Archive for January, 2013

You Can Learn A Lot from a Pupil

Monday, January 28th, 2013

Poole and Ball provide readers, with little to no knowledge of eye-movement tracking, a brief overview of the techniques, equipment, and application of the research. They, unfortunately, do not include a section devoted to geo-visualization, which would make this an exercise in read and repeat. Or fortunately, in that it provides us with a broad spectrum for interpretation.
While eye-movement tracking has made major leaps from its original design, including a metal coil affixed to the cornea, it still fall shorts. According to Poole, researchers still have not developed a standard interpretation of results. An example of which includes the duration and frequency of fixation on a target. Depending on the situation, multiple longer durations are considered positive, in that subjects are more interested in the target, or negative in that subjects take more time to encode the visual information. This does not mean the field does not have applications in GIS, and geo-visualization.
As Poole points out, eye-movement tracking techniques can be used to substantiate claims of what may be visually appealing on a case-by-case basis. GIS serves as a way of conveying spatial data in the form of maps. If maps are responsible for the quick and easy conveyance of information, visually optimal maps may be developed with the help of eye-movement tracking. Whether or not the participant is interested in the topic is up to the researcher.


Eye-tracking in Augmented Reality

Monday, January 28th, 2013

The paper by Poole et. al. discusses in details the metrics used in eye-tracking research and some of its application. However, the paper failed to mention one of the most successful commercial usage of the technology. Canon introduced SLR cameras from as early as 1992 which employed eye-controlled autofocus. The system worked very well and has led to a lot of discussion amongst photographers as to why Canon does not include this technology in their recent cameras.

Now with the coming of augmented reality systems, eye-tracking technology has the potential to revolutionize how users interact with their surroundings. Ubiquity is the most important requirement for any augmented reality system. Eye-tracking technology can be used to detect when the user seems to be confused and accordingly provide him with contextual information. Such application of augmented reality will be less intrusive and more usable in a day to day life. Eye-tracking technology can be further coupled with other technology such as GPS to make augmented reality systems more usable by increasing the speed at which it detects objects. The location information provided by the GPS can be used to narrow down the search space for the object.  For example, if a tourist is staring at the Eiffel Tower, then the system knows that he is located near the Eiffel Tower in Paris. Hence the search space where the system needs to search for similar looking objects is greatly reduced.

The whole domain of augmented reality is still in its infancy and it is up to the imagination of the engineers to find supplementary technologies that might be used to enhance the system.

– Dipto Sarkar


understanding SDSS in the age of Web 2.0

Friday, January 25th, 2013

PJ Densham’s discussion of the possibility of effective Spacial decision support systems gives a useful overview of the concepts in question. The article however, is located in the time it was written, and in an age where GIS (at least as a tool) is moving from the domain of professional geographers to anyone with an internet connection, Densham’s arguments may have to be re-evaluated.
It is conceivable that in our current context (although I wish not to be too presumptous due to my lack of knowledge on the subject) GIS and SDSS aren’t really such separate entities as they once were. Those applications which incorporate the principles of GIS (as science, tool and toolmaking) can be used to support spatial decision making. The growth of user generated content on the internet means that a new SDSS maybe able to use this data (which will often have a spatial element) to produce decisions that are more, if i will, democratic. This is in fact exactly what is done in the Rinner article. The distinctions between GIS and (S)DSS noted by Densham are not so clear cut as they may have been at the time of writing.
As such, while Densham provides a useful background to the concepts that structure SDSS, his article must be read descriptively. It gives a springboard to things that are to come, and to things that are already happening, but is dated and must be considered in our current context to be useful.


A clever Argooment

Friday, January 25th, 2013

Rinner et al. explore the capabilities of participatory GIS in a case study involving an application that uses geographic arguments in collaborative decision-making processes. The application, called ArgooMap, uses a combination of time-stamped thread conversation “mashed-up” with a map API (in this case Google Maps API), and appears to present significant benefits over decision-making without a GIS. The article is written clearly and effectively outlines first the theory/technology behind the process and then uses the Ryerson University case study to showcase the capabilities of the application.

Using Google Maps API in conjunction with user-generated content (whether volunteered or not) poses nearly infinite possibilities in myriad fields. ArgooMap is particularly interesting in its ability to add an entire dimension to normal conversation. So much of what we say, especially when we are making decisions, has geographic ramifications. Many markets and advertisers are trying, and in many ways succeeding, in parsing our monitored conversations to extract geographic content to better target products. This is largely out of our hands, but normal conversation and decision-making is not. ArgooMap seems to implement the concept of cognitive maps, which drives the conversation in alternative directions. This rings especially true in the reference to mentioning geographic content at varying scales depending on the presence of the visible map. If all interlocutors are seeing the same map simultaneously, they can refer to specific places or directions that previously only existed in the mind of the speaker alone.

As an aside, it would be incredibly interesting to see Twitter, where users are constantly tweeting back and forth, implement a map similar to ArgooMap. Perhaps when programmers solve the geotagging puzzle…

– JMonterey

Is SDSS Geoweb’s ancestor?

Friday, January 25th, 2013

In an article from the 1980’s, P.J. Densham outlines the concept of a Decision Support System (DSS), which aids the user in a decision-making process that includes a number of complex parameters included in a database. He posits that in many cases, a Spatial Decision Support System (SDSS), which uses the basic framework of a DSS, but with a spatial component, would be quite helpful. He notes that an ideal SDSS would a) allow for spatial input, b) represent spatial relationships and structures, c) include geographical analysis, and d) provide spatial visualizations. This is different from GIS in that SDSS is dynamic, while GIS is more rigid.

The need for a dynamic geographic decision-making process is clear, and in that, Densham is completely correct. However, the problem with reading this article today is that GIS has transformed, in large part, away from its infant stage and more towards Densham’s SDSS. More specifically, the Geoweb, rather than the more orthodox desktop client, incorporates many of the outlined SDSS properties. User-generated content allows for near-real-time data, and modern technology allows for rapid regeneration of content on a web page. In fact, it is interesting to read this article in conjunction with the Rinner et al. article, written roughly two decades later, about the use of user-generated content to structure a GIS. Another application is Google Map’s traffic feature, showing roads as red (heavy traffic), yellow (moderate traffic), or green (little or no traffic). As users see this data, they decide, for instance, to choose the “greenest” path, but if enough people do so, the green path becomes the red path, and the red path eases. The data is thus dynamic, and the map adjusts accordingly.


Crowd Sourced Master Plan, One Step Removed

Thursday, January 24th, 2013

Rinner, from the beginning, claims that user-generated information is not considered a “serious” pursuit. To test his theory, he scrapes user-generated text for geographic references, only to retroactively apply a geo-reference to the post. The researchers, who are responsible for geographically referencing the post, strip away the users involvement in the geographic context. This can introduce a large source of error into the data. Consider, on page 14, a marker’s placement corresponds to the “label in Google’s “map” view.” In the event that a user refers to a general area, choosing to place a label greatly reduces the dimension of the users perspective. Much like a home is not a coordinate, but a structure, and the surround property, land, or neighborhood. Had the researchers allowed the users to actively tag locations to their posts, they would have gained far greater insight into the users intentions.

The creation of a Master Plan cannot be accomplished using the scientific method. Studies can find correlations, in certain areas, but many fall apart when the study area is changed. This may be due to social and cultural differences. In that light, and working on the basis that people are subjective creatures, a crowd-sourced master plan can gain from further empowering the constituents. In the case of the Ryerson Master, providing the user with the ability to choose the location of their post’s geo-tag may have developed another dimension for the study.

As a side note for crowd sourced urban planning, I do not think that even high-scale maps are sufficient. The city is rarely experienced from the air. With that in mind, I am in favor of developing forum in which people can experience the city from the ground. To my knowledge, no such technology yet exists.


Web 2.0 and its application in DSS

Thursday, January 24th, 2013

In their paper on the uses of Web 2.0 to support spatial decision making, Rinner et al. address one of the problems that M. C. Er identified in DSS 20 years earlier: group decision making. By using PGIS as a source of data, making decisions for a group of people is made easier. In order to test this, the authors designed Arguumaps, where users could make geographically referenced comments about campus/city life or the Ryerson identity. Though some limitations were present, the power of PGIS is clear in its application of online mapping.


Whether this data is useful in DSS is a whole other questions. The authors argue that this case study shows that it could be a useful tool by having users vote on preferred geographically reference locations. For example, instead of posting comments about their favorite restaurants, users could cast votes on restaurants over a whole array of criteria, thus helping other users pick which restaurants they would want to go to.


Presently, 5 years after this article was written, google implemenets these services on their maps. Great strides have been made in mapping as a support to spatial decision making however much ambiguity still exists over the exact definition of DSS.


Pointy McPolygon


Spatial Decision Support from the Crowd

Thursday, January 24th, 2013

The Rinner et al article explores the intersection of spatial decision support systems (SDSS) and volunteered geographic information (VGI) with their development and piloting of an argumentation mapping web 2.0 application intended to solicit and map spatially-grounded citizen input and discussion. 

Rinner et al single out planning processes as areas where such applications have potential.  By tying user discussions and feedback to explicit locations, the responses can serve as a qualitative gauge by decision-makers as to the relative importance of criteria within a SDSS model.  There is even the opportunity to add a quantitative element to such conversations by integrating a positive/negative rating system to the threaded messages (like a spatial Reddit!). Overall, Rinner et al’s project aims to find effective ways to crowdsource planning decisions and amplify the ideas of citizens using emerging web 2.0 technology.

Argumentation mapping and other geospatial mashups’ applicability to decision support are not without their concerns. As we learned the hard way in GEOG 407, a #neogeoweb 2.0 application is only as good as its programmer, and can only ever be as good as the underpinning API.  Four years after this paper’s publication, many of Rinner et al’s suggestions for improvements to the API are still unaddressed by Google.  Formal integration of the data collected in ArgooMap with SDSS models is still a long way off: for now, it is limited to qualitative uses.  In addition, these digital consultative avenues, even if they are improving in terms of end-user functionality, may still be exclusionary: from the digital divide, to gender dynamics on the internet, to the less affluent simply having less free time to invest in online civic discussion, there is a role for critical geographers and GIScientists to suggest ways for SDSS and its related tools to be more inclusive and thus more likely to be truly democratizing the decision-making process.


Thursday, January 24th, 2013

In reading MC Er’s 1988 article “Decision Support Systems: A  Summary, Problems,  and Future Trends” I am left with the question of how the concept of DSS can produce technologies that are at once broad and specific, such that they can account for both individual and group needs. I wonder too, how much further we can take (and undoubtedly have taken in the 25 years since this article’s publication) this idea before it extends beyond support and into a more active tool.
An interesting aspect of this paper to me was Er’s mention of  a DSS that might be tailored to ones’ decision making style (as determined by a Myers-Briggs test).  While the idea seems somewhat absurd or flaky, it does point towards the concept of technology designed around the needs of the user as opposed to some abstract population. However, in making decisions that are influential to people other than the user, would such specification truly prove helpful, or to the contrary? Further, Er notes the need for development of group DSS. How do we design a DSS that can account for the diverse styles and needs of a group coming to consensus? What does support mean in this context? Does it merely mean an interface for the organization of ideas, or one that may evaluate figures?
There are, in any problem, many factors that must be considered, some of which may not always be quantified or obectively assessed against one another. How can we produce a DSS that may aid us to weigh the options that may be actively analysed while not losing sight of those that may not be?


Beyond the GIS layer cake

Thursday, January 24th, 2013

What is the role of GIS in supporting decision-making processes? It looks like I’m not the only one left with that question after the readings…

There is the GIS tool that continuously allows to add information (the layer cake), store and organize a tremendous amount of data, analyze the data, make maps and better inform decision makers. Is it the only role? Is it enough? Does having a lot of information allows decision-makers to make better decisions? I don’t think so. As M.C Er puts it : “decisions are based on personal experience and subjective judgment.” Taking decision is then a very individual process. As sidewalkballet argue in this blog, maybe the GIS way works for a certain cognitive style of people.

There has to be something more than relying on great good more and more information to make good decisions. Is GIS playing a role in decision-making processes because it’s more cost-effective? That is really hard to answer as M.C Er points out. If we don’t know if there is some economic benefits in using GIS why is it used? Well maybe because it’s a good way to legitimize the process and legitimize the decision. Decision-makers and managers can say :” Look we are so up to date; we are using GIS!”. It can become a way for the agencies to promote ‘good practices’.

Furthermore, I think that seeing the role of GIS in a technocratic way can lead to focus more on the processes of using information (gather information, organize the information, analyze information, communicate the results…) rather than on solving problems. That could be a very comforting thing when it’s complex to identify the problem that you’re dealing with (unstructured problems). However, I don’t think that it’s the way to optimize GIS and decision-making processes.

Even new technologies and Web 2.0 can serve the purpose of simply adding information produced by citizens about local knowledge. However, as it was already mentioned in this forum, the decision makers are not necessarily willing to take that information into consideration.

What if the role was to improve collaboration between stakeholders? Rinner et al. talk more precisely about supporting deliberation in the decision-making processes rather than the decision itself. Now that is GIScience! It is about interactions between the technology, users and producers in a specific context. The outcome is a debate on how different persons view their environment. In the example of the Argumap, the thread structure reveals the spatial thought processes of participants with the relations created between arguments. I might be a little optimistic, but the debate and discussions that are created trough the interaction have a potential to reshape existing structure between agencies and citizens.


The (past?) future of Decision Support Systems

Thursday, January 24th, 2013

M. C. Er, in his paper on Decision Support Systems written in 1988, critically examines the future of a technology that – to say the least – had a lot of room to grow. While his predictions for the future may have read like a sci-fi novel at the time of its writing, they weren’t too far from the truth, especially considering the amount of technological development that has occurred over the last 25 years. While talking about considering personality and cognitive style in decision making may seem like a given to us now, the fact that he was able to recognize that need at the time is somewhat amazing.


Much of the article is still applicable today. While technologies have advanced, the exact definition of a DSS is still unclear. On the other hand, M. C. Er states that the DSS should be centered on the problem solver, while in reality this paradigm is shifting. PGIS means that the data will start coming straight from the source, enabling a more accurate use of a DSS. Facilitating the problem solver is no longer the main concern for DSS, however data quality and data sources have come into the spotlight in a world that seems exponentially more complicated than it was in the year this article was written.

Pointy McPolygon

Has GIS Caught Up with Densham’s SDSS Ideals? Has BIS Left Us in the Dust?

Thursday, January 24th, 2013

Densham’s article reviews work on spatial decision support systems (SDSS), conceptualizing them as distinctive from the GIS of the time.  Crucially, Densham problematizes the direct application of GIS to solving spatial decision problems, proposing instead that dedicated SDSS software incorporating specialized architecture and a modular code repository or model base management system (MBMS) be developed instead. Nonetheless, the author envisions a continued role for geographers in the informed decision process, in order to avoid “the selection of variables with inappropriate levels of resolution and geographical extent… ultimately result[ing] in solutions that are deemed unsatisfactory when evaluated in terms of the quality of the decision-making process that generated them” (p. 403).

Densham argues that “[c]urrent GIS fall short of providing GIA capabilities” because “their support of analytical modeling is lacking”, their display and reporting capabilities are limited, and they “are not flexible enough to accommodate variations in the either the context or the process of spatial decision making” (p. 405). There is no date on the paper, but its most recent citation is 1991, suggesting that when this article was published, the Soviet Union was still a thing and Apple products were at their first peak of popularity: has GIS today overcome the limitations of Densham’s era?  I would argue it has. For starters, hardware and operating systems have made huge advances since the year of my birth, supporting greater data storage, graphical capabilities and computational power for analytical programs (even interpreted ones!).  Meanwhile, the advent of the internet along with new, more user-friendly scripting languages like Python, has made implementing model capabilities within GIS’ DBMS framework and the existence of code libraries—both dismissed by Densham as not feasible—possible.  These technological advances, along with improvements in graphical representation and user interfaces, have enabled GIS software to integrate decision support modules (such as the classic SDSS problem, location-allocation) directly into the software or as a plugin while retaining the potential for customization of decision models.  Today, producers of GIS software packages aggressively market their products’ SDSS functionality.

GIS and its enabling technologies have made strides, but so have competing technologies in business information/intelligence systems/software (BIS) such as the impressive Tableau software package. Despite the increasing role of spatial data visualization, analytics and decision support in BIS, development of these tools tends to be the realm of computer scientists and not geographers. Even though tech has advanced considerably across the board, Densham’s argument that geographers are not obsolete still resonates today. As geographers, we need to assert our place at the spatial decision support table, both by advancing GIScience such that GIS remains relevant to (and if possible, ahead of) contemporary decision support analytics, and by reminding software developers and decision-makers of the importance of a nuanced understanding of spatial concepts and considerations.


The evolution of Spatial Decision Making

Thursday, January 24th, 2013

Claus Rinner delves into the increasing importance of Web 2.0 applications in spatial analysis and decision making process. He highlights the fact that, with the advent of more advanced and easy to use web apps, local geographic knowledge is increasingly being included in decision making processes.  More specifically, the emergence of web based GIS apps, such as Google maps, yahoo maps etc. has made basic spatial analysis extremely easy for the average user. Densham highlights the fact that these tools have a relatively similar interface, making them both faster and easier to use.

I find the evolution of web based apps extremely interesting. As more and more people use these apps, tons of of geodata is produced. This in turn provides of a huge database of potential data for multitudes of spatial analysis and research projects. Apart from obvious ethical issues, I believe this type of data will revolutionize both the research and decision making process, in a wide variety of fields.

One particular aspect of the case study conducted by Dersham was how the use of web based mapping software could be used to enhance a discussion forum. Throughout the discussion, the mapping feature provided for more focused discussion on the particular geographic areas that the participants were interested in. It was interesting to see how through the analysis of the geospatial data, it was visually apparent that most of the discussion members wanted to focus on improving a specific are of their school campus. This holds many implications for various fields, such as sustainable development, where policies could be better tailored to be most effective, based on the analysis of user provided spatial data.

Overall, Web based concepts seem to be evolving quickly and becoming more and more integral to spatial analysis. As these technologies continue to develop, spatial decision making should become much more effective.

Victor Manuel

Are SDSS actually important?

Thursday, January 24th, 2013

Densham gives a good account, albeit very dated (1991) of the basic characteristics of spatial decision support systems. Densham chooses to focus on the importance of these systems in decision making processes, arguing that they are more adaptable to the complex characteristics that must be factored in by decision makers.  He concludes that further development would allow decision makers to solve more complex spatial problems.

As I read through the article, the one recurring thought that kept coming to my mind was how much the field of GIS has evolved since the article was written. Spatial decision support systems have evolved tremendously with the influx of huge amounts of user based geodata. This in turn has led to more complex spatial analysis, with ever changing factors in space and time.One component I found well written was the distinction between GIS and SDSS. Densham highlights the shortcomings of GIS, mainly the lack of Geographical Information Analysis capabilities. He goes on to give a good description of SDSS, albeit one that was much more relevant during the time of writing. The age of the article becomes even more relevant when Densham goes on to the describe some of the problems facing the evolution of SDSS. Modern technology, such large increasing in computing power, have completely evolved SDSS into dynamic models that are affected by a multitude of changing characteristics.

Overall, the article gives great insight into the early days of SDSS. However, modern technology has rendered many of the issues brought up by Dersham rather obsolete.

-Victor Manuel



Thursday, January 24th, 2013

M.C. ER attempts to untangle data management from the impact of data use. In doing so, though, he attributes far more value to Decision Support System than it merits. The age of the paper (1988) may have something to do with this, but the idea that DSS will be able to support all levels of decision-making is excessive. Furthermore, the description of DSS makes it seem that it will eventually become autonomous. At least, that seems to be the goal. By that point DSS will have to be relabeled, DMS, Decision Making System. The reason being that M.C. ER describes systems that can act on their own decisions. He even furthers the narrative by mentioning artificial intelligence in the concluding statements.
As for GIS, System or Science, it still has not quite reached the point of making decisions in place of top management. Let alone the fact that GIS has a very narrow spectrum of applications. If we were to use GIS as a case study of the success or failure of DSS, it would fall short of making decisions for management, but is definitely useful in supplementing the knowledge set of the decision maker.
Then again, that is not to say that it has failed or succeeded as a DSS, in that the definition of a DSS is, according to M.C. ER fluid and open to interpretation, considering the numerous attempts at classifying the field.
One assertion of the paper that caught me off guard was this, “It is important to know that human decision makers generally do not make decisions based on the probability of success, because the penalty for a vital decision that turns out to be wrong is normally substantial.” If this were the case, how else would people make decisions? Gut feeling? If gut feelings do not take probabilistic guesses of success into account, than they are no better than random guesses. In that case, creating a DSS is easy. Unfortunately, I do not believe this is the case. The user is a vital source of information and decision-making along the way, and is unlikely to be stripped from the process.


Spatial Decision Support Systems

Thursday, January 24th, 2013

P.J. Densham’s discussion and explanation of “Spatial Decision Support Systems” is a good summation of the basics of a “spatial decision support system” (SDSS). Even so, the discussion seems to be a bit out of date in relation to current GIScience and SDSSs, as user interfaces and report generators have been modified and further developed, to resolve the issues and needs Densham proposes. Furthermore, some of the ways SDSSs are now used, such as the integration of dynamic modeling and GIS programs, are not even mention, as technology has advanced since the publication of this discussion and explanation. For example, my current research has an aspect of dynamic modeling that it is represented spatially, and new programs now exist that can graphically represent dynamic models in the context of a spatial area. To clarify, Densham seems to only consider single state representation (or one time frame) in SDSSs not states in dynamic flux which change in relation to changing conditions. Today, with the facts of environmental change and the speed of human development dynamic representation is becoming the norm, especially with predictive capabilities, for managers and specialists looking at spatial variation in this new context of understanding. Although the article is a good representation of the time, a lot has changed. One example of change is that database management now has different classification and retrieval styles for spatial data, such as images and descriptions. With changes in interface and computing power, SDSSs are now integrated between programs and user friendly, becoming part of most types of spatial analysis and decision making today.




Decision Support Systems

Thursday, January 24th, 2013

I think it’s interesting that this article (written in 1988) starts the discussion by suggesting that there has been no consensus on defining what a DSS is – it reminds me of the intersection we’re at with GIS; it is a tool or a science? M.C. ER notes that some have tried to different a DSS from a non-DSS through the intention of the design, though many counter examples arise (M.C. ER’s, 1988). Similar to our discussion about GIS as tool, science, or somewhere in-between, perhaps we can use a similar methodology in how we define what a DSS is. How the DSS (or tool of a DSS) it is used, and the intention of the tool in that particular context dictates whether or not it a DSS.

M.C. ER acknowledges that “it cannot replace upper-level managers in decision making”  (M.C. ER’s, 1988), yet I would suggest that if the decision to be made involves any type of complexity, or exceptions, the group should be broadened to encompass a wider range of people. After all, it is a “support” system, implying that it is there to help with the process, rather than making decisions unless the path to a decision can always be deduced to a binary logic.  Since 1988, DSS has significantly evolved and grown in complexity and sophistication. Group DSS (I think of group DSS in terms of electronic meeting systems, such as web conferencing from around the world) have made its mark in the workplace, while I’m less sure about how AI DSSs have progressed since the 90’s. Perhaps a missing, or unsuspected trend that emerged was the integration a spatial component into a DSS, whether it be the ability to web conference from around the world, or the ability to seek new patterns that can affect decisions when factors and information can be geographically tagged.


People-Based GIS and Increased Participation in SDSS

Thursday, January 24th, 2013

Densham makes an extremely valid point when referring to the limited uses of conventional GIS, typically known as a desktop format with limited flexibility.  This sort of work still exists today when we make static maps through the use of conventional software such as ArcGIS.  However, we have definitely made the leap into Spatial Decision Support Systems through the integration of the web into GIS analysis and real time data management and manipulation.

It is through this way that we have been able to realize what Miller was talking about last week.  This was the need to move away from static, rigid place-based GIS to more dynamic, holistic and integrated people-based GIS.  I believe that this is in line with Spatial Decision Support Systems that allow users to interact more with the information, tweaking it depending on their certain needs and interests.  As space becomes something that people move about more freely in, the ability to adjust to this mobility is essential.

Additionally, I believe that SDSS are no longer confined to “managers.”  Average citizens are able to use these types of systems to make decisions that affect their daily lives.  For example, this could be allowing someone to input their location and desired destination into an application, which outputs a variety of routes to get there (various buses, walking routes etc…).

I see the use of SDSS continuing to make its way into the daily lives of everyone, not just the bank manager looking where to open his/her next branch



Dire Consequences of Increased Reliance on DSS

Thursday, January 24th, 2013

This week we read another paper that brings forth important implications although it was written almost 25 years ago (yes, 1988 is 25 years ago).  The growth of Decision Support Systems have allowed for huge expansion in various economic industries and given companies the power to increase their decision making efficiency.  This was no doubt seen by M.C. Er.  However, the incredible growth of DSS has created whole industries that are essentially automated.

While reading this paper I could not help but think of the current state of the stock exchange.  Investment banks have now developed incredibly complex algorithms to run thousands of trades a day based on fractions of a cent.  This normative support allows for the transaction of millions of dollars a day, essentially with zero human interaction.  The only difference between some major companies is their ability to perform these functions quicker, based a lot on their proximity to the stock exchange itself.  My worry is that this intense automation will someday lead to a catastrophic collapse.  We’ve seen what can happen when financial markets become unstable, but I believe that the cataclysmic risk grows every day as investors continue to automate their transactions.

Of course, this is a small look at one industry in a very diverse global economy.  However, I think the main point is that the increased reliance on DSS eliminates the checks and balances that the human mind can bring forth.  In many cases this may be for the better, but other times it will not, and the consequences may be dire.



GIS, SDSS, what?

Thursday, January 24th, 2013

Densham’s article outlines the framework and uses of a spatial decision support system. For much of the article I thought of GIS as an SDSS itself–the descriptors Densham uses to define an SDSS seemed to fit GIS. SDSS is iterative, participative, and integrative and GIS is, too; iterative in that the GIS can offer a set of solutions (i.e. position of a toxic waste site), participative because the user is the one actually defining the problem and doing the analysis, and therefore integrative–the user inputs value judgements when making a decision based on the analysis.

Upon further deliberation I started to see the rift between SDSS and GIS. A GIS is a static environment in which you need a structured problem in order to produce any results. Without a research question and a foreseeable goal, I can’t see GIS being of much use. So is that the kicker? SDSS provides an environment for ill-structured problems via cellular automaton modeling? That’s the only difference in use that I can tell from Densham’s article and my current knowledge of GIS.

Regarding the article itself, I thought it was well formatted, and I enjoyed the clean break downs of what DSS and SDSS are, and the framework structure of an SDSS. Because it was written in 1991, I wasn’t sure how much of the noted differences between an SDSS and GIS are still applicable today, which prompted further searches on the topic.

Densham P. J. (1991) Spatial decision support systems, In: D. J. Maguire, M. S. Goodchild and D. W. Rhind (eds) Geographical information systems: principles and applications, London: Longman, pp. 403 – 412.