Connecting the dots with smart city standards
The British Standards Institute (BSI) has unveiled a series of smart city standards and publications developed as part of their Cities Standards Institute.
You’re not alone if the mention of standards initially triggers a fight-or-flight response out of trepidation for mountains of technical jargon, or worry that vested interests of industry incumbents might bias the formulation of such standards or, worse yet, lead to overly rigid constructs that could stifle the efforts of start-ups and grass-roots tinkering. Instead, the BSI is quick to assure that standards are not dry technical humdrum that tell us what to do, but rather provide a broader decision making framework to help find the right answers. The aim is specifically not to standardise the things that might yet change but rather the things that we might subsequently build on.
The development of the Smart Cities standards ‘stack’ includes several layers ranging from higher-level strategic thinking to very detailed specifics. Much of the initial content of the standards underpins discussion that essentially outlines processes of city management and procurement from the point of view of what exactly a smart city is, how to plan such cities to facilitate smart and resilient development, and how to procure smart city services in such a way that data and services remain open and interoperable.
The current smart city standards stack as gleaned from a slide shown at a recent BSI smart cities standards presentation:
Level 1: Strategic level
- Guidance for city leaders (PD 8100)
- Planning guidelines (PD 8101)
- Decision-making framework (PAS 181)
Level 2: Process level
- Data sharing framework (PAS 183)
- Guidelines for project proposals (PAS 184)
Level 3: Technical level
- Data concept model (PAS 182)
- Internet of Things implementation (Hypercat PAS 212)
- Building Information Modelling (BS/PAS 1192 series)
But do we really need smart city standards?
It may initially seem that Smart City standards will create lock-in and additional complexity, however, it can also be seen to lay the groundwork for longer-term collaboration and innovation. In fact, it could be argued that the evolution of the Smart Cities and urban planning industries is hamstrung until this happens.
We can look to the Architecture, Engineering, and Construction (AEC) industry and the evolution of Building Information Modelling (BIM) to better understand why. Whereas industry adoption of computers took root several decades ago, the way projects and workflows were approached initially didn’t change much at all. In other words, computers were really just glorified pencil and paper. Instead of smudging shirt-sleeves while crouched over drawing boards — or breaking and replacing the delicate and rather pricey nibs of drafting pens — it became possible to point and click to send multiple copies of a drawing to a plotter instead of choking on the ammonia fumes leaching out of blueprinting machines. The point being that the industry was basically still doing the same things using the same workflows, just with newer and more convenient technology. However, at some point something significant began to happen, which is that information and standardisation entered the equation and this information could be connected in spatially and functionally meaningful ways to other information. This heralded the arrival and subsequent evolution of BIM. With BIM, the initial models and templates take some time create, but once up and running they are increasingly powerful and automate much of the previously painful tedium involved in the production of construction documentation while paving the way to advanced performative modelling of everything from structural design to energy performance. BIM has consequently led to a more holistic and integrated approach extending from conceptual stages through to design, construction, and on to the full life-span of a building’s performance and management. (I realise it’s not always this rosy…)
The opportunities and challenges now faced at the urban scale are somewhat similar to the advent of BIM. Much of the work at this scale is analogous to the early pre-BIM stage, where new tools had arrived but were mostly being applied to the same old workflows. In other words, the important tipping-point where information connects seamlessly and meaningfully to other information has yet to be reached. Arguably, the main reason for this is the lack of a cohesive framework wherein we can easily combine ideas, data, and processes in new ways without spending the bulk of time simply getting different city departments, service providers, data APIs, and “Things” (as in the IOT) to talk to (or understand) each other. The effort of finding, cleaning, importing, and connecting urban data can easily take many times the amount of effort otherwise required for the subsequent modelling, analytics, and visualisation. To add insult to injury, these data munging workflows are not only tedious but also brittle, meaning that much of this work often has to be thrown out when changing to a different source or format of data.
A big thorn in the side of BIM is that it developed as a hodgepodge of proprietary software and data formats, something that has cost the AEC industry billions in lost productivity a year, and which is still being resolved. Yet, BIM was still able to hobble along because buildings are relatively self-contained. In contrast, nothing is self-contained at the city scale. For any kind of significant co-evolution of smart city ideas and services, a unified and transparent information framework is needed that not only organises random assortments of data, but that knows how one item might relate to another. This is why smart cities need data standards, interoperability of systems, and open procurement baked-in from the get-go.
Standards as a spring-board for innovation
The hope is that standards will permit sustained innovation by embodying earlier steps as a spring-board for subsequent steps, allowing new effort to be directed towards the synthesis of data and ideas instead of endlessly reprocessing data. Thus, in a perfect world, the explorative processes of innovation would occur in lock-step with the consolidative development of standards, neither of which should be static or existing in isolation. Lean too heavily in the explorative direction (i.e. too little support from standards), then too much energy is wasted in re-inventions and butting-of-heads due to a lack of compatibility. Lean too heavily in the consolidative direction (i.e. standards become too rigid), then you stifle innovation. For standards to remain relevant and helpful they’ll need to to remain open to stakeholder feedback and flexible to change.
Given the relative youth of smart city standards, much of the current documentation is broad high-level discussion and the more technical documents remain abstract. The challenge at present is how to extrapolate this framework into tangible tools and services that deliver new levels of efficiency and insight to urban planning workflows, without sacrificing interoperability and transparency.