Will Cadell is the founder and CEO of Sparkgeo.com, a Prince George-based business which builds geospatial technology for some of the biggest companies on Earth. Since starting Sparkgeo, he has been helping startups, large enterprises, and non-profits across North America make the most of location and geospatial technology.
Leading a team of highly specialized, deeply skilled geospatial web engineers, Will has built products, won patents, and generally broken the rules. Holding a degree in Electronic and Electrical Engineering and a Masters in Environmental Remote Sensing, Will has worked in academia, government, and in the private sector on two different continents, making things better with technology. He is on the board of Innovation Central Society, a non-profit society committed to growing and supporting technology entrepreneurs in North Central BC.
I’m not really old enough to reflect on cartography and its “nature”, however I want to comment on a trend I see in the modern state of our art and suggest a pattern back to an old truism.
At Sparkgeo we have a unique position in the market. Let me clarify that position, we create web mapping products. Meaning cartographic or simply geographic products which are built for people to consume primarily via web browsers. Additionally, we are vendor agnostic and continue to push the idea of geographic excellence & client pragmatism rather than particular brands. We work with organizations as diverse as financial institutions, startups, big tech, satellite companies and non-profits. In essence we build a lot of geographic technology, for a lot of very different organizations. We have also created paper maps, but in the last half decade I haven’t created a paper product. Not because we haven’t pursued projects of this nature, but because no one has asked us to. To be clear, we have created signage, for trail networks and such, but our activity with personal mapping products has moved to the web almost completely.
Telling. But not entirely surprising given that maps are largely tools and tools evolve with available technology.
Our position in the market, therefore is as a company creating cartographic products using the medium which is most pertinent to the users of that product. In the vast majority, those users are on a computer or most likely a mobile device.
Maps are of course defined by their relationship between things and people. An art form which links people to events and things on our (or indeed any other) planet. People and places, my friends. This will be obvious to most of my readers here, but what may be less obvious is the linkage therefore that our industry must have to cities. More-so, that cities and indeed urbanization have and will continue to craft the art of cartography for our still young millennium.
I say this whilst flying from one highly urbanized place to another, but also whilst calling relative rurality home. I am a great fan of open space, but even I can see that large groups of people are sculpting the future of our industry. It could be argued that cartography was originally driven by the ideas of discovery & conquest. Conquest or our more modern equivalence, “defense” is still very much an industrial presence. Subsequently, it could be argued that ‘GIS’ was driven by the resource sector, indeed much effort is still being undertaken in this space. I would have, until the last half decade, still argued that geospatial was in the majority the domain of those in the defense trade and the resource sector. Not so now. We have become an urban animal and with that urbanization it is clear that the inhabitants and administrators of our cities will drive geospatial. Cities and their evolution into smart cities will determine how we understand digital geography.
Let’s take a look at some of the industrial ecology which has enabled this trend. My hope is to engender some argument and discussion. Feel free to dissent and challenge, we are all better for it. I want to talk briefly about 5 key features of our environment which have individually, but more-so together, altered the tide of our industry.
It is clear that the general trend has and is continuing to be for people to move toward cities (https://en.wikipedia.org/wiki/Urbanization_by_country). Now, though I dispute that this is necessary (https://www.linkedin.com/pulse/location-life-livelihood-will-cadell), I cannot ignore the evidence that clearly describes the mass migration of people of most nationalities towards the more urbanized areas of their worlds. Our pastoral days have been coming to an end for some time. We will of course always need food, but the vast majority of Earth’s population will be in or around cities. The likelihood of employment, economy, and *success* are central to this trend it seems.
Where there are people there is entrepreneurism, administration and now, devices. Entrepreneurism and devices mean data; administration and devices mean data.
Our world is becoming urbanized and our urbanized world is connected. Our devices, our sensors, are helping to augment our realities with extra information. The weather of the place we are about to arrive at, the result of a presidential debate, the nearest vendor of my favorite coffee and opinions disputing the quality of my favorite coffee. Ah, the Internet. My reality is now much wider than it would have been without my device. Some might argue shallower too, but that is a different discussion. The central point here is that my device detects things about my personal universe and stores those data points in a variety of places. I now travel with three devices: a laptop, tablet and phone. This would have been ludicrous to me a decade ago, but much of what I do now would have been ludicrous a decade ago. We truly live in the future. Much of that future has been enabled by devices and our subsequently connected egos.
Devices capture data. Really, all a device is is a node attached to a variety of greater networks. Whether those networks are temperature gradients, a telephonic grid, home wifi, elevation or a rapid transit line, the device is simply trying to record its place in our multidimensional network and relay that in some meaningful way back to you and likely a software vendor. Devices capture and receive data on those networks. That data could be your voice or a location, and that data could be going A N Y W H E R E.
But, the fact that the data is multidimensional and likely has a location component is critical for the geospatially inclined amongst us. The crowd-sourced effect, coupled with the urbanization effect equal enormous amounts of location data. That is the basic social contract of consumer geospatial.
Of course, the abilities of our devices are magnified by connectivity, wifi, or whatever. Although Sparkgeo is still creating online – offline solutions for data capture, these are becoming more an exception than the rule. Connectivity is a modern utility, it is a competitive advantage that urban centers have over rurality. With increased connectivity we have great access to data transfer, connectivity is thus enabling geographic data capture. Its presence encourages the use of devices which captures data which is often geographic. Urban areas have greater access to connectivity due to the better economies of scale for the cellular and cable companies (who are quickly becoming digital media distribution companies). It is simple really; more people in less area equals more money for less infrastructural investment. For the purposes of this article in reality we just need to concede that those multitude of devices talked about above are more connected for less money in cities than anywhere else.
Compute is the ability to turn the data we collect into ‘more’, whatever that might mean; perhaps some data science, or ‘analysis’ like we used to call it, perhaps some machine learning. In essence compute is joining data to a process to achieve something greater. Amazon Web Services, and subsequently Microsoft’s Azure and Google’s Cloud platforms have provided us with amazing access to relatively inexpensive infrastructure which supports the ability to undertake meaningful compute on the web. Not enough can be said about the opportunity that increased compute on the web provides, but consider that GIS has typically be data limited and RAM limited. With access to robust cloud networks, those two limitations have been entirely removed.
People and devices mean data. Without doubt, lots of people and lots of devices mean lots of data, but there is also likely a multiplier effect here too as we become accustomed to creating data via communication and consumption of digital services. As an example, more ride-sharing happens in urbanized locations, so more data is created in that regard. Connectivity to various networks enabled those rides. Compute will be applied to those recorded data points to determine everything from the cost of the journey to the impact on a municipal transit network and congestion. At every step in that chain of events more data was created, obviously adding more data volume, but also greater opportunity for understanding, of what is yet to be seen. Beyond consumer applications however, city administration and their data also play deeply into this equation.
With these supportive trends we have seen two ends of our industry grow enormously. It is a wonderful, organic symbiosis really.
On one hand we have the idea of consumer geospatial (Google Maps, Mapbox), which has put robust mapping platforms in the hands of everyone with an appropriate device. Consumer geospatial has enabled activities like location based social networks (Nextdoor), location based advertising (Pokemon Go), ride sharing (Uber, Lyft), wearables (Fitbit, Apple watch), quantified self (Strava, Life360), connected vehicles (Tesla, Uber), digital realty (Zillow), and many others.
On another hand we have seen the rise in the availability of data, and in particular open data. Open data is the publishing of data sets describing features of potentially public interest such as financial reports, road networks, public health records, zip-code areas, census statistics, detected earthquakes, etc.
The great promises of open data are increased transparency and an enabling effect. The enabling of entrepreneurism based on the availability of data to which value can subsequently be added. Typically, bigger cities have more open data available. This is not always true, and the developing world is still approaching this problem, but in general terms a bigger population pays more tax which supports a bigger municipal infrastructure which therefore has the ability to do ‘more’. In recent discussions I am still asked if those promises are being kept, is the investment worth it? The idea of transparency is ‘above my pay grade’, but I can genuinely attest to the entrepreneurial benefit of open data. Though, that benefit might not be realized in the geographic community where the data is published. As a community of data consumers however, we do benefit through better navigational aids, more robust consumer geospatial platforms and ‘better technology’. As a company we at Sparkgeo have recently built a practice around the identification, assessment, cleansing and generalization of open data, because demand for this work never ceases. It’s clear that our open data revolution is in a somewhat chaotic (*ref) phase, but is very much here to stay.
Our geospatial technology industry has taken note too. Greater emphasis from Esri on opening municipal datasets through their http://opendata.arcgis.com/ program is an interesting way for cities who might easily already be using Esri products to get more data “out”. Additionally, Mapbox Cities (https://www.mapbox.com/blog/mapbox-cities/) is a program which is also looking at how to magnify the urban data effect. Clearly there is industrial interest in supporting cities in the management of ever growing data resources. Consider that Uber, an overtly urban company is building its very own map fabric.
If we combine the ideas of consumer geospatial and those of open data, what do we reveal? Amongst other things we can see that more & better data result in many benefits for the consumer, typically in the form of services and products. But we can also see that too much focus on the consumer & crowd based data can be problematic. Indeed, the very nature of the ‘crowd’ is to be less precise and more general. The ‘mob’ is not very nuanced, yet. For crowd based nuance, we can look to advances in machine learning and AI. In the meantime, it’s great to ask the crowd if something exists, but it’s terrible to ask the crowd where that thing is, precisely.
> “is there a new subdivision?” – “yes!”
> “When, exactly should my automated vehicle start to initiate its turn to enter that new subdivision?” – “Now, no wait, now… stop, go back”
Generalization and subsequent trend determination is the domain of the crowd; precision through complex environments is something much more tangible, especially if you miss the turn. As we move towards our automated vehicle future, once that vehicle knows a new subdivision exists, then conceivably it can use on-board LiDAR to provide highly detailed data back to whomever it may concern. This is really where smart cities need to enter our purview. Smart Cities will help join the consumer web to the municipal web, and indeed numerous other webs too. Not to be too facetious, but my notion of consumer geospatial could also be a loose description of an Internet of Things (IoT) application. Smart cities are in essence an expansive IoT problem set.
It’s clear that cities with their growing populations have in-part driven our understanding of people and digital geography through greater data volume. But as we push harder into what a future smart city will look like, we will also start to see even greater multiplier effects.
One thought on “Will Cadell: “Cities are people, and people are maps””
Much of this depends on data quality (the subdivision example is a good one). A self-driving car needs to know what data sources to trust and perhaps have some internal logic to do a self-assessment of the data quality independently of the sources. I could see a future in which the user/car/device compares several open and proprietary data sources and decides which one to believe (or it may choose to believe none, or to automatically update them with new info). It reminds me of the early days of GPS when people drove cars into canals by blindly following directions.
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