The Open Digital Lab is hosted on IBM Cloud and provides open source tools companies can use to create platforms and develop new services for customers. In the case of the Smart City Living Labs project, GeoSpock (a company that provides tools for data visualization and curation) and Sigma Systems (a provider of operational and business support systems including product catalog, ordering and inventory systems) are using the collaborative work space to build a data management platform for smart cities using real data from the City of Cambridge in the UK. The team demonstrated the Catalyst at Digital Transformation World last month.
“One of the things we’ve addressed as part of the Catalyst is the fact that cities really don’t have a good handle on the set of data they’re managing,” says Drew Jordan, Solutions Architect Director, Sigma Systems. “There’s a whole set of consumers out there that need access to this data and need to understand what’s there. It’s up to the city to have a system in place where they can identify where the data is and who’s allowed to access it – and potentially monetize that data because some could be valuable. The catalog plays a key role in providing this.”
City as a Platform
The team’s platform architecture adheres to the principles outlined in the TM Forum City as a Platform Manifesto and is based on the TM Forum Hybrid Infrastructure Platform, which provides a blueprint for platform management.
“We’ve come up with an architecture that covers many of the same concepts but is very much focused around what we can do pragmatically within the concept of this living lab,” Jordan says.
The team also has developed a metadata model to describe all of the aspects of the data. “Once you have that layer of building blocks for the data, we could see layering on top some services – so exposing the data as a service, but also integrating and mashing up the possibilities between the network services, mobility services, IoT and cloud and allowing the product managers for a city to innovate and come up with new products and services for citizens and businesses that are part of the city,” Jordan explains.
The team looked at four types of data:
- Observational – use cases that combine data so that cities can see how they’re working (or not).
- Transactional (monetized) – use cases that allow for monetization of data
- Transactional (not monetized) – use cases that require a controlled transaction but do not involve payment or monetization of a city resource
- Predictive – use cases that include automation
“Ultimately the goal for cities is to get to the point where they can do predictive analysis on the data they have,” Jordan says. “We haven’t made it to that point yet as a part of the Catalyst, but in our ongoing work we will head in that direction.”
City data is different
One thing the Catalyst team had to address was the fact that smart city data is different from telco data. It is usually siloed and most use cases aren’t transactional.
“This isn’t like a billing or CRM system,” Phil Claridge, Chief Architect and Strategist, GeoSpock, explains. “We have large sets of data which are both real-time and batch that we’ve got to correlate. And identity is a problem – there is no single person, like a SIM card on a telco network, to tie things back to. And the business models are emerging.”
The City of Cambridge wants to be able to collect, store and analyze data, and most importantly, they want to use it for predicting things like traffic congestion and population growth.
“Smart cities have hundreds of datasets that they’re collecting,” Claridge says. For example, many cities collect traffic light, bus GPS and air quality data. “But it isn’t cataloged or organized. There is no inventory of what’s there, and most queries they do are ad hoc.”
The graphic below shows the kinds of data Cambridge is collecting:
“Once we can start to catalog the data in cities and visualize and correlate it, we can get the big insights that cities require,” Claridge says. “The long-term goal for many cities is to get a ‘digital twin’ they can use to predict reality.”
He adds that the goal is to combine data from multiple cities in the platform. “They’re not in competition, so they can cooperate,” he explains. “If they can see other cities’ data, they can benchmark against it.”
Watch Claridge and Jordan discuss the Catalyst in this video filmed at Digital Transformation World: