Archive for September, 2017

Geospatial agents or AI agents? On Sieber and Sengupta, 2007

Saturday, September 30th, 2017

Sengupta and Sieber (2007) present an overview of geospatial agents and situate the concept within existing literature. The concept of an intelligent agent was completely new to me before reading this article. Despite the definitions provided, my lack of knowledge about AI made it difficult for me to grasp many of the concepts outlined in this paper.

This article provides the basis for geospatial agents as a distinct category of AI agents. After previous class discussions, I better understand the need for such an argument. By giving geospatial agents their own territory, distinct from that of AI agents, research agendas focusing on geospatial agents are legitimized and perhaps better funded. A review article like this, which works to define an emergent research area, is also incredibly beneficial as it allows researchers in the field to better situate their own work and draw from key bodies of literature. In this sense, working to define and contextualize a research domain can help drive further innovation in that domain.

Sengupta and Sieber outline two distinct types of geospatial agents: artificial life geospatial agents (ALGAs) and software geospatial agents (SGAs). As ALGAs are used in geosimulation to model movement in space, I understand the relevance of geography and spatial awareness. While SGAs are used to directly handle geospatial information, it is less clear to me how these types of agents are unique to geography. An SGA which has been programmed with information about spatial data models and geospatial issues may still not be intelligent about space itself. I believe that ALGAs are an example of a geospatial agent that is distinct from an AI agent, but I’m not convinced that the same can be said for SGAs.

Sengupta and Sieber – Geospatial agents

Saturday, September 30th, 2017

According to Woolridge and Jennings (1995), an artificial intelligent (AI) agent must be able to  (1) behave autonomously; (2) sense its environment and other agents; (3) act upon its environment; and (4) make rational decisions. For geospatial agents, this environment is (or is a subset of) ‘the earth’. Consequently, a geospatial agent may also have access to other geographic data, which it can compare to its own sensing data to make decisions.

In their paper, Sengupta and Sieber argue that GIScience provides a strong context for the study of spatially explicit AI agents and their expanding array of applications. GIScientists are well equipped not only to answer questions about the nature of AI agents in geographic space, but also, importantly, possess a rich toolkit to examine the “cultural and positivist assumptions” underlying AI. It is less clear for me however, why an AI agent lacking knowledge of its geolocation would be dysfunctional in a non-geographic environment. Would a UAV with limited storage/ processing resources navigating the corridors of an unknown building preference geospatial information over its own sensory data?

The Sungupta (forthcoming 2018) paper outlines a particular application of agent-based modelling (ABM) in movement ecology. Statistical and spectral analyses of location data revealed distinct patterns and trends in the monkey’s movements at different spatiotemporal scales, suggesting the existence of movement ‘rules’, which part-governed their behaviour. I did not fully understand when, and at what temporal granularity the observations were made (day or night?), or how many data points constituted a particular observation (one ‘observation’ every 15 mins for 1.5 years = 52560 point observations), which would affect the ‘stationary: movement’ ratio used in calculations. These types of model provide us with a powerful method to capture ‘characteristic’ behaviours and explore relationships between organic agents and their environment.

The animals for which the largest and most finely resolved geospatial datasets now exist are humans. As ABM models become more sophisticated and well-trained, to what extent will modellers be able to infer Nathan et al’s (2008) mechanistic components from an individual’s movement data? Controlling for their capacity for navigation/ movement, and external factors, how readily could their ‘internal state’ be estimated? Is movement-derived mood-based advertising on the horizon?

Automated Extraction of Movement Rationales for ABMs

Friday, September 29th, 2017

This essay presented an introduction to me for ABMs. Through the regular snapshot of a red colobus monkey’s positioning on GPS, both accounting for time and space, we can make soem strong empirical studies into the nature of movement for the monkeys. Up onto this point, most theories on movement whether they be animals or people were taken up on inference through observation of behavioral patterns. Now there is a significant presence of empirical data to back up these notions. Would this mean that zoologists tracking animals would be needing to pick up on GI Science soon? Perhaps. I understood that both quantitative and qualitative interpretations can be well married through the article.

One aspect that I found interesting was how the trackers were still working in tandem with other Arcmap layers, notably with DEM and land use mapping. Through this we can understand the constraining rules that surround the monkeys’ behavior. Hence, it sounds that with the right algorithm and inputs, it sounds like it would be possible to create adequate simulation models.

This feels as if it may have some repercussions with the advent of “big data”, and some issues concerning privacy arose while I was reading this. While it felt fine using this data on animals, and the amount of data available to measure their behavior was extolled by Sengupta, I wonder how this data carries on over to humans. Ubiquitous phone use is a real aspect of many people’s lives, and we are continuously producing data on a regular basis by the mere fact of having a phone on us. One thing that I wonder is how one would be able to access this data and who? Going by the same principle as the red colobus monkeys study, movement is subject to change largely by the change of external factors. This, I fear would mean that our assumed behaviors in ABMs may be recognized by public or private actors. One can take a cynical take on the presence of this data. This could lead to the advent of an exploitative social architecture that determines our movements in space time based on exploitative desires. This data may be potentially harmful and we ought to take note on how this is being used in the future.



Geospatial Agents, Agents Everywhere… Sengupta and Sieber (2007)

Thursday, September 28th, 2017

I thought this review was an interesting contrast to the discourse presented in the Wright et al. (1997) article on GIS as a tool or science. There seems to have been a transition from GIScience arguing for its own existence to asserting its domain over established concepts.

At first, I was a little skeptical of the unique “geospatial” designation for agents used in GIScience. I was easily persuaded of the commonalities between the properties of intelligent agents described in AI research and those applied in GIScience. Perhaps too easily persuaded. I struggled with how geospatial agents could be distinguished from other intelligent agents–particular those that don’t explicitly operate in geographic space. The element of geographic space is more evident in the case of artificial life geospatial agents, but at a glance, a software geospatial agent used to locate and retrieve spatial data from the Internet might resemble any other intelligent agent used to scrape non-spatial data. Of course, handling any spatial information requires some understanding of topology, scale, spatial data structures, etc. that is inherent to GIScience. In fact, I would imagine many intelligent agents implemented outside the domain of GIScience could benefit from the nuance that GIScience is able to offer.

I’m convinced! Geospatial agents most definitely necessitate their own designation. Again I’m reminded of the plight of the neogeographer. The article demonstrates a clear need for GIScience considerations in what are sometimes careless applications of geospatial information in technology.

On Sengupta et al. (forthcoming 2018), movement, and ABMs

Thursday, September 28th, 2017

I thought Sengupta et al.’s article, “Automated Extraction of Movement Rationales for Building Agent-Based Models: Example of a Red Colobus Monkey Group” (forthcoming 2018), was incredibly interesting. “Automated Extraction” discusses the use of agent-based modeling (ABM) strategies in simulating red colobus monkey groups’ movements “across space and time and predict[ing] environmental outcomes” (2). Utilizing the knowledge of experts as input, the modelling hopes to augment “the expert’s interpretation” (2).

At the conclusion of the article, Sengupta et al. note the possibility of ABM’s eventual replacement of scientists’ “heuristic knowledge” (11). It is exciting that ABM is continuing in the theme of original excitement behind GIS (helping us identify patterns that are not easily discernible quantitatively). However, it is also incredibly worrying, as it has the possibility of growing larger than zoological research purposes.

Sengupta et al.’s model relies on human monitoring of the model to check for errors, and the model requires more information from human experts’ field observations to become better at modelling. If AI were to be introduced to the model, and the model learns and understands the patterns better than human experts have observed or can observe, could we reach a point where nothing is unpredictable?

Continuing with the animal theme, this information could be used to predict, for example, where a group could be at a given time and then used on wildlife reserves to organize tours with high success of tourists seeing animals, or help researchers with short time-tables to most effectively study the animals. However, if poachers were to access (possibly) highly accurate modelling, they could more accurately predict the location(s) of groups of animals on the reserve and become more effective hunters of protected species.

For applications using human populations, ABM could be used for humanitarian purposes, like finding the most ideal evacuation routes (and edit existing routes or add new ones) for natural disasters, for example. However, if the model learns extremely well and everything becomes predictable, what would stop nefarious actors from using this information on human populations to catastrophic degrees?

Automated extraction of movement rationales for building ABMs: Sengupta et al. (2018)

Thursday, September 28th, 2017

I found both of these articles really fascinating, and found it helpful to understand the theories and differences between the ALGAs and SGAs presented in Sengupta and Sieber (2007), especially in analyzing the ABM presented in Sengupta et al. (2018).

Sengupta et al. (2018) use field-recorded data on Red Colobus monkey location and movements in space and time, combined with other GIS data (land cover type, slope) to automate ABM movement rules in an ALGA. Sengupta and Sieber (2007) suggest that ALGAs began with studying the flocking behaviours of animals and birds. To me, this suggests that the effects of a study on animals can have broad-reaching effects, beyond the study of “movement ecology” (2).

Sengupta et al. (2018) suggest that the advancement of high-resolution tracking technologies have created an ‘“enormous volume” (2) of data (i.e. big data). In this study, the authors refer to big data derived from GPS tags on animals, but couldn’t this easily be expanded to the movement-tracking (big data-creating) devices we carry around with us all day? Is there justification for concern given the necessarily reductive and therefore inherently wrong nature of models? Are our movements as easy to predict as a Red Colobus Monkeys’?

Though I tend to be a bit a doomsday-ist and cynic, in this case, I think that though models may try to track behaviours and predict movements, both humans and animals have one things the models don’t have: free will. Though the models can incorporate and automate complex decision-making models, I think that humans and monkeys and various other animals sometimes make irrational decisions that models cannot predict. In fact, I think that there is a huge potential for error in these models, which neither article addresses.

Public Participation on the Geospatial Web (2016)

Monday, September 25th, 2017

This article concludes that unitizing participation eventually hurts data quality.  Sieber also concludes that in many cases, VGI is an imperfect method for lack of traditional expertise. The cases examined in this article fall under the same umbrella of VGI applications for the public good, or specifically for narrowing the G2C relationship. The cases also all appear to require quite active participation in the form of content contribution.

I would argue that the four “avenues” discussed in the conclusion can be seen differently when examining PPGIS in the private sector. Many of the difficulties expressed in the articles vis-à-vis lowering barriers to participation are ameliorated in a private VGI effort. The private sector has more resources to develop friendlier GUIs. The issue of digital inequality would not be solved and participation by rural residents would likely still be stunted, however, passive participation such as location-sharing or simple multiple-choice prompts could see success in the form of quantity.

I think that additional research on the motivators behind citizen participation is a necessary step forward for this field of research. The article notes that PPGIS applications often maintain a facade of C2G proximity. If the desire for a louder voice in government supersedes that of “citizen science” or community-building, PPGIS projects should adapt and find a way to emphasize recognition and immediate response to citizen participation.

PPGIS: A Lit Review and Framework (Sieber, 2006)

Sunday, September 24th, 2017

In this paper, Sieber (2016) review the history of Public Participation Geographic Information System (PPGIS), explore four themes of it including place and people, technology and data, process, and outcome and evaluation. In my perspective, it is no doubt that PPGIS has been socially-constructed. However, there are some critical questions I think worth discussing.

Since PPGIS is contextualized, Sieber (2006) proposes a question about whether PPGIS can be generalized in certain degree. In my perspective, it depends what you regard PPGIS as. If it refers to approaches engage the public in application of GIS with certain goals, I would say it can be and should be generalized for sake of being learnt and adapted in different locations. Every approach or method needs adaptation when applied. The generalization helps understand an approach well, especially approaches that need to be applied in multi-disciplinary projects. While if you see PPGIS differently, such as a practical tool, I believe how to generalize it will be different. The significant problem is what is the nature of PPGIS. This also involves the question about how to define the public. For PPGIS, one of the goals is ensure the decision-making process more participatory. Consequently, I may question that whom we should include to claim the decision-making process is participatory enough. Surely, we can have multiple levels of public, while in a specific project, there must be a boundary exclude some people who may be relevant to the decision. Discussing such questions is the essential part when talking about PPGIS. Therefore, PPGIS, even as “GIS/2”, has been far more “socially-constructed” than its origins. Besides, it is a sad story that the public usually not engage with GIS directly, instead, they just provide inputs and evaluate outputs. The problem is whether this is enough to be called as “participation” since the public miss details when generating the decision. It increases the possibilities that vulnerable groups are manipulated by the whom with more power. I don’t think this can improve social justice. When the public provide inputs, there are problems about representing the knowledge; when they evaluate outputs, there are difficulties to match the empowerment goals and measure the intangible subjects.

As it can be seen, there are numerous problems in both theorizing and practicing the PPGIS. They stem from our society and may or may not be solved by more advanced technologies.

PPGIS Literature & Framework

Sunday, September 24th, 2017

The idea of PPGIS may appear relatively abstract when compared to the run-of-the-mill public participation (PP) process but at its core it is striving to accomplish the same thing. It is unbiasedly taking stakeholders into consideration for projects by giving them all the same information they would have in a regular PP process but with the addition of a simple (in most cases) geovisualization/spatial representation. This provides the stakeholder with perspective/insight that potentially could have been overlooked.

As noted in the article, PPGIS has grown to cover an extensive range of applications. As the technology changes and individual projects differ so does the PPGIS process. This left me with a more abstract understanding of these projects than I would have liked. It left me intrigued by the possibility of projects; what does a basic but useful geographic information system consist of that translates useful information from layman to the experts. The author includes brief and vague examples of interfaces that left me curious to find out more. Considering the purpose and nature of the article, this general coverage of case examples was definitely sufficient.

Throughout the article, the abstractness of the concept of PPGIS fades away; because it is highly interdisciplinary and has changed so much over time, attempting to define PPGIS is confusing. it was only later in the article that I began to fully understand what a PPGIS project really was/could be.

Regarding the age of the article (11 years (published in 2006)), I would be disappointed to find out that great strides had not been made in this field. The prevalence of natural user interface devices available now (e.g. iPad’s & smartphones) have effectively expanded the amount of potential participants for PPGIS projects. With proper software, intuitive and efficient PPGIS programs and systems could provide more comprehensive participation and ideally more successful projects.

PPGIS: Literature Review and Framework, Sieber (2006)

Sunday, September 24th, 2017

Sieber’s article establishes the historical context for PPGIS, and explores a framework for evaluation based on themes found throughout the PPGIS literature. It’s an interesting point that the term “participation” itself suggests the need for some intermediary. If PPGIS is to be viewed as a decision making tool, I would imagine that the typical role of the intermediary is to facilitate the relationship between stakeholders and decision makers, perhaps by way of technical GIS expertise. When stakeholders are empowered by a “bottom-up process,” or their own decision-making power or technical expertise, does a PPGIS framework still hold? Is the ambiguity a problematic feature of PPGIS, or is it that it should be differentiated from PPGIS in some way?


I was really struck by the discussion about public participation as a “ladder of increasing involvement and influence in public policymaking.” Admittedly–maybe unsurprisingly as an MSE student–I’ve always accepted the idea that ascending the ladder of stakeholder engagement is the ultimate goal. Evidently, I suppose it’s important to consider the ways in which community control are realized. In the era of the geospatial web, it’s conceivable that community control through PPGIS would likely require some technical ability on behalf of the community members, perhaps access to the internet or a personal computer. Of course, challenges to the framework arise if the ability to meet these requirements varies between individuals. It’s clear one of the most critical aspects of the public participation GIS framework is the consideration for differential ability to participate among the public.

Sieber et al. (2016) – Geoweb for PPGIS

Sunday, September 24th, 2017
Web-based geospatial tools (Geoweb) have opened up a wealth of opportunities for Public Participation GIS (PPGIS). With emphasis on usability and design, the Geoweb consists of platforms where everyday users can view, collect and share geospatial data. For governments, this provides potential new sites for interaction  with citizens. In this paper, Sieber and colleagues explore the wider implications of this “sophisticated and alluringly simple conduit for participation”.
Tying four years of empirical research and twelve individual PPGIS case studies, the authors examine claims about the transformative capacity of the geoweb. Can Geoweb bridge existing inequalities, and does it create new ones? How might Geoweb affect the relationship between a government and its citizens? Does it reorganise expert/ non-expert power structures, and if so, what are the consequences? And how does it change the nature of information that is being exchanged?
The results suggest that the answers to these questions can be highly variable and case-dependent. Furthermore, the use of Geoweb for PPGIS comes with its own set of problems. For instance, the substance of the information exchanged between organisers and volunteers might be reduced down to tallies of likes or page views, masking underlying complexity and heterogeneity.
I would argue that this reductionism exists in any interaction between government and citizens, where public opinion is condensed down to inform decision making (e.g. voting). However, proficiency/ access to Web 2.0 platforms changes who is able/ willing to contribute, and who’s voices will be dampened/ amplified – there are always winners and losers. It is important to identify who those might be, particularly when socio-political agendas are closely (but invisibly) interconnected with the technology.
Ultimately, this paper says we should be critical of Geoweb in PPGIS, which nonetheless offers strong potential for organisers, activists and governments to better serve their public.

Public Participation in the Geospatial Web

Sunday, September 24th, 2017

The way that neography is presented in this article sounds incredibly exciting. It presents itself as a radical counterpoint to the ubiquitous and predatorial cultivation of data from powerful private interests. The organizations discussed in this article all seemed to have altruistic measures with the reasons given for volunteer participation also reflecting that point of view. Volunteer participation stems from altruism, or pride of a place or open source convictions. In a large way this would reflect a kind of civic duty that I feel is still not ubiquitously recognized. I think of the digital divide discussed in the article, with different ontologies of the internet being in play.
I had the impression while reading this article that there these organizations had a poor level of communication with many of their volunteers. I think of the example of the blurring line of experts and nonexperts, and the anxieties contributors had of the validity of their own data. Perhaps these organizations are not properly reaching out and stating what kind of information they are looking for. This, I feel, stems from a lack of financial resources. This is often a problem when dealing with political action from a grassroots level.
Before the P/GIS becomes a truly disruptive force in the current world, it must become part of the regular social mores of as many people as possible. This would require a better level amount of education of it amongst the public, and it may even perhaps need to become a proper political force. I can imagine that on a municipal level, P/GIS may be an incredibly powerful tool for political mobilization and community knowledge.


Public Participation in the 21st Century: Now on a Map! (Sieber et al. 2016)

Sunday, September 24th, 2017

This paper’s truly interesting in that it addresses the philosophical questions of why people contribute anything, as well as the thought process that goes into contributions, and what makes them valid. I found that grounding of the geospatial web (a brand new topic) to its fundamental core, which is civic participation dating back to ancient Greece (Sieber 2007, p.1042) very needed. Along with reminding the reader that adding a map is a very aesthetic and fun way to contribute data, it still remains as just a GUI of sorts for the user to interact with a larger database. This increased interaction of user to web-architect does not necessarily equate to a reduced digital divide however, as was interestingly brought up with the rural participants of the FASNO project, who found Web 1.0 more comfortable than the Web 2.0. It’s sad to say the least that with technological advances, and increased access to the web that those left behind are now more behind than ever and are thus excluded (or feel excluded) from contributing in a new social group/setting.

It’s also useful to consider how ‘contributions are increasingly monetized’ (Sieber 2007, p.1034), as this plays a large hidden role into how the blurring of expert to non-expert occurs when we no longer know who is mapping. A large part of the time, it’s neither expert, nor non-expert, contributing to maps, though rather commercial entities. With this I mean how Google Maps differs from person to person based on ‘liked’/’saved’ areas, and sponsored markers. Though in the same sense of this article, this needs to be kept in the context that maps have always been made with an agenda, and you could argue that all maps lie to a certain degree to get their creator’s message across.

In short, I feel there should be more papers, or papers like this strip GIS and new forms of the neogeoweb past its GUI and fancy technological capabilities, to the fundamental data behind it, which is simple civic participation. Just this aspect being linked with the geospatial web is an incredibly powerful tool, though a better understanding of the user and to validate and quantify their contributions is definitely needed when moving forward with the discussion of P/PGIS.


Thoughts on ‘Doing Public Participation on the Geoweb) Sieber et al. 2016

Sunday, September 24th, 2017

In the case studies outlined in the paper, there were a broad variety of participants. From rural farmers to local governments to academic researchers, they encompassed people from different strata of society. This illustrates what was discussed earlier in the paper about how the geoweb has allowed for non-experts to engage with mapping and geospatial technologies.

There seem to be two different ways to do participatory GIS: to expand the geographical data available to us to manipulate (basic GIS) and the use of GIS to solve a specific problem or attain a pre-determined goal, such as to increase awareness, express identity or establish connections and document history (applied GIS). This observation harks back to the previous GIScience/Tool debate and lends support to the idea that GIS is a science because it is not only used for the latter purpose, and there are questions and problems related to the technology and methods of geographic information obtainment and manipulation themselves.

I found it interesting how the authors pointed out that a digital divide can exist within a community once some members have acquired skills and others have not. This presents a more nuanced picture than that of haves and have-nots, and combined with the observation of how the Geoweb creates “more rungs on the ladder”, shows how there is a gradient of participation and inclusion upon which people can fall. Rather than a binary perspective, it is necessary to see dynamics within participants as continuously changing and shifting with the balance of power and knowledge among government, citizen, academic, and under-represented individual.

Much is said today about disruptive technologies and how certain apps like Uber completely change the prevailing model of the industry which they infiltrate. One can consider PGIS to be disruptive in the sense that it picked apart the hegemony of crown copyright laws in the UK with the advent of open street maps. What unites these two is that in both cases, the disruptive capability comes from the adoption of the app or the PGIS portal/website/tool by the masses.

The example of Argoomap as a geo-referenced discussion engine made me think about how assigning explicit spatial characteristics to all aspects of our lives (thoughts, memories, songs, emotions) might influence the kinds of maps we create, especially with the advances in virtual and augmented reality. It was interesting to note that when volunteering geographic information, people tended to want the representation to be a map, although this may not always be the best way to visualize the information. I wonder if this is because of a cultural familiarity with maps and not due to their inherent superiority for the task at hand: if we were exposed to different methods earlier on, would we represent geographic information differently?

The tension between wanting more responses and wanting meaningful contributions is a difficult one to resolve with respect to PGIS and I think there is a fine balance to strike between making the lowest possible barriers to participation and still ensuring that people are contributing meaningfully.

– futureSpock

PPGIS: A literature review and framework

Saturday, September 23rd, 2017

In this article, Sieber traces a history of PPGIS, engages with the existing literature to create a framework for PPGIS. I found lots of the discussion very interesting, but what I found most interesting was the discussion on the accessibility of data. As PPGIS involves those affected by decision-making in the process, accessibility to data is crucial. I have to admit I have not ever contemplated the definition of ‘access’, though the various definitions show the nuances in the understanding of ‘access’.

While reading the four competing ethics of data availability, I was struck by how each of these positions, and politics, could drastically alter the process of PPGIS. I am also struck with how fluid the boundaries between these ethics can be, and I think that most countries would employ a combination of these approaches to data availability.

An open government would facilitate PPGIS, while any of the other positions would hinder PPGIS to varying degrees. While I mainly agree with the open government position in terms of spatial data, I also understand why personal privacy is important, and can in fact be crucial to a healthy society. Likewise, in terms of national security, it could be important to protect the location of secure facilities. I do have fundamental issues with the fiscal responsibility position, and see this as the biggest hurdle to effective PPGIS (good old capitalism…). Putting a price on public data invariably grants access to resource rich organizations, solidifying a top-down framework of PPGIS. This touches on the notion of the inherent inequality in PPGIS, a subject that I think Sieber does a good job addressing throughout the article.

Thoughts on a literature review of PPGIS (Sieber 2006)

Friday, September 22nd, 2017

Sieber’s literature review and framework for public participatory GIS (PPGIS) effectively situates PPGIS within existing bodies of thought in GISciences, and highlights relevant critiques and considerations. This article discusses ways that local knowledge can be integrated into GIS frameworks to democratize the technology and use it as a tool for empowerment and social change.
This article challenged my existing notions of what it really means to undertake “participatory” research methods. Sieber’s critique of the “PPGIS as GIS” approach was particularly interesting to me as she notes that public participation may often need to go deeper than simply extracting input from communities. Despite solicitations for public input, participatory research may still be top-down and impose the agenda of the researcher.
In reading this article, I was often reminded of what I have learned about “qualitative GIS”, which attempts to capture subjective forms of spatial knowledge in a GIS framework. Both qualitative and public participatory GIS respond to the technocratic social critiques of GIS and attempt to employ the technology in a more bottom-up process. I would be curious to investigate how these two domains intersect and are distinct from each other.
The key theme that I took away from this article was the highly context-based nature of PPGIS. Sieber asks whether or not the presence of such contextual factors leave us unable to generalize PPGIS. This question is a very important one and stayed in my thoughts as I read through the rest of the article. To effectively engage and empower a given community through PPGIS, a researcher must consider factors such as how this community communicates knowledge, the community’s level of technological literacy, and how the local knowledge can best be integrated into a GIS to meet the goals of the project. How can a set of best practices for PPGIS be established if what it means to “do” PPGIS changes with each project or initiative?
– janejacobs

Thoughts on Sieber et al. (2016) & the future of PPGIS

Friday, September 22nd, 2017

Sieber et al. (2016)’s discussion of Doing Public Participation on the Geospatial Web raises issue with accepting the standard GIS uses in governments as forms of public participation. While this public use seems benign and helpful at first glance, their analysis shows that it is not always this way, and the government-public relationship has remained fairly unchanged by the advent of the public use of the Geoweb.

The field of PPGIS will be particularly interesting as the “digital generation”, or those who have grown up or started from an early age in using the Internet or other virtual devices, ages. As more of this generation reaches voting age (usually when one becomes politically active/conscious) the ways in which government interacts with citizens will change irreversibly, and perhaps the demarcation between government and citizen will blur or mutate as well (as Sieber et al. denoted has only slightly occurred so far).

In addition, the aging of this “digital generation” may eliminate the digital inequality brought on by technological advances. I hesitate to say that it will eliminate this specific inequality, as the “broadening of access” excitedly brought on by technology clearly has not lessened the divides between urban-rural/socioeconomic/age, as Sieber et al. noted, but also between (dis)abilities, in accessing resources virtually. And will web-based tech ever lessen the divides?

Without intervention, lower-income communities or geographically isolated communities may not have access to the web due to lack of financial resources, lack of device availability (to buy or to rent), lack of a platform to connect to, or other such concerns. In addition, technology will always evolve and it will always be “new”, regardless of which platforms or tech or equipment on which the older generation grew up, and the older generation may continue to not have access to teachers or they may not care to learn how to use/benefit from new technologies. Finally, text-to-speech technologies have made advances in connecting sight/audio impaired communities to the Internet, but there remains a lack of access for those with motor skills impairments, for example, which hopefully will be solved with advancements in science. With these persisting issues with web connectivity, public participation through the Geoweb cannot be taken at face value and must be studied more thoroughly through an equity lens.

Thoughts on Goodchild (2010)

Monday, September 18th, 2017

Goodchild concludes his paper “Twenty Years of Progress” by realizing a need for greater interaction between the fields of geography, computer science, and information science in the future of GIScience. Seven years ago, when this paper was written, neogeography was an emerging concept. RFID and GPS location collection operations were still relatively small scale. Goodchild notes the benefits of having such large real-time datasets, as well as the implications such data would have on personal privacy. I’m not sure if Goodchild could have predicted the roles that the private sector would have in advancing location-based technology.

Many datasets that have been collected by tech companies are invaluable to actors in the public sector and academia. Google and Uber data would surely benefit transportation planners, and Instagram geospatial data might be of use to a board of tourism. Goodchild asks the right questions about the future of real-time location data, but today might ask more questions specific to the privatization of such datasets. Are the developers of location-based applications members of the GIScience community? Do they recognize the significance of the geospatial data they are collecting? Or do they seek to make a profit over the advancement of science?

I would argue that in 2017 the actors on the stage of GIScience include much more geographers, computer scientists, and information scientists. Goodchild correctly predicts that the average citizen will become “both a consumer and producer of geographic information,” but fails to mention the elephants, the private tech companies that provide VGI-fed services to the newest generation of smartphone owners. App developers are as much a part of GIScience as the transportation planners that install sensors to measure traffic flow, and the computer scientists that use agent-based modeling to optimize emergency services in the event of a terrorist attack. I hope that academic GIScientists such as Goodchild are changing the way they see GIScience to bridge the gap between private collectors of geospatial data.

On Kuhn’s (2012) Core concepts of spatial information for transdisciplinary research

Monday, September 18th, 2017

Similarly to Mark’s (2003) paper, Kuhn advocates for a conceptual consensus on spatial information – what it is and how it can be used – by proposing a set of ten core concepts of the field intended for specialists and non-specialists alike. Kuhn also argues along the same line as Mark in that GIScience transcends the boundaries of a single discipline. Spatial information is what bridges separate fields, it integrates multiple scientific disciplines and ties them with other stakeholders in social policy making. Given its essential role, a consensus amongst experts of what spatial information actually is is needed to then open the field to non-specialists and be conducive for transdisciplinary research.

One of the main challenges Kuhn briefly mentions is the need to “map the concepts across disciplines.” Concepts are human constructs and vary from one discipline to another, in what they mean, what they are used for, or how they are used. Especially in trandisciplinary research, these concept variations can become very confusing and inhibit successful collaboration. For a paper that is intended to be intelligible to non-specialists from various disciplines with different backgrounds, I find that Kuhn offers a somewhat narrow-minded definition of each concept – that is, from the perspective of the GIScience field –without necessarily acknowledging any possible disparity with other disciplines’ understanding of the concept. While I do agree that building a foundational ontology of spatial information drawn and complemented from existing ones from other disciplines could offer conceptual clarity, I believe this paper needs more practical elaborations on each concept and less abstract conceptual definitions to be understood by non-specialists.


GIS: Tool or Science?

Monday, September 18th, 2017

The debate surrounding the use of GIS as either a tool or a science did not occur to me while I was taking introductory courses in the field. I simply understood it as being a subset of geography, distinct in its own right as it compelled the visualization of geographic data for the maps. While reading through this article I was struck by the complexity and rigour this debate engendered. One thing that was evident to me was its place in history. The article was published in 1997 and used data extracted from early messaging boards shared between people who did GIS in their respective universities. I am unsure of how developed GIS was at the time, but I imagine that it was much more rudimentary than the way I was introduced to it. I mention this as I recall Wright et al’s positioning of GIS as a science, injecting that in order to be considered a science it would need to be in a position in which it drives technology. We are in a position today in which the demand for GIS knowledge is in high demand due to the sheer immensity of GIS data being produced and consumed on a daily basis. As it is advertised as a skill or a tool, as I would imagine many of those trained in it consider it, it would lack the same sort of scientific rigour that other disciplines will have. While scientists and psychologists are subject to a code of conduct with their disciplines, I imagine that there are many people using GIS who do not acknowledge the power that the technology may have on the wellbeing of people. As we look back embarrassingly on the racist and colonialist legacies of other academic disciplines, perhaps one day we will look back on the mismanagement of GIS data in a similar light. Perhaps by establishing GIS as a science, an broader understanding of its ethical implications may unfold.