Archive for November, 2015

GIS and Society: Towards a Research Agenda (1995)

Saturday, November 14th, 2015

Since Sheppard’s article was published in 1995, certain technological and societal conditions have encouraged GIS research to expand into GIScience, and thus current GI research has affected our modern “way of knowing” (9). For example: with easy internet access and norms, VGI developed and then affected society (e.g. citizens now check VGI-based traffic reports). Before delving into VGI’s involvement, I would like to reflect the social cognitive scientist Sperber’s theory on how societal norms develop onto GIS.

Dan Sperber argues there are certain private conceptions of reality and there are certain public conceptions of reality. These public representations are the ideals, beliefs, and epistemologies that are publicly held; however, they are generalized and do not properly represent intricate privately/individually held perceptions. These generalized public conceptualizations that are not consciously and frequently thought about (e.g. colonialism, capitalism), are what developed GIS originally and are also conceptions that GIS helps shape. Since Sheppard’s article, different generalized public conceptions have arisen, and these new publicly-held views have altered GIS. For example: inductive reasoning is now also considered a legitimate way of understanding truths, and because of this PPGIS and VGI were established. Although public conceptions of knowledge (including technology) have broaden, which allows more private (and marginalized) representations to be included, there are still underlying hierarchal epistemologies that GIScience still prioritizes, and thus will affect which research is more attractive. Since VGI focuses on “technological information” compared to PPGIS’s “cultural information,” VGI is more “attractive” in GIScience over PPGIS (Sieber and Haklay 2015, p. 11).

Moreover, Sheppard states that GIS will “develop far more sophisticated solutions” to “account [for] a greater detail and variety of information,” but “this capability can lead analysts” to focus on technicalities, thus losing “sight of the larger picture altogether” (14). I certainly agree with this statement because I have recognized this pattern while researching VGI. Originally, VGI issues focused on centralizing and standardizing data uncertainty (i.e. accuracy, credibility), which assumed universal standards to make VGI data valuable. This is similar to what we discussed in last week’s seminar, GIScience assumes there are universalities (i.e. “brute facts”) that can be compared, and, with this assumption, ontological patterns can be developed (Searle 1995). However, these publicly held assumptions do not account for all the privately-held variations. For instance, a VGI producer’s conception of data validity may not match the VGI user’s conception of data validity. Fortunately, some recent VGI researchers have recognized these hierarchical norms that assume universality within GI research, thus GIScientists, such as Fast and Rinner (2014), have argued that VGI should focus on how spatial data is collected within a system. In another case, Grira et al. (2009) argued that VGI producers should communicate properly with VGI users so that the provided valid spatial data can attempt to match the user’s perceptions of valid data.


Fast, V. and Rinner, C. (2014). A Systems Perspective on Volunteered Geographic Information. International Journal of Geo-Information, 3, 1278-1292.

Grira, J., Bedard, Y., Roche, S. (2009). Spatial Data Uncertainty in the VGI World: Going from Consumer to Producer. Geomatica 64(1), 61-71.

Searle, J. (1995). The Building Blocks of Social Reality. In The Construction of Social Reality. The Free Press, New York.

Sieber, R and Haklay, M. (2015). The epistemology(s) of volunteered geographic information: a critique. Geography and Environment, 1-12.

Sperber, D. (1996). Interpreting and Explaining Cultural Representations. In Explaining Culture: A Materialistic Approach. Oxford, UK: Cambridge.

An Example of Ontology Design Patterns (Sinha 2014)

Tuesday, November 10th, 2015

In studying Ontology, I constantly find myself searching for an overarching definition that satisfies all perspectives, philosophical and scientific, to mitigate my confusion surrounding the subject. I recently read a long article exhaustively exploring all aspects of ontology, but I found that clarity for this subject lies in application.

The main focus of this paper is the domain ontology, which are theoretical frameworks that apply to certain domains. The theoretical framework concept is an idea stemming from the scientific ontology. In layman’s terms these ontologies seek to standardize informal distinctions and definitions, such as the boundary between a boreal forest and a temperate rainforest. In the pacific northwest, these two biomes exist close to each other, but there is no formal boundary line universally agreed upon by scientists.

In his 2014 paper, Sinha et. al explore this same question, but rather than forests they explore  surface water features. The main goal of a domain ontology is to create an exhaustive and sturdy foundation for future study in a topic. In doing so, the researcher searches for the “most essential concepts of a domain” (15). How far must one go in defining and dividing a domain to create adequate definitions of features and classes that best display the relationships that compose that domain?



Smith and Mark – Folk Ontologies

Tuesday, November 10th, 2015

In this article Smith and Mark describe an experiment that investigates the possible existence of a “folk” geospatial ontology. The concept of different scientific fields all having a corresponding folk ontology is is fascinating. The notion that scientific ontologies actually have roots in their folk ontologies suggests that a scientific field comes about from a paradigm shift from the folk ontology. While the authors brought up the issue that the “legitimacy” of these folk ontologies is often brought into question, I wish they had gone into more detail about what constitutes legitimacy in these discussions. Also, I wonder if traditional Chinese medicine would be best described as a folk ontology corresponding to the scientific ontology of modern western medicine. The distinction between good and bad conceptualizations seemed slightly problematic to me. A good conceptualization is defined as one that is transparent to a corresponding independent domain of reality. A bad conceptualization, meanwhile, is associated with a pseudo-domain. However, isn’t it probable that in the future, conceptualizations that we currently consider good will be judged to be bad, and that domains of today will be regarded as pseudo-domains in the future? With regard to geographic folk ontologies, I’m not very surprised that folk geography was found to be a single ontology in this study. The fact that it is widely taught as a subject in primary and secondary schools around the world probably strengthens its unity. Geography has gone through so many paradigmatic changes since the 1950s, that what we may regard as a geographic folk ontology may actually be the remnants of what was considered the scientific geographic ontology half a century ago.



Functions and Applications of Spatial Cognition

Tuesday, November 10th, 2015

Spatial Cognition can be a misleading term. One of the authors first assessments is that one could argue all cognition involves space or exists in space, but it is important to distinguish between cognition that occurs within space and cognition that occurs about spatial relations, the latter being the concern of this paper. Spatial cognition also varies between individuals or sensors, given its interpretive mental component.

I find that unlike other topics we’ve examined as a class, spatial cognition plays a large role in one’s everyday life, but one does not realize this (at least consciously) until the term is defined. This unrealized component best fall under the second task involving spatial cognition, but also includes components of tasks three and four. I find these three categories to compose the most common and basic type of spatial cognition employed by most humans on a daily basis. Task 1 would have fit into this category before the mass production and utilization of mapping technology.

I am reminded of our explorations of  Inuit way-findings and how this difference in spatial cognition is entirely dependent on the use of technology. For iInuits, way-finding is a method of spatial cognition employed on a daily basis, similarly to use of spatial language, acquiring knowledge from direct experience, and using spatially iconic symbolic representations. This article has shed new light on the potential damage of cultural dissemination from settlers, mainly through the use of GPS. In my own experience, the application and utilization of the other tasks outlined on page 251 are very organic and uninhibited in nature. There is an individual freedom but collective benefit for each person gathering information from their environment and relaying or using this information. The impact of the GPS on Inuit culture and livelihood is not nearly as benevolent, but is rather a rapid and damaging infiltration that imposes on the six tasks outlined in Montello’s paper.





Geographical categories: an ontological investigation

Monday, November 9th, 2015

Ontologies are an area of study that is difficult to understand and apply to the world around us. My topic of spatial cognition closely ties into ontologies because it tries to categorize and understand representations of objects in the real world. For instance, spatial cognition address the same questions in Geographic Categories: An Ontological Investigation of where we end and the “outside” world begins. Trying to answer these questions of categories is very problematic because ontologies are closely related to epistemological frameworks. I’m surprised that Smith and Mark’s article did not incorporate epistemological frameworks. Cognitive geo-ontologies remind us that one can hardly discuss ontologies with out bringing up epistemologies. Better understanding of spatial cognition has the capacity to inform geo-ontologies because it examines consensus processes that contribute to constructing ontological frameworks. In addition, the interoperability of systems will depend on applying cognitive geo-ontologies  in order to uncover, “the relative semantic commensurability of different models of geographic phenomena in different systems” (Montello, 2009). We can apply cognitive geo-ontologies, therefore, to devise data standards and informational schemas that better categorize geo-spatial entities.

In addition, I’m a little skeptical of the claim in Smith and Mark’s article that ontology in the information science domain is, “a neutral and computationally tractable description or theory of a given domain which can be accepted and reused by all information gatherers in that domain”. Ontologies are linked to epistemologies, and these epistemologies of course exist within the context of power hierarchies. In other words, some epistemologies dominate and marginalize other epistemologies. Therefore, as we discussed in the Rudstrom reading about mapping indigenous places with GIS, can we say that ontology in information science ever exists in a neutral context?


Smith, Barry and David Mark. 2001. Geographical categories: an ontological investigation. International Journal of Geographical Information science 15(7): 591-612.

Montello, Daniel R. 2009. Cognitive Research in GIScience: Recent Achievements and Future Prospects. Geography Compass 3(5): 1824-840.

Thoughts on Spatial Cognition and VGI

Monday, November 9th, 2015

In his article “Cognitive Research in GIScience: Recent Achievements and Future Prospects”, Daniel Montello discusses some of the cognitive effects of the emergence of navigation systems as a “coordinated and goal-directed” form of travel (1828). In particular, Montello discusses how the designers of navigations systems seek to improve usability by providing “travelers with just the information they want and need, and not more,” and thusly, reducing the user’s intuitive sense of orientation in their environment (1829). In this topic, I see rich issues in several of the topics discussed in the course, as well as those I’ve encountered anecdotally.
One area that navigation systems and digital mapping platforms have spatial cognition implications is VGI. Personally, I am often startled to see how Google saves locations of places I’ve searched for in the past (e.g.: friend’s addresses, restaurants, cafés, etc.) and will show me these locations the next time I log in. Increasingly, Google is also becoming aggressive in its suggestions of similar venues, by either displaying the icons more prominently or suggesting them in auto-complete. For many people, Google Maps and other digital mapping interfaces are increasingly the only maps they consult, and increasingly, the ‘landmarks’ they are shown are personalized. My question, therefore, is what effect this will have on the on people’s experience of the city and, particularly, their tolerance of and exposure to third spaces that are not algorithmically calibrated for their personal preferences? If people begin navigating their city and consuming primarily based on their previously VGI-inferred preferences, will they ever have the opportunity to encounter people and places that will expand their awareness of people and communities outside theirs? My fear is that as geographic information becomes more fine-grained, comprehensive, and personalized, that people will be less likely to ‘stumble into’ places by chance, and that as the practice diminishes, it will be less acceptable to go to third spaces without fitting a particular target demographic.
Personally, I think that we should reconsider the way the VGI-derived information should be presented to end users. For instance, perhaps digital maps should first display a ‘base map’ which includes place names and neutral landmarks (e.g.: prominent buildings, parks, etc.), and then display the ‘personal’ layer only after the user makes a relevant search. This simple move could reduce the degree to which people use ‘personal’ landmarks which reduces their knowledge of other places in the area. Although this may slightly reduce usability, it could provide a less pre-determined and fragmented base for geographic cognition with the same community. I fear the emergent alternative could produce a form of soft ‘red-lining’ in user’s spatial cognition, where people’s geographic decisions about where to consume and where to go are reinforced by algorithmically determined paths, and thusly separating different social groups and cementing certain areas and businesses as economically prosperous or neglected based on their VGI footprint.


Breaking down Cognitive GIScience

Monday, November 9th, 2015

In “Cognitive Research in GIScience: Recent Achievements and Future Prospects” by Daniel Montello, the key aspets of cognitive GIScience are introduced. I feel like dividing the areas of cognitive GIScience into the six sections of “(i) human factors of GIS, (ii) geovisualization, (iii) navigation systems, (iv) cognitive geo-ontologies, (v) geographic and environmental spatial thinking and memory, and (vi) cognitive aspects of geographic education (1826)” as well as giving concrete examples of what each one meant, helped my understanding of the range of the field.

This paper had some very thoughtful observations about GIScience and I would like to bring attention to one paragraph in particular that encapsulates the challenges of studying GIScience to which I think our entire class can relate:

GIScience involves knowing about geography, cartography, surveying, mathematics, computer science, psychology, philosophy, linguistics, economics, sociology, and more. It is asking a lot to expect any individual to achieve expertise in such a diverse array of fields; integrating all of it is even more challenging. But it is just such an integration of many diverse areas of intellectual content and method that is the central challenge of GIScience. Arguably, without such a coherent integration, there is little warrant for referring to ‘GIScience’ as a single entity.

Being a competent GIScientist seems to necessitate both specialization in many topics yet also the ability to construct a general understanding of how they all combine. Under the topic of cognitive geo-ontologies, the idea of language being a limiting factor resonates strongly – I am constantly searching for more precise phrasing and sometimes get the feeling that if only the right words were invented then all the half-formed conceptual relationships in my head could become real.

On a completely different tangent, a few weeks ago we talked about how it would be a challenge for geographers to keep themselves relevant in the face of increased dependence on advanced coding and computer scientists to tackle GIS issues. This article mentioned how the intersection of cognitive neuroscience and GIScience has not been properly explored and it might be that area can give a chance for a new type of specialized geographer to employ unique beneficial skills.


An Ontology Design Pattern – Sinha et al. (2014)

Monday, November 9th, 2015

Returning back to my previous post’s concluding question, Sinha et al. (2014) make a statement that can provide some insight: “For a comprehensive understanding [“of different conceptualization systems”], substantial research on geographic cognition, nature of geographic categories, and naïve geography will be needed to discover general principles” (188). This statement relates to our discussions on Open Data last week, specifically how general standards need to be implemented in order to compare all the heterogeneous data. These general standards will develop through various research, including linked (open) data, spatial cognition, and spatial ontology.

Yes, I believe it is valuable to develop general categories that match physical facts cross-culturally; however, I wonder whether our increasing use of technology will dissolve the unique cultural ontologies that exist. Maybe they will be maintained orally, but how will marginalized ontologies be maintained and distinguished through the mass amounts of online data? This article describes the “Geo-Vocabulary Camp” as a “bottom-up” approach that involved “domain experts and ontology engineers… discuss[ing] and implement[ing] patterns for the geospatial domain” (190). Nevertheless, this workshop is still done by experts who, for example, may be taught a marginalized conception rather than actually experiencing first-handily a marginalized ontology. Let me clarify that I respect the team effort to develop ontologies, which shows just how complex and time-consuming it is to design ontological patterns (good luck Olivia), I just hope they include personal marginalized point-of-views in the decision-making scheme. I believe this is a more inductive process and allows more individuals to contribute as well.

As soon as I read the following statement, “a pattern needs to be generic enough to find recurring use in diverse contexts,” it reminded me about the anthropological debates I was taught (191). Within anthropology, structural anthropologists argued in the 1960s-80s that cultures across space can be compared by identifying underlying general patterns, however, post-modernist anthropologists argued back that these methods are too generalizing, ignoring the variations that exist between different individuals within the same space. With this spatial/cultural complexity in mind, and once we come up with a general standard for spatial data, then maybe (hopefully) we can reflect on how to incorporate all the specifics.



What IS a geographical thing? Smith & Mark 2001

Monday, November 9th, 2015

The article by Smith and Mark gives an overview of ontologies, and then explores how geography is defined by non-geographers. For me, this article (and the other by Sinha et al) brought up questions of the expert/non-expert dynamic. Particularly, one sentence was especially interesting to me: “Geographers, it seems, are not studying geographical things as such things are conceptualized by naïve subjects. Rather, they are studying the domain of what can be portrayed on maps.” This definitely ties into our discussions in class: geography doesn’t always have to be about maps and lat/long coordinates. How can we make more new and interesting ways to present geographical information? I would say that this is where GIScience enters the picture: as geography shifts from being cartographical, GIS provides a way to interpret and present geographic information that doesn’t necessarily need to be a map. However, clearly the non-expert, non-geographer hasn’t seen this shift yet, and still thinks of geography as just maps.

These thoughts are interesting for me to reflect on as I work on my own project, emotional mapping. From the perspective of the non-geographer, most people would not think to portray them on a map, therefore not making them geographical. The authors point out that geographical objects are not only located in space, but are usually part of the Earth’s surface. So, since it is difficult to argue that they are part of the Earth’s surface, can emotions be mapped? Are they geographical? I’m not sure of the answer yet. For now, I would suggest that they are dynamic features on the landscape of the Earth, which each person experiences differently.



Important frontiers of Spatial Cognitive Research – Montello 2009

Sunday, November 8th, 2015

Montello’s overview of research in spatial cognition highlights interesting paradoxes. Research on the subject has been quite extensive, yet the benefits of this research have so far been extremely limited. Yet the author advocates enhanced research on specific aspects of spatial cognition. In particular, research would be more useful if there was a greater emphasis on how to preserve human cognitive abilities while simultaneously achieving greater convenience in daily life through devices that are better suited to human cognition. I fear that this goal may be difficult to achieve when research is so industry-driven. Unfortunately the private sector probably has no incentive to prevent technological infantilization and would in fact have very strong incentives to encourage it. Another issue stressed by Montello which I found particularly interesting was that of how uncertainty metadata affects the decision-making process of users of geographic information. I wonder, however, what sorts of uncertainty metadata users are exposed to at all. GIS users with an academic background may be exposed to such metadata as standard error, but I can’t picture how uncertainty metadata could be presented to ordinary users of Google Maps, for example. I would guess that it would mostly be people from a particular educational and cultural background who think of uncertainty quantitatively. I suppose a good application of this research would be in the management of automobile traffic. Planners could provide uncertainty metadata about how bad traffic might be on certain route options, in order to bring about an optimal scenario of how many drivers opt for which route. They could thereby maximize the efficiency of the distribution of traffic. However, I think this would be greatly complicated by the diversity of conceptions of uncertainty between individuals and cultures.

– Yojo


Cognitive Research in GIS – Montello

Sunday, November 8th, 2015

The article by Montello introduces six areas of recent cognitive GIS research and raises many questions about cognitive research in GIScience. I found it interesting that Montello included questions about the discipline of GIS itself. For example, the author questions whether GIS is coherent as a discipline and can be referred to as a single entity, and if it is possible for any individual to know about and integrate all the different fields that contribute to GIScience.

One point I found especially interesting was that “GIS is not exclusively spatial.” In our discussions, we have not talked much about the distinctions between geographical and spatial. This statement, I imagine, would be rather mind-blowing for someone just starting in GIScience. It is true that GIS incorporates many other aspects: temporal, logical and informational. As we have discussed in class, the end products of GIS work doesn’t have to be a map (contrary to popular belief). Montello’s argument that much of the spatial cognition of using GIS “really just involves perceiving patterns on a computer screen” is a strong statement. It has implications about the usefulness of incorporating GIS in K-12 education. It also has implications for what GIScientists are really contributing if using a GIS “does not involve much spatial memory, inference or reasoning.” It’s certainly not an inspiring thing to read about a discipline that I am becoming increasingly interested in. But it certainly does provide a challenge: to use GIS in a way that DOES involve more cognitive heavy-lifting.



Cognitive Research in GIScience: Recent Achievements and Future Prospects: Montello, 2009

Sunday, November 8th, 2015

Montello provides a comprehensive review of cognitive GIScience work since the term ‘geographic information science’ was coined in 1992.He explains that it “concerns human knowledge and knowing involving geographic information and geographic information systems (GIS)” (1824). This article may have only mentioned ‘epistemologies’ once, however it ties in very well with the discussion we had in class regarding traditional ecological knowledge and, more broadly, alternative epistemologies, as well as our discussion on uncertainty. Despite this, I found it to fall short in some areas.

I found Montello’s highlighting of issues in cognitive GIScience that still require significant research to be thought-provoking (MRI scans and GIScience?), but ultimately I was not convinced by the piece alone that cognitive GIScience is important and that it can significantly push GIScience forward.

I understand that the subject is interesting; tracking people’s eye movements as they look at a 2-D map is ‘cool’ GIScience research, but how can it actually improve the way we make maps? How will teaching young children to ‘think spatially’ make them better citizens of society?

I suppose what I’m getting at is that the author highlights what’s been done in cognitive GIScience, and what lies ahead, but does not convincingly tell me why I should care. And that’s a problem. I’m sure people should care about these fundamental issues (as they should ontologies), but the potential of the field is not communicated clearly enough to readers. Montello admits that “the notion that understanding human cognition should help improve the use of geographic information and GIS makes sense and seems valid. But it must be noted that the applied payoff of cognitive GIScience research has been minimal to this point”. Perhaps the reason for this is more than just “economic and technological inertia” (1836).

While I myself can appreciate the field of cognitive GIScience – even in its “humble beginnings” form – I wonder how lay people and those in charge of allocating research funds to academics may perceive its usefulness.


Montello, D. (2009). Cognitive Research in GIScience: Recent Achievements and Future Prospects. Geography Compass, 3(5), 1824-1840.

An Ontology Design Pattern for Surface Water Features: Sinha et al. 2014

Sunday, November 8th, 2015

Ontology is the study of what a conceptual model should encapsulate to represent reality. But what about the when?

This week, I began reading the more theoretical article on geographic ontologies (Smith & Mark, 2001), but quickly found that the discussion was much too difficult to wrap my head around. I read Sinha and colleagues’ article hoping to understand why ontologies are important for GIScience, and indeed was able to grasp the theory of ontologies much better with the use of surface water features as an example of how an ontology is built, and why it is important to build in the first place.

While the article admits that spatial scale at which the features are represented is still a significant challenge to the success of this ontology (and others), I think that the temporal relationships between the features and the stochastic nature of the features themselves over time is and will be the biggest hurdle for this field of study. The varying levels of abstraction of the ontology appear to be effective in describing geophysical phenomena at first thought. However, the stochastic nature of many of these features (such as streams drying up or freezing) seasonally is important to include in an ontology of such features if the ontology is to be used for further study of landforms.

I found this article to be very helpful in teaching the geographically-inclined to better understand ontologies, but found it to be lacking in the discussion of temporality. That being said, I do not pretend do understand ontologies after having read these two articles alone. It is highly likely that the temporal characteristics of surface water features are captured at lower levels of abstraction in other ontologies that will be or already are connected to this surface water feature model.

My last thought regarding this topic is that of how geocomplexity fits into the conversation. I think that it is important to understand how people (not just academics) represent static snapshots of reality before attempting to represent and model dynamic systems. These articles made me realize that though the discussion around ontologies can be painfully philosophical at times, it is such fundamental issues such as these that need to talked about more, especially in GISCience and geocomplexity science.


Smith, Barry and David Mark. 2001. Geographical categories: an ontological investigation. International Journal of Geographical Information science 15(7): 591-612.

Sinha, Gaurav, David Mark, Dave Kolas, Dalia Varanka, Boleslo E. Romero, Chen-Chieh Feng, E. Lynn Usery, Joshua Liebermann, and Alexandre Sorokine. 2014. An Ontology Design Patter for Surface Water Features. Geographic Information Science, Lecture Notes in Computer Science Vol. 8279: 187-203.


Montello (2009)

Saturday, November 7th, 2015

Daniel Montello’s article (2009) provides a brief summary on cognitive research and its development within GIScience. Similar to what we discussed in our Indigenous Mapping seminar about GPS’s implications on way-finding, Montello argues that technology alters “how we think” by “reducing our ability to reason effectively without technology” (1835). Reflecting on my days in GEOG 201, I certainly can agree with this statement; I found students, including myself, were memorizing ArcMap’s tools at times instead of spatially understanding what certain tools do.

In another case, navigation systems within cell phones are shifting humans’ conceptions of space. Although our mobile phones are useful navigational tools and sensors, I also believe that it is important to maintain a strong cognitive map, or at least some basic spatial knowledge (e.g. the ability to know which direction one is moving). As for concerns over “‘infantilizing’” within my own topic, VGI scientists need to develop models that users can spatially understand (1835). Specifically, models that are visualized in a way that allows users to easily input their own geographic information (e.g. providing a user-friendly interface). However, VGI scientists are solving users’ lack of spatial knowledge through automatic algorithms as well (e.g. crowdsourcing user-generated data through coded filters). This means, VGI scientists are maintaining and standardizing people’s conceptions of space prior to input, and then solving “infantilizing” issues through refining data post-input.

This tug-of-war between the benefits of technology versus benefits of a strong individual cognitive map will persist because GIScientists are at a crossroads. Like Montello states, one of the most difficult obstacles for cognitive GIScientists, as well as other GIScientists, will be “to clarify its values in the design and use of geographic information technologies” (1836). As such, where do ethics come in? Is it more important for people to understand new ways of conceptualizing space (i.e. ‘infantilizing’), or is it more important for people to maintain old ways of conceptualizing space? How can we improve both at the same time? Furthermore, how can we consider different ways of conceptualizing space other than the Western centric model?


Spatial Cognition in everyday life (Montello and Raubal)

Friday, November 6th, 2015

As technology changes, so do our applications of spatial cognition. When reading this article, I first thought it was dated, as technology has replaced the need to imagine many spaces. Perhaps as a geography student I am biased, but for almost every small task I looked at travel times, Google maps transit extension for route planning, Streetview, and long hours on google earth which replaces the spatially iconic symbolic representation with a digital earth.

What I have learned from this article is that spatial cognition is not irrelevant in my technology-saturated life. A good example is how people perceive the distance of my apartment from campus. Technology tells us that I live 1.5 km west of campus whereas most of my friends live 1.5 km east of campus. Despite this similarity almost all these eastern friends have concluded at some point that I live “very far” from campus and getting there must be difficult. I propose there are several factors of spatial cognition that contribute to this spatial understanding as described in the article. Firstly these friends are not familiar with the area west of campus, so their wayfinding through experience abilities are limited. Navigating through the high-rises of the downtown core, you lose your common landmarks like McGill campus or Mont-Royal. The highrises block your view and therefore limit your spatial knowledge learned directly as well as inhibit your sense of orientation. I believe that these factors are why my friends have a limited ability to judge the distance of my apartment from campus. In terms of using spatial language, when explaining directions to my apartment from campus I say, “it’s just down from the Bell Centre.” I can justify this spatially vague language because most people have an understanding of how to get to the Bell center as it is a large landmark of the city. In addition, the ability for people to use smartphones if they get lost, means that my spatial language does not have to navigate people directly, only give them idea of distance base on their own acquired or imagined spatial knowledge.



Sagl: Contextual Sensing for Smarter Cities

Tuesday, November 3rd, 2015

This article examines incorporating spatiotemporal contextual information in the hope of creating smarter cities.

When trying to contextualize my topic of drones in GIS, I find myself wondering how it differentiates from just being a tool; a sensor on a new platform. One of the possible fields of research in drone GIScience is geofencing, whereby drones are programmed to not take off in certain areas and altitudes. The article mentions how drones could be used to monitor urban areas, but are not because of (good) restrictions. To create a smart city, one needs both sophisticated monitoring systems, and equally sophisticated systrems to keep out the unwanted sensors, like drones. One of the ways in which drones could be detected and regulated is through contextual sensing. For example, police use networks of microphones that collect noise data which is then processed to listen for drones. However there is not one sound that identifies a drone, and many other machines can sound similar, like a far-away leafblower. Therefore other sensors are needed to provide context to this noise. Another way drones are sensed is through optical sensors, which could identify a distant moving object and classify it based on its flightpath. However in order to distinguish a drone from say, an eagle, you would need to contextualize the optical information with thermal sensor information.

From this article I learned some terms that can be used to classify drone technology. An interesting aspect of military drones is that the US government uses “collective sensing” in order to establish the location of a target before using “classic sensors” as termed by the author to command the drone. Collective sensing is sensor data that users do not necessarily intentionally share, like there location generated from a mobile phone call. The problem though is that they do not bother to associate this data with any contextual information from other sensors, and so frequently make bad judgement calls. I think that contextual information in this form of sensing is important, but involves more of a political shift than a shift in GIScience.



Worthy – Open Data in the UK

Tuesday, November 3rd, 2015


This article looks at the complex effects of open data in the case of the UK government. The rationale of Open Data in this context was to democratize government, and devolve power to the people. With government spending open to the public, surely there would be more accountability, participation, and information transmission. As mentioned last week by CRAZY15, will the “certainty, validity and utility” of the data decrease as the quantity increases? I feel that similar to the way people behave on social media, governments will become more performative as their actions become more shared and open. The author states that governments have redacted sensitive information, and what is published lacks context. The result is that overall engagement by the public is low, and those who do engage have specific interests. One of the most successful examples of engagement was through a website created by This organization claims to “make websites that empower citizens worldwide”. An example of one of their other projects is “FixMyStreet”, an open source tool for reporting infrastructure problems to city council. I think that organizations like this are an example of progressive toolmaking in GIS, where VGI can be integrated with open data and effect change. Simply publishing data will not create armchair auditors; we need to create the tools to understand the data.


A Different Context for Smart Cities?

Monday, November 2nd, 2015

While I understand the importance of creating healthier, happier and more sustainable cities. “Contextual Sensing: Integrating Contextual Information with Human and Technical Geo-Sensor Information for Smart Cities” by Sagl, Resch and Blaschke seems to leave a lot unsaid. The authors talk about ‘smart citizens’ becoming bigger contributors to city dynamics but a lot of technological advancement so far has been in making it ubiquitous and as seamlessly fit into our lifestyle as possible so it is easy to ignore. It is very interesting to see the dissonance in presentation of information from Worthy’s article on “The Impact of Open Data in the UK: Complex, Unpredictable, and Political” where he describes how interaction with open data varies across heterogeneous groups. It brings to mind question such as: What would the ‘average’ citizen’s awareness of the smart city actually be? Would smart city data be open data? Who would use it? Furthermore, the feedback loop between smart citizens and beneficiaries seems to imply that people will become more externally engaged with their surroundings (17024), yet over time people have been narrowing their scope of interaction, especially in so-called third spaces, to their personal devices. I think there is some sense of taking for granted that all these environmental interactions will continue to exist with the increased saturation of technology in our lives.

Sagl et al. also remind me of our previous class discussion on big data. The authors deliberately state that more data does not necessarily provide better results (17017). However, when they state that “…in contextual sensing a larger quantity of data may allow contexts that have not previously been thought of, or have not previously been considered relevant, to be better understood and taken into account (17017)”, they also seem troublingly close to the trend of aimlessly analyzing masses of data that spits out patterns without scientific methods of inquiry. I think it would be very interesting indeed to have a skeptic of open and big data to analyze smart city trends. I do have to say that some of my questions are outside the scope of this article but the tangents to be explored are potentially more interesting.


Spatially (& Equitably) Enabled Smart Cities

Monday, November 2nd, 2015

Stephane Roche Discusses in his 2014 report in Progress in Human Geography the concept of a “spatially enabled city” in the context of “smart” cities. While the terminology alone inspires ideas of Utopian (or dystopian) futures, the conversion that Roche presents in this piece is very much grounded in reality.

I found the discussion with regards to the conditions that cities must meet in order to be considered “spatially enabled” in Roche’s view – spatially literate citizens, open data, and unified data standards – very interesting. What makes a citizen spatially literate? Does it require digital literacy as well? And what of Open Data (as discussed in Sundberg & Melander’s and Worthy’s respective pieces): Do global citizens or only local citizens truly have access to all this data? What are the repercussions?

I wonder as well how we will use the remote sensing data gathering techniques discussed in Sagl and colleagues’ 2015 article in Sensor to “spatially enable” cities. The first thought that came to mind when reading these two articles on smart cities is who do you consider to be citizens? Will smart cities devolve into having border control to stop digitally illiterate folk from obtaining residence status? Will smart cities be used as a tool to further stratify society?

My hope, of course, is that geospatial information & GIScience can improve society and reduce as much harm as possible. With that in mind, I look forward to see how scientists developing these remote sensing tools and “spatially enabled” cities use their knowledge and expertise to increase livelihoods at all levels, i.e., notions of equity and equality are not left behind in the dust, but rather woven into the fabric (or circuit board) of our evolving urban centers.



The UCDP GED & the Power of GIScience

Monday, November 2nd, 2015

Sundberg & Melander (2013) introduce the Uppsala Conflict Data Program (UCDP) new Georeferenced Event Dataset (GED) in their 2013 piece published in the Journal of Peace Research. The details of the dataset are presented in a concise manner, however I had to dig a bit deeper to find more information regarding the geocoding of lethal events. I found a very interesting article written by Kristine Eck (Department of Peace and Conflict Research, Uppsala University) that highlighted the geocoding procedure of the UCDP’s GED (see excerpt below):

The creators of the dataset appear to have really thought about that importance of communicating uncertainty to end-users of the database. The 3-step process includes manual input from “coders”, revision of entries by a supervisor, and a final verification of the entries with specific automated processes (scripts). I applaud the creators of the dataset for this rigorous verification of the entries into the dataset. Moreover, I am also happily surprised to read that the creators of the dataset have really thought about how to deal with uncertainty in the geospatial data (e.g. a fatal event that occurs “somewhere near place X”, or “In province Y”). The introduction of a system that assigns an integer value (1-7) to an attribute/event based on the precision of the geospatial information associated with the event itself is not particularly new: the Armed Conflict Location and Event Dataset – ACLED – has a 1 to 3 scale similar to the UCDP’s GED. What is noteworthy is the use of centroid locations, rather than important cities, as pseudo-locations to events that have vague event areas (and not so much locations).

While the sociopolitical ramifications of a database of this sort are important and should be debated, I really think that the authors and creators of the dataset have done a thorough job of thinking through the use of geospatial information within their data. They strive to minimize bias towards densely populated areas, and strive to maintain, not “improve” or “make more detailed” by introducing MORE error into the location information, the uncertainty in spatial information by using an uncertainty scale and using location information other than a a country’s capital city, for example, as the default location of events that have vague locations/areas.

I believe that this dataset is a great step forward for GIScience, as it has proven to be useful and arguably essential to the success of the UDCP’s GED. As for the Sundberg & Melander piece, I really wish they went more into detail about the decisions behind the georeferencing of these events. That’s probably just the (albeit reluctant) GIScience side of me starting to come out, though.

– ClaireM

Eck, K. (2012). In data we trust? A comparison of UCDP GED and ACLED conflict events datasets. Cooperation And Conflict, 47(1), 124-141.

“UCDP GED avoids a great deal of these problems through a triple-checking process. The first manual check is done by the coder, and the second by the UCDP project leader, who manually checks the data and uses Spatial Key, a visualization software for geographic data, to map the data and locate possible miscoded coordinates. In the third stage, automated scripts in Python and PHP are run to check for internal consistency in dates, actors, dyads, conflicts, and fatality counts. The automated scripts pick up problems like the same city being given different coordinates. The scripts normally pick up dozens of errors per country, suggesting that they are invaluable in the data-cleaning process.

The second recurring geocoding problem in the ACLED data is the misuse of the geoprecision codes. In ACLED and UCDP GED, a geoprecision code of 1 indicates that the coordinates marking the exact location that the event took place, usually a inhabited area. When a specific location is not provided, i.e. “Helmand province,” ACLED and UCDP GED employ different strategies for managing this issue. ACLED selects the provincial capital while UCDP GED selects the centroid point when available and the provincial capital when a centroid point is not available. One can debate which is the best practice, but what is crucial is that the data provider convey uncertainty about the location to the user. This is done through geoprecision codes; higher numbers on the geoprecision code indicate broader geographic spans and thus greater uncertainty about where the event occurred (the range for ACLED is 1-3, for UCDP GED it is 1-7).”