Archive for September, 2014

The Emergence of Spatial Cyberinfrastructure

Monday, September 29th, 2014

In the Wright and Wang article (2011), the advent of cyberinfrastructure (CI) is explained as a “paradigm shift in scientific research that has facilitated collaboration across distance and disciplines, thus enabling quick and efficient scientific breakthroughs” (1). This contribution to science seems astounding, yet the article doesn’t clearly explain what it is or how it works. Nevertheless, for students in 2014, it is hard to imagine a time when sharing data and collaborating couldn’t be done with the click of a button.

One of the uses of geospatial CI (GCI) given in the article is for an optimized sampling scheme for research in the Antarctic, which trumped the traditional method of sampling a parameter around each station. This sounds like great progress, but the article does not elucidate the logic behind the scheme and how the GCI runs the operation.

An interesting facet of GCI is that it allows us to redefine spatial modeling, to include both physical and virtual spaces. This adds a huge dimension to geography: spatial notions and theories can be applied to networks and “spaces” that aren’t tangeable. Whilst this allows a broadening of horizons, there is one caveat: an understanding of the concept of space is necessary for the GCI to work.


The future of GCI – more acronyms!

Monday, September 29th, 2014

Yang et al. (2010) Geospatial Cyberinfrastructure: Past, present and future

Yang et al. (2010) describe how the complex conglomeration of resources, networks, platforms, and services that is cyberinfrastructure (CI) is combined with geospatial information and principles to form the geospatial cyberinfrastructure (GCI). The authors conduct a review of the current GCI research, development, and teachings to determine the status of GCI. Subsequently they go on to predict how CGI will transform the geospatial sciences and other fields.

The GCI objectives put forward by this paper are certainly hopeful in what they seek to achieve, but they may in fact be quixotic. The authors are likely correct that advancements in technology will transform the GCI, especially in the realm of data sharing and increasing volume of geospatial data, however, Yang et al. do not consider the role of social obstacles. The sharing of data is not as simple as handing over it over to someone. The lack of standards and consensus surrounding standards impedes the interoperability of data between users. Defining standards may be likened to finding a common ontology within GIScience – it is subject to debate and differences between public and private usage. Licensing is another can of worms, as rights of ownership vary greatly between states around the world. Calls for open data have initiated the data standardization discussions although it is unlikely that major adoption will occur in the near future.

This article suffered from a lack of readability. A puzzling number of acronyms standing in the place of a myriad of neologisms made this article awfully confusing. I assume the intended audience of this article is academic researchers that are familiar with the technical jargon of GCI. For a newcomer to cyberinfrastructure this article makes the topic seem hopelessly esoteric.



Envisioning CyberInfrastructures

Monday, September 29th, 2014

“The emergence of spatial cyber infrastructure” by Wright and Wang explores how cyberinfrastructures (spatial or otherwise) has contributed to the advancement of scientific enquiries.

After reading this article, I still can’t imagine what a cyberinfrastructure would look like. Is it just a really big database?

Reading the article made me wonder what characteristics make a CI good and effective, and how design of the CI shapes what can be done with the data it stores?
In the beginning of the semester, we discussed how different understandings or definition of a given ‘thing’ affects how store information about it. We talked about how a hydrologist would define a river vs how the Cree community sees a river (which would include the bank as well as the flowing water (if I remember correctly)). How would you account for this difference in a CI?

CIs have been essential to collaborative research, however more work is needed to understand how the conceptual and cultural assumptions a CI embeds affects (or not) research.


Spatial Cyberinfrastructure

Monday, September 29th, 2014

Wright and Wang’s article, The emergence of spatial cyberinfrastructure, discusses the basic components of Cyberinfrastructure and provides an overview of spatial cyberinfrastructure specifically. This was my first introduction to cyberinfrastructure, especially of the spatial variety (S.C.I.). After reading the article, it became clear to me the power that S.C.I. has and the benefit it can provide to the study of G.I.S. and other geographic fields of interest.

One part I found interesting was how S.C.I. could enable very large sets of spatial data to be efficiently and quickly processed and analyzed. It reminds me of a section of a book I recently read (Halo: Ghosts of Onyx by Eric Nylund), where a spaceship can circle a planet and have a complete spectroscopic analysis of the surface within minutes, all without the need for human involvement (a process those who took/are taking Geog 308 know would take many months of labour). While currently solely in the realm of science fiction, advances in S.C.I. would hopefully one day make that feasible.

Another fascinating idea the authors touched upon was how S.C.I. would facilitate collaboration among scientists, and especially between traditional scientist and citizen scientists. Given that geography is a multidisciplinary field of study, this co-operation is critical for the advancement of geographic thought as a whole, and especially G.I.Science. More advanced S.C.I. could increase the usefulness of citizen science by providing better platforms for such science to occur, or by expediting the analysis of large quantities of spatial data provided by citizen scientists (i.e. location tagging on Twitter).


The Social Cl

Monday, September 29th, 2014

This week’s article “The emergence of spatial cyberinfrastructure” by Wright and Wang basically goes over what cyber infrastructure is, the types, and its applications. While most of the article is just listing different ways to use computers for science and research (this is an oversimplification of course, but when it boils down to it that’s essentially what the article is) it does manage to bring up some points that got me pondering. The first were of course, ‘Man, there are really endless ways to use GIS and computers in scientific research’ and ‘Computers really do help in the advancement of knowledge, especially when it comes to massive datasets and calculations’. On a separate note, the ‘social endeavour’ aspect of CI piqued my interest. It’s weirdly fantastic in the way that sharing data for collaboration is now as simple as putting it up into a ‘cloud’ (still a mind-boggling concept to me – consider the iCloud breach) and that data can be commonly shared due to removing common international collaboration roadblocks like “multilingual, biographical, and temporal ambiguities in the data”. Finally, there was the aspect of ‘the small independent investigator’ is the driving force behind innovation in the scientific research capacity and that a small research project can now blossom into something even larger and more impactful (i.e. as large as group science) which I thought was a pretty awesome perk of using technology. My only qualm about this article is that not a whole lot of discussion was done, it was more of a quick list of ways to use CI – which is okay given that it was only four pages, however I would have preferred to hear a little bit more about each application and how CI helped them.

Until next time,


Generally Confusing Infrastructure

Monday, September 29th, 2014

I have long been more than just a little confused as to what Cyberinfrastructure exactly is and my confusion can be adequately embodied by my response to the figure shown in this article titled “GCI Framework Cube” – a lot of words not not a lot of understanding to match on my end. Despite my initial reluctance to engage with GCI this article brought to light the vast importance of the subject to the field of GISCience.

We live in a complex world, one that is also incredibly data-rich. Advancements in computers, network technology and electronics has made access and sharing of information rapid in comparison to previous generations. With stronger geospatial cyberinfrastructure (GCI), geospatial science research will flourish. Yang et al., identify multiple examples of how advancing technology in storing, integrating and utilizing large sums of georeferenced data have benefited different studies, all this while at the same time identifying the need for further advancement.

Upon reading the article I felt the authors did not succeed in introducing clearly and simply GCI to the group identified in their introduction. For most of the article I was buried under layers of jargon, left to fend for myself with general concepts and ideas. The section on enabling technologies provided the most clarity to my confusion. The article enhanced the base knowledge I had but still left me with many questions on a subject so vast. Perhaps if I saw GIS as less of a tool, these concepts would have come easier. It feels all too fluffy and intangible to me. High performance computing, earth observation, open access technology were among the technologies I would have previously attributed to GCI but newer concepts and ideas have been added to this collection through the article – and I will seek out understanding this subject at a deeper level over time.

– Othello


CI and the endless possibilities

Monday, September 29th, 2014

This article was quite informative and did a great job in demonstrating the importance of C.I. Based on the reading, C.I. seems to be a revolution in computational capabilities. The article demonstrates that the advent of C.I. has advanced science so much that computation could arguably be considered one of the three major “pillars” of science. Being relatively new to the field, C.I. and its role was not something that I ever truly gave too much thought. However, this article has been eye-opening in advocating for its role in today’s science. What seems so appealing about is its multidisciplinary capabilities.
Before C.I. the problems in data analysis left many questions unanswered. Now with its availability, it allows for much more complex questions to be asked, with a way to find these answers. C.I. has changed the way that data can be handled, shared, and analyzed. The question I ask is to what limit does C.I. have? It seems like it has the potential to continue to change how science can be done, across all disciplines. Is there a weak link that has yet to be found, or is this the real deal that will continue to benefit scientists for years to come? I suppose only time will tell, much like the authors assert in closing. For now however, C.I. appears to be building a solid relationship with science and the way science is done.


Geospatial Cyberinfrastructure: Past, Present and Future

Sunday, September 28th, 2014

In Yang et al’s article, the authors briefly, yet with enough detail, explains the origin of “Geospatial Cyberinfrastructure” (GCI), various technologies that contributes to its birth and current uses of it.

From this article, GCI is referred as an infrastructure that can support the collection, management and utilization of geospatial data, information and knowledge for multiple science domains based on recent advancements in geographic information, science, information technology, etc.

As a newbie who just started to explore the world of GIS, it was a surprise to learn about an existence of GCI that encompass even the Geographic Information Science, because I found that the concept of GIScience itself was already quite vast when I first learn about it from this course just a couple of weeks ago.

Putting aside my own impressed feelings, as I was reading further in the article, I found it very informative overall and liked the ‘discussion & future strategies’ where the authors even assessed the future studies required for the GCI to improve further. On the other hand, at some point of the reading, it seems like the authors seem to overly emphasize the importance of developing GCI, but I guess that was the whole point of this article anyway.


GiScience and primates

Monday, September 22nd, 2014

Advancements in GIScience and associated technologies have enabled researchers to ask more original and complex questions. In “Emergent Group Level Navigation: An Agent-Based Evaluation of Movement Patterns in a Folivorous Primate”, the researchers use agents to simulate the foraging behaviour of red colobus monkeys. The intersection of GIS with other disciplines not only highlights its role as a tool, but also advances the discipline of GIScience. It encourages the development of questions/problems that are unique to GIS, such as: How do you model topologies and proximity, while being mindful of issues of scale?
While models often don’t fully capture the complexity of reality, the development of agents to represent different hypotheses of primate foraging behavior deepens, presents an exciting way to test the validity of various theories.
More generally, artificial life geospatial agents allow us to better characterize interactions among people and their environments. The predictive nature of simulations provides many opportunities to improve scientific understanding (e.g of primate foraging behaviour) and design efficiency (e.g modeling people response during natural disasters to better plan for evacuations/emergency response). But can’t the modeling human behaviours also be used as a tool for tacit control?
When it comes to the developments of agents, are there any ethical considerations; and if so, what are they?
The growth of GIScience allows use to do incredibly interesting and innovative things, pushing the envelop of research in a variety of disciplines; but has the discussion around the social and ethical implications of GIScience kept paste with the development of the field?


Is GIS monkey business?

Monday, September 22nd, 2014

Bonnell et al (2013) reports the modeling of the movement of the red colobus monkey in Uganda using the following factors: memory type (Euclidian or landmark based), memory retention and social rule. The use of GIScience in this project is novel and exciting: it shows the importance and the magnitude of the field. Most subjects have a spatial component, for which GIScience could be used.

However, I had a few questions about the research project and the ensuing article. Why were the monkeys only observed from 8AM to 1PM? Are they inactive in the afternoon? If there were a logical explanation for choosing this time slot, it would have been worthwhile to include it in the article. If not, it seems plausible that monkeys might act differently in the afternoon and that finding out if they do would be useful for the research. It would also have been interesting to add less predictable factors to the model, such as weather, natural disasters, human activity, etc.

Moreover, I’ve always felt it was impossible to prove or disprove theories on animals, as we will never know what they are thinking, and why. Would it be possible to use this kind on model on humans? I agree with Othello that by modeling human behaviour, it would be possible to get the subject’s opinion on the research’s findings.  It would be interesting to model the movements of students on a university campus, or in places where people act most like primates: bars.

Cheers, IMC



Agents Agents Agents

Monday, September 22nd, 2014

This article review other articles and provide a brief definition on terms that are quite difficult to find, even in Google, such as ‘Artificial Life Geospatial Agents’ (ALGA) representing a computer model that may be independent programming code interacting with other code or a single piece of software itself that use computational models to imitate  an individual’s behavioral responses to an external stimuli. It is a crucial tool to model interactions and behaviors between humans, animals and the natural environment.


Unlike ALGA, ‘Software Geospatial Agents’(SGA) is used to manage information and making decisions in hardware and software environment, and it is designed to manage geographically explicit information, such as a geographic coordinate, on behalf of an entity, which can be a person, a software or even hardware.


These agents share couple of common points. For instance, they are both a predominant type of agents in GIScience and they both perceive and respond rationally to new situations to new situations and their environment In addition, they are enable to handle the unique qualities of geospatial data as well.

This article demonstrates further explanations and examples to demonstrate the minimum requirements for a piece of software code to be considered as an “agent” in the AI literature and then, the authors question the existence a Geospatial Agent and underline its importance to both ALGA and SGA. They argue that as much as AI requires spatial information, without it, AI is likely to fail. It sounded quite convincing and all until they mentioned how geographic coordinates as a part of IP specifications could benefit the SGA and Internet community…my skeptical ego just woke up and oh well…Nonetheless of my regard in that specific example, this article in overall did a good job in reviewing other agents-related articles and explaining the roles and definitions of the intelligent agents and of course underlined the uniqueness and importance of geospatial agents that are playing and will be playing in the future by handling geospatial data, which makes it so unique and valuable.

It required me to re-re-re-read this article over and over because the terminology and concept was very unfamiliar and uneasy for me, but it was still quite interesting and always good to learn new terminologies…sometimes… 😛


Oh It Used To Be So Simple

Monday, September 22nd, 2014

This article made me think. For one, it was a slow read – no details were spared in the complicated explanation of the science behind the research. As an Arts major, I was seriously intimidated and I’m still not sure I grasp the methodology behind the findings. Secondly (and more importantly), it made me consider applications of GIS outside of mapping. I know, I know, it’s like every single week my mind is being blown by how vast the field of GIScience is – but it’s the truth. Looking at the behavioural responses of primates (in the research, they are using simulated primates) to stimuli was pretty cool if I do say so myself. Looking at where they go, how they go, and who they go with to get resources was something I had never considered as being applicable to GIS. I’m still getting over the fact that psychology/memory is a factor in mapping now (I’m referencing to the ‘social rules’ and how they impact the travel patterns of a group). Its starting to make me think that there are pretty much endless applications of this tool (or science – I am still waiting to be persuaded). For instance, why can’t we use GIS to save those little polar bears I mentioned last week? We could look at behavioural patterns and add it to any spatial data that we already have. Then, look at the response to stimuli, such as the glaciers and sea ice being obliterated by global warming. Of course I’m over simplifying but you get the point. GIS is essentially engulfing every field that I thought was mutually exclusive from it and I’m not sure how I like it.

Until next time,


Agent Based Modeling & Monkeys

Monday, September 22nd, 2014

Bonnell et al.’s research paper deals with agent based modeling in relation to the feeding and movement patterns of Red Colobus monkeys. They tested for the effects of memory type, memory retention and social order within the group on their movement patterns. From a G.I.Science perspective, this article is interesting due to the fact that the authors used agent based modeling in order to get a better understanding of monkey behavior. By doing research such as this, they help to further expand the field of G.I.Science through the novel use of agent based modeling methods. Further development of A.B.M. (and specifically geospatial agents) could include such things as developing better models that provide more flexibility for individual agent choice, with obvious benefits to the field of G.I.Science.

What I found interesting was the potential that existed for visualizing the geographic data that was produced through the agent-based evaluation of the monkeys. Given that geography is inherently spatial, being able to visualize complex data (such as monkey movement patterns) would enable a better understanding of the processes at work. This visualization could also help with introducing A.B.M. to a wider audience and therefore help expand public participation of G.I.Science.

Tying this article in with the “Geospatial Agents, Agents Everywhere…” article, it is clear that the authors used Artificial Life Geospatial Units as the agents which they based the Red Colobus monkeys off of. It is also evident that the agents used in the study were geospatial in nature, not merely A.I. agents.


Spatial Memory and Societies

Monday, September 22nd, 2014

Bonnell et al. (2013) Emergent Group Level Navigation: An Agent-Based Evaluation of Movement Patterns in a Folivorous Primate

In an intriguing compilation of GIS, ecology, and primatology, Bonnell et al. (2013) seek to model the complex foraging behaviour of the red colobus monkey in order to uncover patterns of spatial memory. The agent-based modeling used in this study exemplifies one of the cutting edge applications of GIS technologies ­– predictive science.

This is my first academic encounter with spatial memory but the concept encompasses something that I have often thought about i.e. how people (and animals) navigate the world around them. In this article, social rules were the primary factor in determining step length – different societies behaved differently. It would be interesting to research how spatial memory in human societies differs between age groups, cultures, urban-rural settings, etc. as I suspect that they may differ greatly. It also makes me wonder how GIS technologies such as Google Maps have altered spatial memory in humans.

There were a few omissions made in this study, although I suspect these were due to the issue of complexity. Firstly, by limiting the foraging simulations to six months the researchers neglected the seasonal variability of resources. Developing this component of modeling could identify how animal movements and feeding habits change throughout the year. Secondly, it would be interesting to add the component of competition into the simulation to account for rival groups, interspecies relationships, and human activity. Thirdly, as colobus monkeys are a tree-dwelling species, it would be interesting to see if the addition of a z-axis would affect the results of the simulation (e.g. would movement more closely resemble Euclidean memory, would this affect group safety). Keep in mind that these recommendations come from someone without a background in computer modeling, primate behavioural studies, or ecology, so I am uncertain as to what extent any of the abovementioned components could be added to the simulation or if they would in fact enhance the study in any measurable way.



The endless potential of modelling

Monday, September 22nd, 2014

This is quite an interesting article, as the authors attempted to simulate a system involving the behaviour of primates and the struggle for both food and safety, both of which work against each other. The model was complex and involved many variables and considerations. I appreciated the complexity of the model as I recently constructed a model involving the Green Monkey in Barbados. As an invasive specie, the goal was to find a reasonable technique to stabilize the population explosion before the system and the resources on the island reached the carrying capacity. What I appreciated about this article is that the authors go a step further and manage to display their primate model spatially, something that would have greatly improved the accuracy and interest of my model.

This type of model is fascinating, as so much of the general public would be interested to know how something like this works. This is something that you could see on the Discovery Channel, or National Geographic and would easily attract viewers. People are interested in science and animals and they love to see scientists study them. Thus is a great way to introduce such technology to the general public, and perhaps influence people to take an interest in GIScience.

As mentioned in the article, there is so much potential with GIScience and its ever expanding capabilities. Using GIScience and coupling it with a model similar to what was constructed in the article, a better understanding of animal behavior and movement could be established in the scientific community. It could potentially be used to allow humans to better understand and avoid human-animal interaction, eliminating many problems. GIScience is proving more and more to be an incredibly valuable discipline, and the possibilities of application appear limitless.

Paging Agent Monkey

Sunday, September 21st, 2014

Applications of GIScience are widespread, this is in part due to the fact that every event or process, involving objects or beings has a spatial element in the storyline. Emergent Group Level Navigation: An Agent Based Evaluation of Movement Patterns in a Folivorous Primate (Bonnell et al., 2013) uses GIS to model the movements of primates will the goal of gaining a better understanding of their movement strategy as they forage for food. This is achieved by comparing 12 combinations of collective behaviour against observed moments tracked in the field. Therein demonstrating the power of GIS to not only represent reality, but also simulate it – and in this case bringing the two together.

While an innovative use of technology, I feel there is much more work to be done to further such research. As all models can be defined as ‘a [mere] substitute for a real system’ I’d be cautious in criticizing the small pool of strategy hypothesis presented as too simplistic. I applaud the researchers’ audacious attempt to model such a complex system, living creatures are wildly unpredictable. I would argue that modeling human movements and interactions would offer more insight as most of us carry tracking devices (smart phones) and so many of our transactions feeding or otherwise can be tracked electronically and spatially. The added benefit would be in that one could supplement the research by interviewing a sample of those tracked – we can’t quite talk to monkeys just yet.

I ask: “Why we need to understand monkey movements?” The paper does however point to how such a comprehension sheds light on the cognitive functions of the observed agents, telling us much about how their memory works. This alone leaves this project as one of the most creative uses of GIS. 10/10!

– Othello

On “Emergent Group Level Navigation: An Agent-Based Evaluation of Movement Patterns in a Folivorous Primate” (Bonnell et al. 2013)

Saturday, September 20th, 2014

The authors modeled the decision-making process in foraging of red colobus monkeys in Kibale National Park, Uganda, and then tested it against their observed data to test the effect of spatial memory type (Euclidean or landmark-based), memory retention (low, medium, or high), and social group type (democratic/independent or leader) on the patterns of movement of the primate groups, and see which model fit the colobus monkeys best. Several environmental, group behavioral, and primate capabilities variables were taken into account. The authors seemed to have thought about everything. A fascinating part of the model was that the authors simulated that grouping in primates increased safety in individuals by mitigating predation, but also increased food competition. The monkeys in the model even had a knowledge of “grow back rate”: the rate at which vegetation in their feeding sites grow back after they have left them.

Although predation was included indirectly (by modeling that grouping in primates increased safety by mitigating predation), I wonder why predation was not included directly in the model. It seems that predation is a crucial factor to consider in modeling the displacement of monkeys and testing the effect of  spatial memory type, memory retention, and social group type. Maybe the colobus monkeys remembered that there was predation in a feeding area, and this could have affected the patterns of movement, type, or size of the group. Another factor that could have been modeled, although brought up towards the end of the article, is group demographics. It was found that the leader-led group with a landmark-based memory and low memory retention best fit the observed red colobus monkey data. However, a group that is composed of an older population might function with a democratic (independent) social group type, while a group composed of an younger population might function with a leader-led social group type. In view of that, it would be an interesting experiment to include demographics in the model.


– Solfar


Public Participation related issue

Monday, September 15th, 2014

This article is based on several years of studies and multiple research project that examined through the social change, capacity of PGeoweb to support citizen science, participating in decision-making, etc. This project was conducted my numerous researchers and yet the paper seems to be very biased towards the pro-Geoweb only. Since the very first time I have learned about the VGI, I have always wondered about the issue of accuracy and standard related issue and when I started to read this paper, I kind of hoped that some sort of solution or any suggestion concerning those issues would be mentioned, but it did not.. In addition, when a public participation and/or crowdsourcing issues are concerned, whether web based or not, there used to be always some kind of manipulation issues that arise as well and nowadays, when cyber security is becoming more and more serious social problem, simply encouraging the public participation using web application without mentioning such issue doesn’t seem very convincing to me. Or perhaps I am just being way too skeptical about this…


geoweb nation

Monday, September 15th, 2014

Reading  “Doing Public Participation on the Geospatial Web” made me wonder who is posting on the Internet and what we know about them. In the case of the Okanagan Fire map, some participants weren’t sharing their experiences online because they felt they didn’t have the authority to do so. This challenges the common idea that the anonymity of online forums allows people to lose their inhibitions. It is in fact the “reach and durability” of the platform that stopped them from contributing. Does this imply that the contributors have actual knowledge or expertise? It would certainly be interesting to see if those who speak up in real life are also those who feel entitled to write their opinions online, and vice versa, and then compare their qualifications.

Moreover, more weight or importance was awarded to posts with “likes” or “thumbs ups”. Who is behind these popular views, and are they trustworthy? A quick look at the comments section of any online publication might make the reader reconsider the merits of democracy. I, for one, would not want to be led by any “top posters”.

Finally, the following argument on anonymity and accuracy gave me pause: “[a]nonymity also complicated questions of data accuracy since scientists examining results on nlnature wanted the identity of contributor x as a way to verify who was (in)correctly identifying species” (26). Are the scientists identifying the correct and incorrect entries, and then want to know the identity of the posters for statistical purposes? Or are the poster’s qualifications affecting the findings’ accuracy?


[One last note, vis-à-vis the spelling of the expression as viz-a-viz: am I missing a pun or is this an English interpretation of French?]





Public Participation 2.0

Monday, September 15th, 2014

“Doing Public Participation on the Geospatial Web” explores how the Geoweb has altered public participation. In particular, the layouts and algorithms of Geoweb applications have the power to structure and influence public engagement. Do these forms of engagement support democratic ideals, or do they lull us into complacency as freedoms erode? Filter bubbles applied to many online queries limit our exposure to different opinions and perspectives, reinforcing our own beliefs, and removing us from the broader discussion. In my opinion, the creation of these online ghettos of thought facilitates citizen two citizen dialogue among like minded people but has the potential to undercut the interaction of people with differing or opposing points of you from meaningfully engaging with one another. What’s more, anonymity removes accountability for what is shared on online fora and can hamper respectful dialogue among online contributors. The elitist attitudes that this can consolidate deeply undermine the inclusive nature of democracy.
Nevertheless, the Geobweb allows its user to stay ‘plugged in’. It provides a medium of expression for those that may not be comfortable in face-to-face discussions; the anonymity it provides can empower individuals who would otherwise stay disengaged.
Similar to high school civics classes, I think we need to teach and explain the implications of online engagement, outlining its obligations, rights and responsibilities. We need to upgrade to civics 2.0.
The influence of the Geoweb on public participation is complicated. It presents challenges and opportunities for democracy, but more research is needed to fully characterize it.