Tag Archives: Universite Laval

Paper Spotlight: Examining Urban Reasoning Skills in the Age of Digital Cities

Smart citizens of the future must develop the skillsets required to understand spatio-temporal interactions in dynamically linked urban networks of places according to Geothink Co-Applicant Stéphane Roche (Photo courtesy of http://www.i2cat.net/sites/default/files/smart-city.jpg).

By Drew Bush

In a paper published this past May, Geothink Co-Applicant Stéphane Roche posits that emerging smart cities require citizens to develop an urban intelligence that meshes material realities with digital information. In order to fully manage and engage with urban spaces, future smart citizens must develop the skillset required to understand spatio-temporal interactions in dynamically linked urban networks of places.

Stéphane Roche is a professor and vice dean of research for the Faculty of Forestry, Geography, and Geomatics at the University of Laval (Photo courtesy of www.scg.ulaval.ca).

Entitled Geographic information science III: Spatial thinking, interfaces and algorithmic urban places-Toward smart cities, the paper was published in Progress in Human Geography. Roche, a professor and vice dean of research for the Faculty of Forestry, Geography, and Geomatics at the University of Laval, has previously written two papers on the subject. The series of papers defines urban intelligence, the importance of spatial reasoning in smart cities, and the organization of digitally enabled cities.

“Most of the resources that are today available in order to help people to move in the city, are available—are digitally available,” Roche said. “[Yet] at the same time, mobility in the city is really grounded in the materiality. If you need to walk or if you need to take your bike, it’s an active kind of mobility. And if you don’t really know perfectly the places where you need to travel, you need to have the minimum capability to access information from different kinds of interfaces. Through your phone, through the Internet, through a different kind of display available in the city for example.”

Transportation presents but one case study for examining the integration of digital technology into physical urban places. Roche expands on this interaction to further define place as consisting of three elements: 1) A geographical location; 2) An event (such as an accident, festival, or meeting); and 3) A name. This, of course, means that two separate places could involve the same physical space but at different times.

As you may imagine, this type of insight takes time to develop. After reflecting on the existing literature in the field, along with his own previous work, Roche begins his first paper, Geographic Information Science I: Why does a smart city need to be spatially enabled? by emphasizing the importance of Geographic Information Science (GIS) to smart cities. He argues that the smart city is first and foremost a spatially enabled city.

His second paper, Geographic information science II: Less space, more places in smart cities, Roche advances the idea that modern cities consist of networks of connecting places, amends the very definition of place, and posits urban intelligence as the capability to understand how urban places are created and how they interact. Finally, his most recent third paper comes full circle to question why people who have developed urban intelligence necessarily also employ spatial learning and reasoning skills.

“Actually, what I’ve tried to do in this report is probably link what I define as the urban intelligence,” he said. “That means the capability of someone, people, or a group to understand the urban dynamic by using spatial skills and spatial thinking abilities. That means making the link between different components of the urban environment. So this is what I define as the urban intelligence. The capability of understanding what’s happened at the specific time and specific place.”

“The aim, ok, is to say in our current modern environment, there are multiple opportunities and tools and approaches that could help humans to improve their spatial thinking ability,” he added. “And these improvements will be more and more required if people want to engage. That means they will, there is no way to keep them engaged without spatial thinking abilities in this kind of new urban environment where everything is connected. Where everything is based on dynamic fluxes and mobilities. So if you are not able to understand how those dynamics work, you will have more and more difficulty in getting grounded in the place where you live.”

Please find links and abstracts to each paper mentioned in this article below:

Abstract 1
Geographic Information Science I: Why does a smart city need to be spatially enabled?
In this report I propose to examine the concept of the ‘smart city’ from the standpoint of spatial enablement. I analyse emerging research on smart cities, particularly those addressing the potential role of GISciences in the development and implementation of the concept of smart cities. I develop the idea that the intelligence of a city should be measured by its ability to produce favourable conditions to get urban operators (citizens, organizations, private companies, etc.) actively involved into sociospatial innovation dynamics. To obtain such a commitment, I believe that operators should be able to develop and mobilize (digital) spatial skills so that they could efficiently manage their spatiality. In other words, I argue that a smart city is first of all a spatially enabled city.

Abstract 2
Geographic information science II: Less space, more places in smart cities
This second report is dedicated to the concept of ‘place’ revisited in the context of smart cities. Some recent studies suggest that today’s digital cities rely more on an approach to the urban context based on a network of connected places than on an approach to the city built on areal spaces. Does it mean that there are more places and fewer spaces in spatially enabled cities? Is the intelligence of a city mainly related to its ability to sound out the genesis of urban places? These issues raise questions about the design of spatial models used to build GIS, as well as place-based urban design methods and tools. This second report explores these questions from the standpoint of GISciences.

Abstract 3
Geographic information science III: Spatial thinking, interfaces and algorithmic urban places—Toward smart cities
This third report examines interfaces as a key element enabling spatial skills, and development of new forms of digital spatialities for smart cities. Digital technology is becoming consubstantial to urban materiality, but map interfaces are particularly central tools for indexing (geographic) knowledge and expertise, accessing informational components of digital cities, and actively engaging digital dimensions of urban places.

If you have thoughts or questions about the article, get in touch with Drew Bush, Geothink’s digital journalist, at drew.bush@mail.mcgill.ca.

Spotlight on Recent Publications: Interrogating the Nature of Geosocial Data with Stéphane Roche

London Olympic wayfinding beacon (Photo courtesy of www.mudarchitecture.com).

By Drew Bush

In two articles published this January, Geothink researcher Stéphane Roche and his doctoral student Teriitutea Quesnot argue that not all geosocial data is equivalent, and that better data on the social significance of a landmark could greatly enhance our understanding of human wayfinding behavior. A Professor of Geomatics at University of Laval, Roche’s research over the past five years has focused on how new forms of digital spatiality affect spatial reasoning skills, and the capacity of individuals to engage in the city.

Entitled “Measure of Landmark Semantic Salience through Geosocial Data Streams,” the first paper was published by Roche in the ISPRS International Journal of Geo-Information. The authors write that a lot of research “in wayfinding is done in order to enable individuals to reach as quickly as possible a desired destination, to help people with disabilities by designing cognitively appropriate orientation signs, and reduce the fact of being lost.”

Previous researchers in the field of geo-cognition have tried to characterize the salience of landmarks in human wayfinding behaviour. Most have classified differing landmarks by visual, structural and semantic cues. However, the social dimensions of a landmark, such as how they are practised or recognized by individuals or groups, had been excluded from its semantic salience (or often reduced to historical or cultural cues), according to the authors.

Instead, the authors follow in a tradition of research which utilizes text mining from the web to understand how places are expressed by Internet users rather than relying on how they are visually perceived. Such an approach has been made possible by social media and mobile communications technology that has resulted in vast user-generated databases that constitute “the most appropriate VGI data for the detection of global semantic landmarks.”

In conducting their research, the authors examined world famous landmarks and detected semantic landmarks in the cities of Vienna and Paris using data from Foursquare API v2 and Facebook API v2.1. from September 29, 2014 to November 15, 2014.

In a second paper entitled “Platial or Locational Data? Toward the Characterization of Social Location Sharing,” the authors expanded on this theme in arguing that not all geosocial data is equal. The paper was presented at 48^th Hawaii International Conference on Systems Sciences this past January.

Some data, which the authors consider “platial,” relates more to users experiences of a given place while “spatial” data is tied to the actual coordinates of a place. In the context of geosocial data, spatial data might mean the exact location of the Eiffel tower while palatial could refer to a person passing by the Eiffel tower or taking a photo of it from another location.

Because each can potentially represent a very different kind of data point, they must be treated differently. As the authors write, “With the objective of a better understanding of urban dynamics, lots of research projects focused on the combination of geosocial data harvested from different social media platforms. Those analyses were mainly realized on a traditional GIS, which is a tool that does not take into account the platial component of spatial data. Yet, with the advent of Social Location Sharing, the inconvenience of relying on a classic GIS is that a large part of VGI is now more palatial than locational.”

Find links to each article along with their abstracts below.

Measure of Landmark Semantic Salience through Geosocial Data Streams

ABSTRACT

Research in the area of spatial cognition demonstrated that references to landmarks are essential in the communication and the interpretation of wayfinding instructions for human being. In order to detect landmarks, a model for the assessment of their salience has been previously developed by Raubal and Winter. According to their model, landmark salience is divided into three categories: visual, structural, and semantic. Several solutions have been proposed to automatically detect landmarks on the basis of these categories. Due to a lack of relevant data, semantic salience has been frequently reduced to objects’ historical and cultural significance. Social dimension (i.e., the way an object is practiced and recognized by a person or a group of people) is systematically excluded from the measure of landmark semantic salience even though it represents an important component. Since the advent of mobile Internet and smartphones, the production of geolocated content from social web platforms—also described as geosocial data—became commonplace. Actually, these data allow us to have a better understanding of the local geographic knowledge. Therefore, we argue that geosocial data, especially Social Location Sharing datasets, represent a reliable source of information to precisely measure landmark semantic salience in urban area.

Platial or Locational Data? Toward the Characterization of Social Location Sharing

ABSTRACT

Sharing “location” information on social media became commonplace since the advent of smartphones. Location-based social networks introduced a derivative form of Volunteered Geographic Information (VGI) known as Social Location Sharing (SLS). It consists of claiming “I am/was at that Place”. Since SLS represents a singular form of place-based (i.e. platial) communication, we argue that SLS data are more platial than locational. According to our data classification of VGI, locational data (e.g. a geotagged tweet which geographic dimension is limited to its coordinate information) are a reduced form of platial data (e.g. a Swarm check-in). Therefore, we believe these two kinds of data should not be analyzed on the same spatial level. This distinction needs to be clarified because a large part of geosocial data (i.e. spatial data published from social media) tends to be analyzed on the basis of a locational equivalence and not on a platial one.

If you have thoughts or questions about the article, get in touch with Drew Bush, Geothink’s digital journalist, at drew.bush@mail.mcgill.ca.

Accuracy, Authenticity and Technical Aspects of Privacy

At the Universities of Laval and Waterloo, we are interested in what is often seen as the “virtuous cycle” of citizens’ increasing use of open government data and, potentially, for governments to actively leverage information that the public creates. Our work centers on issues of accuracy, authenticity and privacy in citizen-generated spatial data and the changing relationships between governments and citizens in data provision and use. In Year 1, we are concentrating on assembling baseline information that will help us understand how citizens use open data from governments and the extent that Canadian governments’ currently leverage citizen-contributed data. In this first phase, we will assemble a literature review and survey government partners at local, provincial and national levels to:

Identify and characterize the main current open data initiatives (e.g., who is providing what data, in which forms?) and what data standards are used at local and provincial levels (if any?),
Identify existing as well as potential practices for: a) using crowdsourced data (including barriers and opportunities) and, b) for validating crowdsourced data,
Explore the linkages between open data (as a product and as practice) and crowdsourcing at the municipal and provincial levels (e.g. open data not only a service provided by the organization but also a way to improve data and by feedback loops in practice).

Two PhD students (Ashley Zhang – Waterloo, Teriitutea Quesnot – Laval) have been hired to jointly complete the literature review, survey administration and analysis and also participate in reporting the results through a journal paper. Teriitutea Quesnot is from French Polynesia. Teriitutea received his bachelor and masters in France and he has strong geocomputing and programming skills as well as consulting experience. Ashley is from China and has completed her Masters at the University of Georgia with a thesis focus on exploring spatio-temporal changes in the sociao-spatial structure of Beijing. Currently, her PhD research is centred on public engagement and place-making in smart cities. Since our government partners operate in both English and French, the survey will be bilingual to allow a pan-Canadian assessment to be developed. This information relating to current opportunities and barriers will help us develop new methods for promoting and visualizing data authenticity and accuracy. We anticipate that it also will contribute to project-wide efforts to develop best practices for Canadian governments to manage citizen-generated in light of data privacy and quality concerns.

We know that many of our partners and others have considerable experience in utilizing crowdsourced data. Even if you don’t then you probably have questions you’d like explored.

We encourage you to get in touch with us to enrich our research. Feel free to email stephane.roche@scg.ulaval.ca and robert.feick@uwaterloo.ca.