this case, and ask them would you like to use some data? Would you like to see some BIM?

And for a lot of them, that was interesting. For a lot of the innovators among the builders, interesting. But of course, like a pretty steep mountain to walk because of many, many, many different reasons.

So I'll try, over the next couple of slides and during the presentation, to talk a little bit about what these people are looking for, why this is happening, and what the result is. And then maybe discuss a little bit how we can solve the issue.

For the owners, I think there is a wish to-- well, let's call it what it is. I'm afraid of using the word because it means so many different things.

But I think a lot of the owners today actually want to build a digital twin strategy. They understand, all of them understand, that the BIM is not their digital twin, but the same way a set of drawings can function as an underlay to their work and processes and their archive buildings.

They know that can also be a set of digital models. So that is why they are starting to ask for this data. They want to build up an archive of data where they have a portfolio of all their walls, all rooms, all spaces, all HVAC, all electrical, all structural in digital format.

Not in paper with graphics. And I think a lot of them don't really know exactly what they are going to do with that digital twin, but they want to start.

And as one of the owners told me once-- actually the hospital construction agency of Norway, they are currently building 17 hospitals all over the country --and he told me, well, we want to have an archive of all our assets in one database.

And we want to be able to sort, and filter, and group on asset data across all the different hospitals. And of course, every single hospital have a different design team.

They have a different contractor, or a different set of contractors. So they need this data to be consistent across all their 17 assets, like buildings.

And how do you do that? Well yeah, you tell your engineers, and architects, and builders, if you work for us, have to fill out all this data in this, and this, and this way.

That is where it gets painful for especially the designers, we'll get back to that later. The owners also want effectiveness. So they want more data and they understand that if I'm going to have a digital twin in the future, I need an archive that is consistent across all my 17 projects.

I don't know exactly what I'm going to do with it but, we have to start somewhere. And when they do, they will ask for a lot of data. They need a bunch of data instead of just an empty BIM, like you would normally get.

If you design something in Revit and click Export to whatever format, it will be like a blank file with some dimensions, length of wall, height of wall, thickness and so on.

But all the metadata that these people need to organize their work, organize the different assets and buildings that they have in their portfolio, they need a bunch of metadata.

So they start asking for metadata and this is the information requirements. that I had in one of the previous slides. So they say, if you work for me, you need to fill out this, and this, and this, and this, and this, and this property.

Bunch of properties. Some of them have 500, thousands of properties that people now today have to fulfill in order to work for them. But at the same time, they want the design teams and the builders to be more effective.

Oh. How are we going to solve that? Who is going to punch all that data if the hourly fees are going down and the request for man hours are going down?

But also, in the third point, in this, they also, of course, they want a return of investment. Most owners are business people, or at least the private ones, and they want value out of what they pay people to do.

So this is a difficult calculation that I think a lot of public building owners have just started because they are maybe not so driven about return on investment.

They have their budgets, of course, they want to be within the budgets. But they are not necessarily thinking about making money out of the digital assets or the data that they are asking for.

But the people are now starting, in the owner space, they are starting to understand that every parameter, or every property, or attribute that I'm asking my design team to produce, and quality assurance send to me, has a cost.

So that is a balance that they're all looking at. The builders, when they start receiving data-- because remember in this trinity, you have people now starting to ask each other of data instead of graphics.

The designers produce data, send it to the builders, send it to the owners. The owners produce data, send requirements to the designers, and structure and facilitate the process of exchange between the builders and designers, and so on.

And in this space, something happens to the builders of course, also. They-- for reasons I'll get back to later --there's no trust today in the quality of the data that they receive.

I think there was a lot of trust in the quality of the drawings, because we had hundreds of years of best practice and collective knowledge about what a good drawing was like. That's the first thing I learned as an engineer when I came out of University.

The first thing I learned, this is a good formwork drawing. This is a good bending schedule. This is a good reinforcement drawing. Down to the details.

It was passed on from man to man, and woman to woman, until a collective intelligence, if you want, where everybody knew what a good drawing was. Nobody knows what a good data set is for BIM today.

So many people in the design space just produce data, don't know what it's going to be used for. Send it to builders, contractors who open it up and just see so many errors.

And this is real. I'm not making this up. It's crazy, even down to spelling mistakes. So the builders, they want to trust the data, but they don't today.

They also, of course, want the effectiveness, probably more than anyone in this whole ecosystem. The builders are depending on being fast. They hate being slow.

So, they had an existing process with the drawings. It was of course, clunky. There's a revision, and where is that drawing? And hey, did you see the latest revision from the blah, blah, blah.

OK. That wasn't great, but it's even worse now because of the data quality of the model. So when they have to start calling the architect, and calling the engineer, and asking is it correct that this property here on the fifth floor is this and that?

And the engineer has to check. Let me check. Oh, I can't open Revit. Then the effectiveness hurts. So when the trust goes away and people start feeling less effective, that's when the adoption of digital transformation just goes down through the floor.

And the third thing that the builders now really feel that they don't have is autonomy. Before, when they received the drawing, book came by the mail. Thank you, sir.

And then the first thing they did was they took out a pen-- oh, there it is --they took out a pen and started sketching on the drawing. Ah, I'm going to this, I'm going to do on Tuesday. And this, I'm going to do on Wednesday.

And then when they were finished, it was like double the drawing from what it was before. The architect and the engineer's drawings were an underlay for their work.

And what happens when they receive data from design team? Maybe an IFC file, or maybe a Revit file, or maybe something else. Oh my. Yeah, that's a problem. Total dead data.

And they struggle with even mastering the tools. And all the contractors that I talked with, they do so many training sessions to teach their people how to work in BIM, with all the BIM viewers, all the 3D viewers.

I won't even name one of them, but there's a bunch of 3D viewers in the space today that different builders use for their data driven process. And somehow they are great, but they lack that autonomy.

They can look at things, and they can click on things, and see things, but they can't change anything. So that is a little bit of a broken workflow, and it really hurts the heart of the builder. No trust, no effectiveness, and no autonomy.

Not a good day at work. And then we come to the designers. Now the designers, they have been happy. I've been part of many, many, many design teams, and we have been, if not happy, then at least content and satisfied in this world of BIM.

We had our little bubble. We linked the engineers model, look for clashes, and like coordinate system, and all of this. And then printed drawings, and everything was fine.

And then all of a sudden, these annoying building owners and contractors start yapping on data quality, asking for information requirements, and standards, and why is my parameter wrong?

So, this is really increasing the stress level of a lot of architects and engineers. I would say, in my personal experience, that a lot of-- well, they all have this issue.

Actually, I was going to say that MEP engineers have the easiest time, but they don't, because they have so many elements in their models. It's difficult to manage a big, big, big data set of a lot of elements, especially in a-- how do I say this?

Well, Revit is not the best database. Let's just say that. So, architects also have problems, but that is for other reasons. They have much less complicated models, but they have-- well, they're architects. So, let's just leave it at that.

Architects have a human problem and engineers have a data size problem, I suppose. And interestingly, very few designers that I ever met and worked with in my life just came to me in the morning and say, hey buddy, do you know what?

I woke up this morning and I was thinking I was going to be a data scientist. I think that would be nice. That's a good career path for me. That happened 0 times. Every single designer, architect, or engineer that I ever met, maybe with a few exceptions, wanted to design.

They wanted to design beautiful space. They want to create nice systems, good structures, beautiful geometry, and pleasant space. They want to do it in a sustainable way. They want to have a good process.

They don't want to sit and punch data because owners and builders need it. They also want the effectiveness. Who don't? So when they are stuck with a database tool, like a lot of them are doing-- and imagine a building owner comes with information requirements, here, please, can you fill out all these 500 parameters on every single element in your entire data set for the project?

Their effectiveness also goes down. So the peace and tranquility hurts because they cannot stay in their like BIM bubble. Now all these people are starting to bother them with all the data requests. And they just really want to, most of them at least, really just want to design buildings.

Oy, yoy, yoy, yoy, yoy. What are we going to do about this? I'll show you a few examples of people who are trying to solve this problem today.

First, from the building owner's point of view. The Norwegian building owner that started mandating BIM for the first time on the history of Earth, together with a few other countries, was Statsbygg in Norway.

Statsbygg is the public building owner that handles, or owns, or operates all the cultural buildings, and all that stuff that's not hospitals, or infrastructure, or military establishments.

So, this is the Viking Ship Museum, outside of Oslo, in the beautiful peninsula of Bygdoy. Very green and nice. If you ever come to Norway, I highly recommend going there.

And it's been redeveloped. Before the Viking Ship Museum was only this cross building, and now there's a super nice, curvy addition to the building where the three Viking ships that they dug up almost 100 years ago, probably, are going to be inside of that building.

It's one of the biggest tourist attractions in Norway. Four years ago, Statsbygg, that same building owner, exactly like I explained before, said, you are still going to deliver BIM on my project, but you are also going to deliver a bunch of information on all of our projects.

So they published what was then called SIMBA, which is the name of their information, their BIM requirements, basically. SIMBA, the next version. Actually don't remember which version it was, but it was the next version.

The original version said, you are going to work in BIM and you're going to deliver IFC files. The next version that came four years ago in 2019 said, you're going to do that and you are going to fill out all of this data during the process.

Not even at the end, but during the process. You're going to work with data. They did that in 2019, and then during the first three years, absolutely zero projects were able to fulfill their data requirements.

So can you imagine you're a building owner-- you're a pretty big one --and you say, now everyone is going to do this, and then nobody does it. Hm. Not so good.

So on the Viking Ship Museum, that actually changed. And I'm not making this up. This is true. The building owner, Statsbygg, they deployed this automated validation process.

Like everyone figured that, OK, where do we have to start to solve this? Oh, we have to start with validation. They had existing validation tools, but they were really clunky to use and difficult to scale and distribute the results, and blah, blah blah, blah, blah.

So they created this validation workflow facilitated by the owner and the contractor. The owner, Statsbygg, the contractor, slash, builder-- I should actually just say builder from now on --builder, AF Gruppen, one of the-- I think it's the second largest in Norway.

They facilitated this process. AF Gruppen was going to have a digital construction process, and Statsbygg, the owner were going to have their digital asset, the digital twin, basically.

And then the engineers at Multiconsult and the architects at Art Danish Company were going to work together and use this validation platform to help everyone get better at producing data. And it worked.

Six months ago, Statsbygg went to The Building Smart conference and announced for the first time ever, we actually have a project where our information requirements are being fulfilled. They did that by automating the whole process.

So, big surprise. We deployed anchor on the Viking Ship Museum Statsbygg and AF Gruppen were facilitating the process, setting up the requirements, defining the bits and pieces inside the requirements.

And the cool thing was that they were able to publish the result on a daily basis to the project's team's channel. So in the morning, anyone in the project could go into teams and then see that graph.

Arrow going up, arrow going down. Red numbers, green numbers. Is it going good? Is it going bad? And that changed the mindset of the project. And then we also closed the loop into the designers BIM software.

Both Art and Multiconsult are using Revit in this project. So we live fed the results of the validation into Revit so that every day they could go in and check this automated validation result, click on the elements in the table that didn't work, and then fix them inside of Revit, and then publish new data.

So this has worked, and it's been a great success for Statsbygg and for everyone in the project. Next example, and this has to do with autonomy. Unfortunately, I don't have a nice render of this project. It's an infrastructure project.

It's called E39. That's Europe Route 39. Big, big, big, road from Kristiansand and I think-- don't know how far up towards Stavanger, on the south and western part of Norway. South part of Norway, really.

And in this whole transition that I've been talking about through this presentation, also, of course, the builders have to produce as built data for the owners. And remember what I said about autonomy? Dead data.

Engineers would publish a bunch of models modeled in Civil 3D, and Revit, and AutoCAD probably, to IFC and then send it to the contractors.

And then the contractor would have to open these models and then maybe open them in Notepad or something and change parameters, and do this full time, all the time.

To add the data, that is the contractors documentation for the elements to the owner.

So, the contractor or the subcontractor, [? Relish, ?] again Danish firm, that have people in [? Umega ?] [? Halton ?] working in Norway, have built this workflow where they stream the IFC data from the engineers into Anker, into the database.

And then, they just made a super, super simple Excel spreadsheet where they just list all the IDs, all the tags of all the elements. They tag the elements in the first row and then they put all the property sets in columns, and then work with that Excel spreadsheet to fill out all of this information in a fast and intuitive way.

And then we merge them, the BIM data and the spreadsheet, and populate the BIM data using the spreadsheet and functionality inside the software, and produce fully enriched IFC data for the owner.

And this is cool because it's fully automatic. We stream the BIM into the database. You upload the IFC file into the database. Everything else goes automatic.

And then all you have to do is like select them and download, or stream the BIM data onto the value chain in the project. And the contractors, they say it's an amazing workflow that is saving them so much time.

Last example. Very good friend of mine, who is also going to be at Autodesk University this year, Angie Mendez, from Costa Rica. She's been working in an architectural firm in Norway for almost 15 years, I believe.

She works at a company called A-lab, which is one of the biggest architectural firms in Norway. And she called me six months ago and was very worried about these information requirements.

That wave. That graph almost looks like a wave, a tsunami, that is hitting architecture. And I told her, well, yeah. It's probably-- you're getting all these requirements, and she was actually going to-- her company was going to receive a daily fine for every property, or something like that, that didn't fulfill the builder's requirements.

And she called me and was super frustrated and said, what is the world coming to? And we talked a little bit about it back and forth. And I've talked to a few builders during this time, and I said to Angie, I think it has to do something with risk.

Because if they are establishing a digital construction process, you're the builder. And remember, you're not trusting the data. And the data actually shows up wrong. And there's plenty of examples for that around Norway.

And you're producing data that hurts the process and the project of the contractor, then that is a risk for them. So that's why this is happening.

So they decided to do something about it and set up this validation process for a lot of their projects, not just this-- the picture of Elvely, which is an office building outside of Oslo, --but other projects as well.

And now they have a system in place where they quality assure not just the validation of data, but also the creation of data for digital construction on several projects. And this is turning into what Angie referred to as BIM 2.0.

I think there's a lot of people claiming to have BIM 2.0, but at least we have one client who does. [LAUGHS] So, that is some nice examples of this.

So, I'll talk next a little bit about what it is like, most of these processes or most of these digital construction processes. What are they looking for? What is this data that they are struggling with?

I mentioned that some building owners have like 500 or more than 1,000 properties. Usually, the case is that it's more important, in my opinion, to have data quality in projects, than data quantity.

So, maybe there are really good reasons why a building owner would have 1,000 properties in their BIM requirement, but in my experience, there's a small set of properties or data that you need to get a digital construction process working.

The first one, I don't know what to call it. It's like digital twin. It's like a word I'm afraid of using, but someone call it LOD. Someone call it LOIN.

In Norway, we call it MMI, model maturity index. But one number, or text field, one attribute that says something about the maturity of the object.

So you model a door. You model a window. You model a rebar. You model a duct. And then you have to use data as a communication tool to say something about how finished this object is in the process of the product.

I like to call it LOD because it's like, everyone knows what an LOD is, but apparently, it's a touchy subject for some people. But anyway, that is a very important attribute because everyone who receives data, the first thing they do when they open a data set that they receive from a design team, is they go and filter on LOD.

That is supposed to-- according to at least Norwegian standard --it's supposed to be a number. 100, 125, 150, 175, and so on. And these numbers mean different things.

400 means it's ready for construction. So when a contractor then opens the data set and filters away everything that is not LOD 400, that is what they build.

And you can imagine what happens then when this parameter is wrong. Maybe there was a spelling mistake, or maybe someone did a wrong number or whatever, and then everything becomes chaos in the construction.

Same thing with control area. Control area is a property that a lot of digital construction projects use, at least in Norway, to split up the project in smaller pieces.

Just like you would with a drawing, right? You don't put the entire building on one drawing. You put by level, you put by section, maybe depending on the architecture of the building.

Then someone calls it like a product breakdown structure, or control volume, or whatever. But you split the project in smaller pieces than what the actual file contains.

Contract number says something very interesting about who this data is for. In the first hospital project in Norway that used digital construction, there's more than 100 contracts.

So this is also a difficult parameter to get right because of the sheer amount of elements, and the sheer amount of different parameter values that can be for this.

And the contractor responsible is pretty common to have. So you know who to beat in the head if something is wrong. But that is an actual person who's responsible for this contract description.

Because when we work in BIM with this data, we always use like IDs, very small numbers and text and codes that mean something because it's like short, easy to see on the screen, and easy to punch.

But a description should be extremely good for a lot of people to see and to be able to use. You click on a door, and there's a description. The door has a tag, like a type mark or something like that, and there's a description.

This information is vital for the understanding of what you're dealing with, as is also, the system code and the type ID. So these seven properties are the most important ones, is what I hear, in the digital construction process.

And then, of course, you have a bunch of other properties that you also need for different purposes. But if you get this right, I think you can succeed a lot with digital construction.

And then, how. How are we going to solve this problem? And in my experience, and I've been dealing with BIM for almost 20 years, it comes down to people and their tools.

I use the term mindset because I like it, but you can call it human factor, or adoption rate, or people. What people end up thinking and doing, and the tools that they have available.

I think that one very, very important change that we are going to have to do as an industry to make this whole thing that I'm talking about today, and that a lot of people are caring very deeply about, work. And that is to change the mindset of a lot of people.

You can say to the builders, oh, you guys you have a big job in trying to convince your colleagues how to use BIM for your processes. You can say to the owners, oh guys, you are requesting too much data. You should actually just have seven parameters in your BIM requirements.

And maybe they will listen, maybe they won't. And you need to talk to the architects and engineers and change their mindset and work with them so that they are able to understand what they are-- or why they are doing this.

That's the question I hear most. I talk to an engineer and I ask him, do you know why you are creating all this data? And he's like, no. Don't know why.

We have to explain to the engineers and architects why this data is vital and important for the operation of the owner and the builder. And we have to help the architects and engineers understand why they do things.

One of the first things that I ever did when did I project in Revit, back in the day, was create a sheet list. When you created a sheet list, and created all the sheets, edited the title block, and put all the views on the sheets, you have a clear understanding of what the output of your process is.

If you know what the output, the goal, is like-- you're looking at the goal and you know what it looks like --you have a much greater chance of succeeding with the process leading up to that goal.

Now we have to help engineers and architects understand what that goal is now when they are producing data instead of graphics. And that is a tricky one. I know.

And I've been part of a project recently that is doing this. If you understand that you are building up a window family in Revit, and the builder is going to use it for quantities, you do different choices.

You do the sun shading in a different way. You use nested families maybe. You build up your whole design process in a different way when you understand what the data is going to be used for.

This is very, very important. But equally important, and I love this presentation or talk that Steve Jobs did like probably 100 years ago, where he talks about why he built the computer in the first place.

And that is that a human being with a tool, in his case, he used a bicycle, is the most efficient creature on the planet. And it's kind of true here in our AEC space. A human being with a good tool becomes very powerful.

So we need new tools. We have built one, I don't think it's going to be the only one in the market. Today It kind of is. And I'm excited to show you a little bit how it works.

I've been working on it now for two years. As I said before, it's been a company for one year. And we have a good chunk of clients now and people are really excited about what we've been thinking, and I want to share that with you.

So with that, I'm going to head over into BIM Space and look at Anker. In short, Anker is a flat web database, a database living in the. Web it's on a server.

It has a web front-end and it has a Revit application. It has integrations in and out to different common data environments like ACC BIM 360, and BIMsync and a few others. And it does a bunch of things in that database based on triggers and events.

I'll show you in just a little bit how people can use it, and how people do use it. And I'll start like I did before with the building owners. So validation. Most of the building owners they are into validation.

When I do things in Revit, like changing some facade panels, or moving something around, and what not, and I think sync the central to the cloud, or to a work shared model, or save the local file like I did now, Anker the add in, how it's installed here, will extract everything that's in that Revit file and push it into the database automatically.

It does that every time someone syncs, actually, if you change in Revit. If you just sit and sync and don't change anything, nothing happens in Anker. That's really smart.

So the Anker database should be, and is, always a one to one with the Revit database, or the Revit databases. Because the general idea here is that you have 100 files, or 50 files, or something and connect all of them to your Anker database.

This is mine. I have one file. And as you can imagine, it gets really, really-- the increase in value people get from collecting data into one database like this, increases exponentially with a number of different files you connect to this system.

So when I sync, it uploads all the data in Revit into my database. And then I have a few different things that I can do inside of the database. I'm going to skip the overview, the tables, populate, and go to validate.

Now because I'm a building owner and I'm curious about the data quality in my Revit model, or my clients Revit model, so I'll go to the validate interface of Anker-- and remember, it's a database.

It contains all the information all the elements and all the properties in that Revit file. Both shared parameters, everything. And I'll create a validation algorithm for checking if the data is being fulfilled.

It works like this. It's pretty simple. It has filters. So I'm going to look for everything that is a family panel, in this case, the facade element here that is across the entire outer skin of this building, is just a family called panel.

Family name, panel. Type name, panel. Just like a good architect. I'm also going to filter out anything that is a type, so that I'm only looking for instances.

And then, I go down into this space where I specify my validation. And I say that I'm going to check the property called asset type.

And I'm going to check whether it fulfills the regex expression D3, which says that this is OK, if it's three numbers. No space, no dot, no dash. Nothing. Just three numbers.

No letter. Three numbers. That's it. If it's three numbers, it's OK. If it's not, it's not. Then I'm going to check a property called asset name, and I'm going to check if it equals to MON, which is like owner's project name of this entire building.

So I want every single element in the entire building to have that property on it. And then I'm going to check, control area. Remember control area? I talked about it before, control area.

It's going to be any one of these numbers. So that's just three ways that you can specify a validation algorithm. This is an algorithm. If this and that, then this.

And then I have a neat set of filters that I can apply at the bottom, that I can use to interact with the validation results. Now, I can either click validate, or I can go and check out previous results.

Every time you run a validation, it saves a snapshot of the results of that validation. So I'm going to go and check the one that I ran two hours ago and see what it looks like.

Very, very simple dashboard. Most of our clients actually stream the data that comes out of this validation into their own Power BI reports. But we have a very simple dashboard that people can use.

And you can see that everything is OK with the asset type. Everything is OK with the asset name. But in control area, there's 75% success rate.

I can actually click here on control data and then I can see that 280 elements in that facade past. That means that they're OK. But 90 elements failed.

Let me move this one over here. And then I can go and filter by file, filter by control area, filter by asset name, filter by all of these parameters that I specified in the previous page.

And then review the results. And I can see here that control area, there's about 90 facade panels here that have a wrong value. All of these green ones have the right value, and then there's 90 elements that have the wrong value.

OK, cool. That's how validation works-- in a very, very short way. And this has become really powerful. Actually, our first client ever needed validation desperately.

And now, every single one of our clients, everyone who is using this database is validating in some aspect. Cool. Let's move on to the contractor side. So contractors or builders, they also usually want to validate something.

They want to validate that the data they are receiving from design teams is buildable. Is the data quality of this data set good enough for me to build? Yes, no?

So they run the same validation that the building owner runs. But they also want to add the data to the architects and engineers, BIM. So remember this point about autonomy that I talked about before?

So one way-- and this is the same process that [? Relish, ?] the Danish contractors, are using, only here, I'm showing it in Revit instead of IFC. They have a Excel spreadsheet that looks like this.

First, on the first row, I have a key basically, the type. This is the type name in Revit. I'm using that as a key to identify the elements inside the Revit file.

And then, I'm basically just adding a bunch of data here that it does not make sense for a contractor to call the architect to put into the elements in the facade, in this case.

So, they would just do it here externally or inside of the database. In Anker you can do that too. But it's really nice in many ways I suppose, for a lot of people to just work in Excel.

So they save this file, upload it to Anker. And then the Anker relationships that I've set up here-- I'm not going to go through the user interface of this because it's a little bit clunky --but here I basically match the CSV file with the Revit file.

Say something about which parameter I'm going to use for the matching. And then when this runs, it populates the elements. Let's go and see it.

I'm going to look at a table. So these are all motherplanks. I'm going to open the Motherplank table. Here are all my motherplanks, 370 motherplanks.

And then, let's see, we have manufacturer and PVB couleur. I'm going to add a column. Manufacturer and then PVB couleur. It's a French project.

Oh. There we go. So all of this has been published from the Excel spreadsheet. I know this is not the first time ever in the history of the world that someone built an Excel link to Revit. Not at all.

But it's really potent that it can talk to both Revit files and IFC files, and that it's completely scalable in a web database like this. It just becomes much more available or accessible for a lot of people.

So the last thing that I want to show then is how designers relate to a product like this. So maybe the biggest value proposition that designers have when they use a product like this, is that it's kind of like a script, or a set of scripts.

I think I told someone a few days ago, that it's like 1,000 Dynamo scripts that are running all the time. A lot of architects and engineers have already built solutions that kind of do this. I've done that before many projects.

But all these scripted solutions that people have to run, actually people have to run. So it becomes a vulnerable process in a project when you have like one Dynamo expert or one BIM manager who needs to go into every single Revit file and run a bunch of scripts before every deliverable.

So instead, what our clients do is that they go to the Populate tab, and they set up these rules for population, which is data creation basically. This one, I asked first-- there's a filter --I ask if the file property-- and here I can search for anything --is this Revit file.

And if it is, then every single element that we extract from that Revit file into the database is going to get these parameter values. Asset number, asset name, designer, contract, blah, blah, blah, and so on.

And you can add-- there's no limit to the amount of things you can add to this. So that's cool. And then you can run this population. When you do, and you can review the data inside of Revit.

Like I can click on this panel and then see, oh, here's my data, blah, blah, blah, blah, blah. All these numbers came automatically. I can do that. And then I can link the data from the Excel spreadsheet.

Like this is what that looks like. I won't go into the details here, but I'm basically saying I'm going to push to this property from this property using this link.

And then, this one. I've set up a population that writes a bunch of data-- or this is three data. Three properties here that are being written from a link property that I've created that's called the Project Breakdown Structure.

Remember what I said before about the control area, and all of these properties, and so on? I have a property called LOIN. I have a property called Levels. I have a property called Control Area.

And in this algorithm, I'm basically just writing all of that data from a project breakdown structure that looks like this. It's as simple as it can get.

This is a mass element in Revit. This is a mass, and this is a mass, and this is a mass. And you can do this with any geometry really, you can build up an in-place generic model, or mass, or even stuff imported from SketchUp or Rhino.

Or you can match between doors and walls, and so on. So you can build relationships between elements in Revit, and then push data from one to the other.

So in this case, I'm-- oh, look at my wrong value. I have a wrong value here from a demo I did before. This control area is supposed to be 47-54.

Here is 47-52. And this is supposed to be 47-53. So I'm going to change that here, 47-53, like this. And then I don't need to do anything, actually. It's just updated in the database.

So the last thing that I'll show in this case, because, right now I haven't really done anything else than build a new Dynamo script. I haven't run. I have to run this population.

So what is the maximum value proposition of a process like this is that everything can be automated. When you take this data out of Revit, you don't need to open Revit or Revit models anymore.

People don't have to do it. So then, I'm going to set up an automation algorithm that is going to do a bunch of things. A bunch of things.

I'm going to open this automation. And automation are the easiest and most powerful thing or feature in a system like this. I'm going to say that when any of the files change, and that can be any Revit file, any IFC file, or any CSV that you put into the system, then I'm going to either validate or populate.

Usually, I populate before I validate. So I'm going to set up the outer skin population, and then I'm going to add and say, let me validate also, after I have populated.

Cool. Then what happens now? Let me go into Revit. Remember, I changed this value. And when I go and click on these facade panels, they have the wrong value.

So now, Anker is going to copy the data from this element, to this element, but it's going to do it based on an automation. So I'm just going to go and save this Revit file.

And then, remember, everything gets extracted to the Anker database. The Anker database collects all the data from this Revit file. The changes at least.

And then, once that happens, my automation starts running. And that is really cool. So you can have these algorithms set up. And then look, most of my data and outer skin validation and population that I created before are now running.

You can see down in the bottom right corner. And in this way, you can make sure that your entire data set across hundreds of files is always up to date. And the validation is always up to date.

So now, this is done. I can go and validate most of the data. I don't have to run it again now because it already ran seven seconds ago.

I can open the validation results. Wow! Voila! 100% pass everything is correct. I wonder why? Tables. I can check out the panels in my table and see oh, actually, here now every control zone is correct.

And when I go back into Revit, I can even do like a visual check. I can do a [NON-ENGLISH], as it's called in Norwegian. Click on single elements and review the data in the database.

Or I can open either the validations, or the tables that is inside and both select elements. This is selecting elements in Revit based on the database in Anker.

And I can color elements. So let's go and see panels. Yeah. This table here that shows me the panel is sorted by control area.

And let me-- I'm going to find-- oh, profiles. That's better, because I've built up a nested family system here so it's not going to color anything. The panel is an empty family.

So if I color this, it will actually color my elements. These are the profiles on the outside of the outer skin, by control area. So, this is really, really-- I see here the property didn't update yet.

It's probably still writing that data into the Anker database, but this is really, really potent stuff. And that concludes the demo. I'm going to head back now to the presentation and close this off.

Now we have talked about mindset and tools. Most people who deploy a workflow like this in a project, they set it up in this way. You import the properties of the client, or the owner, or the contractor into that database.

You let the BIM feed the elements and the property values in that database, but use the database built in population to generate most of the values.

The metadata at least, that's needed for digital construction. Remember all those text and numbers? You use it as a-- some people call it an alphanumerical database that produces the construction ready BIM.

You run it through a check for everyone in the project to see. Everyone needs to see the data quality for it to be important. If not, it becomes something that just exists on the BIM Manager screen.

You publish it to the common data environment for everyone to take part of the issue tracking, and communication, and sharing of data, and then run it through a check again after it's been published to the common data environment, before it goes out to construction sites on these tablets and BIM kiosks that people are now using across the globe and onto operations, so that the owner can have their, if not digital twin, then at least the digital twin underlay.

What does this look like in the future? Where do we want to go? Are the information requirements going to go down this graph that is increasing?

I think it's going to flatten out a little bit, it's not like we're going to have 10 million properties in the future. But more, and more, and more owners of course, are going to start mandating information.

Will they ask for the same information? I don't know. But imagine you're an architectural firm and you have 20 different clients, and they all have different information needs. Are you going to build up 20 different Revit libraries? I don't think so.

So where I want to go with this, and what I see a good solution for the future, and what I'm talking with my colleagues, the people I work with about, and where we are heading trying to do, is to build something that will generate all of this setup that you saw me doing before.

I think that a really, really potent and helpful tool for the future of this industry, that can help digitize the entire industry, will do that. We need to ask our computers to do the boring stuff so that we can build, and own, and design.

And then let computers generate the data that we need in the exchange between these people. So if we are able to, and I think we will be able to, build some kind of--

I'm so afraid of using the word AI, please don't kill me --but some kind of generator. Imagine that you can load the client's information requirements in together with the standards in your local region with the BIM that the design teams are using.

And then automatically create all these cards that we saw in the database. That's all we have to do. Create the algorithms. Can we get an AI to create the algorithms and then let that run all the time so that you always have an updated data set?

And it can be flexible. If you're an owner, you have a data set that's three years old, you don't want to call the engineer to change the classification system of your data set.

You can just upload it to the database, and then upload the new requirements, and it can update and change the data. If you can do that, we are going to be in a beautiful world in the future.

And what gives me goosebumps when I talk about this is that I know that this work is vital for the digitalization of the AEC industry.

A lot of other industries can use AI for a lot of the stuff that they are doing because their data is consistent. They have consistent data sets of their work for decades before.

And we have just started now in the building industry. And we need to solve this data consistency across clients, across regions, across design offices, to be able to build more efficient processes.

And that concludes my presentation. I thank you so much for your attention. If you have any questions to me, reach out to me on the email havard@ankerdb.com, or check out our website Ankerdb.com.

And I hope you liked this presentation.

______
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We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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