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Jeff Thurston — “I think digital city models are continuing to evolve and will include a collection of models. Although some of the elements of these models may be similar, particularly foundation elements, model performance will vary for many unique reasons. The concept of a one-world model looks attractive, but reality for most cities varies widely. Technical performance is an integral component for digital city models but it would be incorrect to disconnect people, culture and history from digital city models.”

Matt Ball — “When considering an über model, there’s the issue of organization, and the need to determine whether the digital city will reside within an interoperable framework or as a central collective repository. Another way to look at this is to assess the different requirements of specific domains to determine if there’s a compelling need for separate modeling environments for different professions or workflows. The issue of ownership and governance of the model also comes into play, particularly in light of security-related issues, which will demand a level of centralized control.”

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I think digital city models are continuing to evolve and will include a collection of models. Although some of the elements of these models may be similar, particularly foundation elements, model performance will vary for many unique reasons. The concept of a one-world model looks attractive, but reality for most cities varies widely. Technical performance is an integral component for digital city models but it would be incorrect to disconnect people, culture and history from digital city models. 

The term digital city model conjures up many different perceptions today. Many people understand digital city models through the already existing work involving 3D city models. These models have become more digital in nature and more realistic, perfecting photo-realistic qualities and improving upon navigation and fly-through.

Another group of people consider digital city models from the perspective of infrastructure. In these cases, the common features including roads, pipelines, telecom, water and other easily recognizable features are often included in models of this type. Further down the line we find another group of people who consider digital city models to include 3D buildings, infrastructure and sensors as well as other supporting technology connected to them. 

The more I think about digital models, the more I think of them as economic forces – as evolving models of transformation, renewal, developing new directions and foundations for living tomorrow. They are more than technical interoperability. They are more than connectedness. They are more than placing all paper records into a digital format.

I’m not sure if many readers are aware of the Bentley Future Cities competition. I first came across it during my conference visit about 5 years ago. It amazed me because of the energy, thought and viewpoints of the kids involved in it – all designing what they considered to be cities of the future.  It is important to talk about how people see cities in the future, as we talk about digital city models. This competition is both an eyeopener and interesting for that reason. It is not surprising that Bentley speaks about advancing infrastructure, because it is a fundmental and required step to building efficient digital city models.

If you look at products like Cadcorp GIS you can see a very high level of interoperability included in their product design.  This tells me that they consider digital city models as having a high level need for interoperability. They envision data flowing from local governments and through other agencies with a need to connect, share and collaborate.  OGC standards are driving this approach and the products supporting a wide variation of participants and users connecting through processes.  This need for high levels of interoperability, through a distributed model approach, is also represented in the products and approaches of Safe Software that build on the transformation of data as it moves across processes and agencies.

Jack Dangermond of ESRI speaks about the Geographic Approach, which can be viewed as an encompassing model for a digital city that integrates geographic information of all kinds. He speaks about a distributed network of services and servers, common cadastral fabrics and other approaches that encapsulate the workings of a digitally constructed city.

Autodesk has announced a Digital City initiative as indicated in a interview recently. That initiative is interested in connecting the design environment to the construction processes and anticipates the realisation of benefits in time and financial saving. Yet, the tools involved to make this work are built upon a feature data model model (FDO) that fully integrates others work, even using different tools – again promoting interoperable workflows.

In reading the words of a recent interview with 1Spatial, I was struck by the thought that that company is considering how to make the whole flow of spatial information work across Europe and is considering new models for informatics with INSPIRE in mind, which will ultimately impact every city in Europe.

There are many company’s and products that are interested in the development of digital city models, and for many reasons. They participate and will interact with them at different levels and for different reasons. Each will have optimized software and tools which enable particular and unique performance. All will come together in unique ways, but the concept of a digital city model is something we need to develop further, and talk about.

Digital city models may have some common features and functions, but their data sources will vary and individual cities will evolve uniquely just as they do now. These models are fluid and dynamic. They will change form and shape as data, tools, knowledge and discovery all contribute to their growth and evolution over time.

It is becoming increasingly obvious that the cities of the future will become more digital. However, we also need to recognize that diversity is a positive factor and performance is crucial for these cities to be represented in their uniqueness as we harness the knowledge of new perspectives, ideals and energy for a sustainable tomorrow.

 

 

Geoff Zeiss of Autodesk moderated a spark panel at the GeoWeb Conference, and one question he posed that’s stuck with me is whether digital city models would become an über model or many models for specific domains. There are many ways to look at this question. When considering an über model, there’s the issue of organization, and the need to determine whether the digital city will reside within an interoperable framework or as a central collective repository. Another way to look at this is to assess the different requirements of specific domains to determine if there’s a compelling need for separate modeling environments for different professions or workflows. The issue of ownership and governance of the model also comes into play, particularly in light of security-related issues, which will demand a level of centralized control.

There’s no easy means to build a digital city model for wide interaction and adoption. The number of potential users is equal to the number of citizens that inhabit our real-world cities, and competing and overlapping interests makes it an impossible task to address the issues of all users at once. A measured approach with good groundwork is necessary, and first and foremost is a workable business model.

Common Framework
Given the complexity of our world, and the many digital means to represent it, the growing trend is toward common framework data and a means to interoperate. It’s simply too big of a challenge for one system or model to try and become a comprehensive representation of reality. Efforts that take this tact are bound to fail, because an inordinate amount of time will need to be devoted to create definitions and to resolve data conflicts among users.

The more realistic approach is to work on defining core data requirements for the basics of a universal shared model. This initial effort to define a common framework needs to be built upon standards, with an effort to develop model data and model exchange mechanisms at the outset. Establishing this core profile and functionality is much easier to maintain, and much easier for users to participate in. The less complex the core system is, the greater use and data it will receive.

The idea of an interoperable digital city model isn’t far removed from a system of systems approach. The key idea here is the creation of the shared framework and the means for different systems/models to interact with one another. The über model in this sense becomes the sum of all the separate models, and doesn’t exist in its own right without the input and participation from other models.

Domain Requirements
Ultimately, for the city model to perpetuate, it must engage a broad set of users that contribute their own data and expertise. The need for a large digital city model comes directly from specific domain requirements — planning, development, building, transportation, infrastructure, energy, water/wastewater, public health, emergency response and security. Each of these domains has realized the promise of the shared model to make our processes more efficient, reducing time and cost for our processes and making our cities more livable. And the model also represents a place where we can combine our domain knowledge and create multidisciplinary workflows.

It’s imperative that we stand up digital city models that preserve the characteristics and workflows necessary for multiple domains, yet realize the ability to share inputs and views from other stakeholders. There may be individualized digital city models for multiple domains, but what cannot happen is a redundancy of data collection and time wasting duplicated maintenance. We must get to the point of the core model, and then work closely with individual industries to preserve their way of working, while making certain that there’s no repetition of labor.

When the core model has reached a certain level of fidelity, it’s then time for individual domains to peel off and enhance the layers and details that they find necessary. There cannot be individual models for specific domains without the common model to begin with. If we don’t achieve this goal of a shared modeling effort, then we’re worse off than if we hadn’t started, for we’d step backward in time to the early days of digitization where competing efforts took many years off of progress.

Governance and Security
The issue of digital city model governance is a tricky one, yet there needs to be a strong effort here to avoid the issues of needless competition and redundancy that are stated above. The city model should ideally be administered by the city and its many citizens in a transparent and user-governed fashion. The city is a relatively neutral player that’s interested in seeing all domains successfully interact. With a board of directors structure for model governance, the individual interests of separate domains can be voiced and consensus can be reached on core platform issues.

The shared governance model can establish data sharing agreements to maintain intellectual property rights and security-related detail. There will be reasons why certain data types or levels of detail cannot be shared, and with transparency at the model governance level, the existence of certain data will be clear and available should an emergency situation arise where that data becomes critical information. The model sharing activity has the potential to engage many more domains than previous geospatial-centric data sharing efforts. The expanded community should gain the benefits of previous similar sharing efforts to reach model build out in the shortest possible time.

The über model is an old construct that cannot fly in the current information age. We need to create a model of amalgamated models, where shared effort is equaled by shared benefits.

 

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