Computers, Society, and Nature

The central argument of this paper is that quantitative and qualitative methods should be seen in terms of a continuum instead of as two separate toolboxes in conducting GIS research. I agree with this argument and I think that there is no clear boundary between quantitative and qualitative research. Most of the time in research we see that even though the method applied is quantitative, the problem it asks is inherently qualitative, and qualitative research also often contains quantitative components. This is shown in some AI research such as natural language processing. The tool itself is quantitative whereas the inferences it makes or the problems it solves are qualitative. In this sense, should there even be a line to distinguish whether or not the research is quantitative or qualitative?

I also noticed that even though this paper discusses a lot about the opportunities of qualitative research in GIS, it is still calling GIS a “tool” instead of a “science”, which reminds me of a lot id discussion in the class. This is kind of conflicting because the points the author made about how we research can be conducted surround GIS makes GIS a science instead of a tool. So I guess the title should be “GIScience for critical geographies”.

This article started by bring out two methods that are widely used in GIScience related researches: qualitative methods and quantitative methods. There is one sentence that I think is very interesting: “Geographers keep equating quantitative methods with advanced statistical and spatial analysis, and, therefore, scientific analysis and qualitative methods with ‘a mix of coffee room discourse, vendor sales hype, informal social interviews with one or two people, and an active imagination’”. Actually, this is very similar to what I think about these two methods as a geographer before reading this article. The part I exposed to GIScience are mostly quantitative, so I what I learned in my undergrad for GIScience techniques are very statistical and mathematical. This has made be quite confused for a while. But I think the authors’ idea that “the use of GIS requires a certain amount of specialized knowledge but this knowledge is different from the expertise in quantitative analysis” has solved my confusion.

So, I think there might be a blurry line between quantitative studies and GIScience, and the quantitative problem in GIScience researches all have a geographical context, which makes it special.

And then it is interesting that we are back to the question that whether GIS is a tool or a science. She has made several points in her article, and I thinks those ideas are very well illustrated and can be easily understood by people in the other fields.

This article about privacy issues in geospatial data gives me a broader idea of the surveillance issue in GIScience. Looking back at my past researches and projects, I have used a lot of data that have location information in it. Some of the information in the dataset are very well protected. As the literature have mentioned, people can protect some of the information by perturbation, aggregation, considering the level of privacy defined by user preferences, shortening the time collection period, and removing sensitive areas. However, not all data are processed by these steps. In one project, I have used some of the twitter data directly download from twitter. Those data reveals tweets with accurate coordinates together with time, username, and contents. So, each line of data has very detailed information in it, and it could be used for anything. So this makes me thing that do people still have privacy where big data are very prevalent recently.

The author also argues that this has a lot to do with users’ awareness of data privacy. I agree that most people will just skip reading privacy policy when they trying to register for websites or apps. Do this necessarily mean if we have more awareness towards data privacy, then we can gain more privacy?

I think in some cases, people do not have a choice to decide whether they want to share this kind if information. And, yes, I think as a researcher we should definitely consider privacy issue when we are dealing with sensitive data and follow the privacy checklists that the author provides.

In this paper, the authors describe the current states of the art of location privacy and formulate challenges. The first of the 21 theses in the manifesto on geoprivacy states that location privacy stands apart from information privacy. The reasons for this include the range of inferences that can be drawn from location, the ease of capturing individuals’ locations, and the incentives which draw users to share their locations with service providers. As a special form of information privacy, is it adequate to apply information privacy models and algorithms for location privacy protection? Additionally, different users tend to have various location privacy requirements. How to enhance the available information privacy techniques to protect location privacy?

What I am also interested in is the benefits of sharing locations. The authors mention that location privacy is intricately related to service quality. The service provider processes a request based on its understanding regarding customers’ location, and more precise location information leads to higher quality of the service delivered. Besides helping to improve service quality, sharing locations is being able to find people in emergencies. Therefore, I wonder if people would become more comfortable with sharing their locations when they feel the benefits outweigh the risks.

This paper by Marianna Pavlovskaya (2006) provides an insightful discussion of theoretical issues related to the distinction between quantitative and qualitative methods. The author does not insist that GIS is either quantitative or qualitative. Critically analyzing the construction of the opposition between quantitative and qualitative methods and the process of breaking the links between epistemologies and methods has occurred in the last decade, Pavlovskaya argues that GIS is not always as quantitative as many geographers assume and claims to an originally non-quantitative GIS enable.

This paper highlights the key role of critical GIS in drawing attention to the potential of incorporating qualitative data and research into spatial analysis. Geographers should notice the importance of doing GIS in critical contexts. For example, much research has examined bikeability, which is the bicycle-friendliness of urban environment, using objective and quantitative measures, such as distance and topography. The qualitative data like perception and emotions of the cyclists can be used to measure the comfort in relation to cycling and improve the experience of cyclists.

The author also mentions that a growing literature on ‘mixed-methods’ integrates quantitative and qualitative techniques. All methods have specific limitations as well as particular strengths, we should combine qualitative and quantitative methods to compensate for their mutual and overlapping weaknesses. For example, in travel behavior studies, while quantitative methods can be applied to measure the frequency and distributions of trips, qualitative approaches focus on the subjective experiences of individuals related to travel and explain the relations that quantitative methods find.

How long can the concept of privacy as we currently understand it last? The quote here, pulled from Duckham and Kulik’s 2006 paper, cuts strait to the point of the privacy debate in the modern era. Even a broad overview of the different conceptions of geoprivacy, as written in this paper, can never successfully address the cultural drive to change norms around privacy. This is best captured in this case by a footnote on page 3, which points towards historic examples of radically different conceptions of privacy. It’s clear that due to cloud computing, the internet, and globalized social media networks we are in the midst of a paradigm shift when it comes to how most people in the world conceive of the line between public and private. While it is clear there will be (and are) negative ramifications of this trend, as outlined in this paper, the steamroller of history is clearly trending towards a far less private world than has ever been seen before. This begs the especially interesting question of what will this change do to culture and society, particularly when geoinformation is considered. What does a country where everyone knows where everyone else is all the time look like? I don’t think it’s especially far off.

Crampton and Krygiers “Introduction to critical cartography” traces the historical roots of the current fixation on critical cartography. I found it to be a compelling read that does an excellent job of providing a description of the field. I especially liked the described purpose of critical cartography – “A critique is not a project of finding fault, but an examination of the assumptions of a field of knowledge. Its purpose is to understand and suggest alternatives to the categories of knowledge that we use. ”

The paper did however leave out the older roots of the concept of critical cartography. CC is framed as a response to the positivist, inflexible discipline of mapmaking that emerged in the early-to-mid 20th century. However, what preceded this era? Cartographic history goes back thousands of years, and the conception of what a map is often changes. I would argue, and I believe the authors would agree, that mapmaking from the age of exploration through the industrial revolution was hyper-aware of it’s own political and cultural biases. Maps were universally made as projects to further an imperial or other political entities goals, and often did not necessarily reflect the truth on the ground. This was an intentional decision by mapmakers who understood the purpose of maps to be something other than scientific.

The rise of science, in conjunction with the industrial revolution and the second wave of colonialism, fundamentally changed how many around the world perceived “truth.” What from this era directly led to the conceptualizations we see built into the movement towards positivist cartography found the century after? It’s clear than an entire book on the history of critical cartography could be written – and certainly has, given a short review of other available literature.

This paper proposes 21 theses that summarize the main arguments related to geoprivacy. It argues that geoprivacy has mainly be addressed isolatedly from the technological and ethical points of view. There is a lack of integrative research on technological, ethical, economical, legal, and educational aspects of geoprivacy.

The concern of geoprivacy has been discussed a lot in previous GIScience topics. The concerns are largely due to the increasing amount of location data shared with external parties. Such concern can be intensified with GeoAI increasingly applied to make inference at a larger scale. This makes geoprivacy an important topic to discuss from various perspectives as discussed in this paper.

Most of the time we are talking about how locational devices infringe upon our privacy, whereas this article brings up an interesting point of how location information can be used for the good. One of the theses argues that individuals have the incentive to share their location information with providers for better services. Another similar situation is the use of locational data for better surveillance in the cities. This brings up the question of how much we should care about geoprivacy vs. better service, and how much we should preserve an individua’s right to privacy vs. better public surveillance.

In the reading “Location Privacy and Location-Aware Computing,” the authors talk about the five principles of fair information practices, which are regulatory strategies to protect location privacy. The first is notice and transparency, making individuals aware of who’s collecting their data. However, I’m not convinced that this helps to protect location privacy. The public is becoming increasingly aware of how much data social media companies collect on our location, for example, and while there has been some outcry this hasn’t prevented such a location privacy breach. The second is consent and use limitation, making individuals consent to personal information being collected. As so many people check “Terms of Service” boxes when downloading apps without reading them, consenting to data being collected on them without realizing it, I also don’t think that consent is enough to protect location privacy- informed consent is. The third fair information practice is access and participation: individuals must be able to access stored personal data. While this is possible, most people are not aware that it is or how they could access their data, so just making such an action feasible doesn’t mean the public at large will practically be able to take advantage of it. The fourth is integrity and security, companies who collect data having to keep them safe from “unauthorized access.” As a number of data hacks over the years has shown, companies may attempt to do this but have not always been successful. Therefore, while all of these practices are nice in theory, they have not been particularly meaningful in practice. Until all individuals are aware of how much location data companies collect of them, give informed consent for such data collection, and have easy, reasonable access to such data, these practices will not practically protect the public at large from unfair or excessive location data collection.

This paper was an interesting read and a good introduction to critical cartography. However, I wonder if the democratization of cartography is quite as bottom-up now as the authors portray it to be in 2005. Nowadays, we have well-developed, public online mapping platforms like Google Maps and Open Street Maps, just to name a few. This makes me question how much the common person is interested in making their own map, when for the most part they have access to these free and relatively thorough platforms. Perhaps in places where the most popular online platforms aren’t well developed (for example, Port-aux-Prince before the earthquake in Haiti as Liz mentioned in her presentation), someone may be inclined to create their own map the way the authors describe. The same may be the case if a map exists but is not accurate. Otherwise, however, why would someone spend their time making a map if an accurate one already exists? In addition, if one were to make a map in this modern era of transition from Web 2.0 to Web 3.0, with the internet so populated with information and even institutions, could this process really be bottom-up? That’s to say, in a world with so much information from “higher authorities” like governments and private institutions, could individuals make maps in a vacuum, with no influence from such authorities? I would say they can’t. If individuals are pulling information or data from the Internet that come from a higher source, then the map they make using such data isn’t top-down. Perhaps back in 2005 the internet was still early enough in its development, and enough people weren’t using it, that bottom-up cartography was still a possibility. Now, however, the internet is a blessing and a curs that would prevent such a bottom-up process in mapmaking.

This article gives a thorough introduction to a very relevant problem: geoprivacy. We have spent so much time bringing privacy issues up in class as potential issues and strains of thought in many GIS techniques, such as geoAI or VGI. I am excited to learn more about this issue as it concerns my everyday life as someone who regularly shares geospatial data via social media.

What interested me the most was the section on the legal and ethical aspects of geoprivacy. It seems like such a slippery slope as different countries have different privacy definitions and that many privacy issues transcend country borders. 

I also have a few questions from the reading. How do researchers and others determine which data is just not private enough to be anonymized? Not sure if this question has an answer, but  is there anything that we can do now to protect our geospatial information, or is it too late? How can we protect the most vulnerable (people who do not realize their privacy is being compromised at all)?

In this paper, the authors classify sites related to the collection of VGI in order to study VGI quality and develop methods for analyzing VGI. VGI has altered how spatial data are created and the mechanisms for using and sharing these data. Because VGI is driven by contributors’ collective efforts, I am curious to know what motivates individuals to give freely of their time and expertise to develop VGI? What makes contributors stop contributing information to VGI projects? How do their motivations change as they engage in VGI activities? Will individuals map an area that has already been mapped in the last few years?

The authors point out concerns over the quality and trustworthiness of VGI. As we know, VGI has been used as an alternative to commercial or proprietary datasets. This makes me wonder about how can a VGI project, with no strict data specification or quality control, establish some type of trust. How to measure the reputation of a contributor to provide a better understanding of the quality and trust of the data? How to assess the quality of the contributions? Last, the authors mention that “VGI has the potential to address and constraints and omissions that plague SDIs”. Although VGI has concerns about data quality and scale and will not completely replace SDIs, I believe that VGI will become a key spatial data producer in SDIs.

This chapter identifies the possibilities of spatial knowledge extraction from unstructured text. Unstructured data does not necessarily require a more structured geography. But if these data are combined with other datasets that are geolocated, being able to geolocate these data might be useful. Translating text into geographic information is difficult. It is also a much more difficult proposition than simply assigning coordinates to photographs. The author introduces geoparsing, which is a process used to extract spatial data from texts. In addition to photos and videos, we can now geotag text messages, tweets, and more. But what about the data generated before the emergence of geoweb? Can we extract spatial information from old new articles? How can we add a spatial structure to data that do not already have it in order to mesh it with geoweb? Also, I am looking forward to knowing some useful tools for geoparsing.

Furthermore, this chapter doesn’t clarify what exactly the geoweb is. What are the boundaries between the web and geoweb? Last, many of the platforms that we rely on for geographic information are for-profit entities that do not have issues of justice and equity. However, it is important for us to note that how the geoweb encode, reify, and (re)produce inequality.

After reading this article, I found out that the geospatial web is much more than what I expected before. It turns out that geospatial web can not only be used in geography studies, but also can be used in other disciplines.

The article has mentioned that “Once geospatial context information becomes widely available, any point in space will be linked to a universe of commentary on its environmental, historical and cultural context, to related community events and activities and to personal stories and preferences”. So, I have a very interesting thoughts on this statement. Researches augmented reality are very popular in recent years. And I would say each world build in AR should also be in a certain geospatial context, so the things in that world also have some kind of location information. If it doesn’t have a location, the AR world would be a mess since everything will be floating around.

Obviously, the location information in AR world cannot be directly interpreted coordinates that exists in real world. But still, AR have some way to have all the things geolocated. And as mentioned in the author’s statement, it should be linked to a universe of commentary where the AR world can have some environmental, historical and cultural context. As a result, the AR world are very similar to the real world. So, the question would be can we have a geospatial web based on the AR world?

I would say yes, but I’m still curious about how can this works.

With the development of the Internet, volunteered geographic formation played a more a more important role in not only geographic information science, but also human geography, human geography, and geographic education. But I noticed that the author emphasizes explicitly about the importance of the volunteer part. The author thinks that in order to be referred to as VGI, the people who involve in this should know that that are doing it voluntarily but not passively. Then this leaves me a question, then where should we categorize the data that are generated passively?

Besides, the author also mentioned that no one can guarantee the data quality of VGI data. Then I think it would be a big problem especially when researchers are using the data to make some critical decisions. Data uncertainty problem are always important no matter in what discipline. The data quality of VGI data, however, are extra harder to evaluate because it is volunteered, and they are collected and analyzed by different groups of people with different background. So, my question is that is there any way that researchers can at least take the data uncertainty problem into consideration when they are using it. The characteristics of the VGI data made it even harder to use regular ways to evaluate the data quality.

Another point is the author mentioned that there is some connection between Geospatial web and VGI, but he didn’t explain it. I’m very curious that is there any examples or explanation of it.