Computers, Society, and Nature

The article about by MacEachren and Kraak was excellent in its introduction to the challenges of geovisualization while simultaneously fuelling the imagination as to the possibilities of these technologies. As a geographer, I too admittedly love maps as Andrew GIS also stated. One of the things that fascinated me in this article is that the map has been redefined, a fact that is well advertised by these authors. I have chosen to extract the various phrases used to define what maps are today in order to emphasize this point. Maps are now “inexpensive”, they are “dynamic portals”, they are “interfaces”, they are “realistic” yet “abstract”, they are “forms of representation”, “active instruments in the user’s thinking process” and “metaphors in design of non-geospatial visualization tools” (although I admit I am not exactly sure what this last one means). A picture may be worth a thousand words and although a paper map is more than a picture and worth many words, maps, today, cannot be quantified in terms of a mere thousand or even million words.  I do not mean to say maps were not some of these things in the past but today they are even more than they ever have been. This makes their understanding and analysis more pressing than ever before and provides the field of geography with yet more reason to expand into the digital realm through more than our largely static structure based GIS.

-Outdoor Addict

The Elwood piece is less focused on geovisualization than the MacEachren and Kraak article. It suggested that in order to make data more global we should standardize the data. When discussing Kuhn’s piece Professor Sieber noted that much like German culture in general, that the data was extremely structured. Apparently the models designed by Kuhn run very well because the data is well structured.

That being said with the amount of data streaming in everyday it seems unfathomable to standardize everything. Elwood suggests that automated standardization is a possibility but this idea scares me. Imagine a world where you cannot control your own data. It seems that this reality is approaching everyday (with the recent blackout protest suggesting imminence). Schuurman also adds that automated data standardization may not be adequate due to dynamic data sets; individuals, constantly modifying data may be difficult to anticipate. What happens when data is changed and standardized? What happens when one parcel of data under a certain label is relabelled? Will a user be notified of the change? Or will the data be transported to another location?

Andrew GIS

Elwood offers us an introduction to the challenges of geo-visualization and the integration of data. One of the major issues facing geo-visualization is the sheer amount of data that are being generated, which is also very heterogeneous. Considering the vastly increasing amounts of data, I can’t help but be under the impression that there is a sense of urgency for the cause of more effectively “incorporat[ing] spatial knowledge into digital environments.” Perhaps this urgency comes from the notion of a group of researchers time-consumingly creating a universal ontology, as was seen in last weeks readings. As the data pile up, the time required to unite all of it also increases.

But, is there a sense of urgency? As stated by Elwood, data are being created in an increasingly dynamic manner, which can be used in very diverse ways. She also discusses the use of metadata, so perhaps providing this will be key will be to ensure that future use of all this data will not be hindered. This will likely be a difficult task, as it is hard to imagine what type of information will be needed for future ontologies. Like MacEachren and Kraak posit, however, creativity as well as efficiency is spurred by these connections. Therefore, it is not necessarily urgent for us to figure this all out now, but we’re probably missing out on some interesting connections and revelations.

– jeremy

Elwood mentions many technologies/applications but seems to focus on geoweb and VGI. However, these are hardly the only interesting and new developments in visualisation. Wiki maps, Google Maps, and other internet based mapping tools all do the same thing – they work on visualising data on a traditional 2D plane. Sometimes you’ll get interactive symbology (like what kmls are capable of). I may be reading the article the wrong way, but I don’t quit understand what the focus on VGI has to do with visualisation. Certainly, products like Google Maps allows many users to contribute to a single dataset, thus bringing up problems of semantics when applying tags, but this is hardly a new problem brought about by a new visualisation platform. These sorts of problems have been around since before participatory GIS/VGI, but have only been blown up due to a much larger number of contributors.
The section on tagging and ontology is interesting – but does this affect ‘visualisation’ or analysis and querying? Perhaps the title of the article should not just be ‘geovisualisation’ technologies. When I read the title, I assumed the article would be purely about new methods to display data, and the effects they have on the way we think (perhaps focusing on things like dynamic zooming in products like Google Maps, or displaying of attributes). The use of the word ‘technology’ can be a little limiting at times.

The ‘real’ new technologies of visualisation should be in things like future 3D hologram displays (the real kind, not the stuff with the smoke and lasers) – these are the new forms of visualisation that, when they come to market, will have a real impact on how we choose to display data (such as, how to take into consideration that the audience is no longer viewing from a fixed angle).

The MacEachren and Kraak article is very interesting in the crosscutting research challenges section. They make a very good point that visualisation needs to develop with other areas like interfaces, since the way we interface with the data is also a key part of the experience. I found this article a little more relevant, but it is still at an exploratory stage, so gives some rather vague recommendations at times.

Final though: while visualisation technology is intertwined with other issues of data, interfaces etc., if we don’t just talk about the purely representational part of visualisation technologies, why are we using those two words?

-Peck

The TED talk posted by sah is very interesting and I think it is a perfect example of the exciting developments occurring in GIS and geo-visualization. The example of Bing Maps demonstrates the ways in which different technologies (photography from flikr and street maps) can be combined based on their geographic locations, enveloping the idea of a ‘canvas for applications.’ This video, however, also highlights the challenges associated with geo-visualization, which MacEachren and Kraak discuss in their article.

One of the aspects of the article that appealed to me the most was how MacEachren and Kraak pose the question of whether or not these technologies enable people to think differently about the world. Specifically, their question seeks to understand how creative thinking is impacted by these technologies. For example, a reason Google Earth has revolutionized the mapping world is due to the creation of “slippy maps.” Has this concept of a computer-based map, which displays the world naturalistically, changed the way we see the world? I would argue that it has and I think that the Bing Maps example highlights this well. The ‘mashing-up’ of different applications enables users to make connections that were inconceivable before.

I think that it’s also very important to consider that geo-visualization is always a work in progress—an issue that MacEachren and Kraak’s article exemplifies well—and needs to be supported by researchers. One of the concerns that arises from this development is the accessibility/usability of technology produced as a result of these advances. Interestingly, in a discussion I had about developing an application for mapping the accessibility of Montreal for those with disabilities, many individuals found that “slippy map” applications were very difficult to use. So, while this idea has completely changed the way many use and perceive geographic information, it has also potentially left behind individuals as well, perhaps solidifying a kind of digital divide. MacEachren and Kraak delve into this problem, but I think it cannot be stressed enough how important it is to consider these aspects during this development.

– jeremy

My main qualm concerning geovisualisation is the insane amounts of data that is popping up on the Internet daily, and how people are trying to go about making any sense of it and using it for research (in academia, for use in constructing political policies, generating public knowledge, etc.). Data is gaining increases in complexity and heterogeneity simultaneously as new uses are being found for this data. Kraak and MacEachren outline that geospatial data resources are being used to create visualization tools that enable understanding and recreate knowledge. From my understanding of the article, not many measures are being enacted to ensure the validity of the data and subsequent knowledge it creates. But are they even necessary?

Particularly following the problems of semantic differences in data across users as well as the presence of collaborative sources, data seems to have inherent problems with translatability when it comes to interfaces trying to support individual differences. People view things different ways and at varying scales, and in the realm of geovisualisation where the social is becoming increasingly prominent, how do we account for the differences seen and deem what is “correct”—how can we say what is valid information and what isn’t?

I suppose the answer lies in the problem. With an increasing number of users creating data there is also an increasing number of users checking the data. Interactivity and collaboration allows people to change data—a sort of built-in member checking. Ensuring validity is as great of a responsibility as generating geospatial data in the first place.

Further thoughts: As user generated data is checked by other users, does this infer that the data used to produce knowledge will reflect some sort of regression towards the mean if outliers are eliminated? In a social aspect, will geovisualisation just show the averages in spatial perception?

-sidewalk ballet

This article made me really excited.  I love that it emphasizes the evolution of maps.  Now, when I am asked (as a geography student) if I make maps, I can say, “YES!”, knowing that means so much more than simply (or sometimes as we all know, not so simply!) drawing lines on a map, and actually creating a dynamic database that reflects an accumulation of spatial and non-spatial data.  The idea of maps becoming so much more than a method of visualization, but methods of visualization AND data storage, representation, data manipulation, etc is incredibly fascinating.

Despite the fact that it was entitled “Research Challenges in Geovisualization”, I managed to overlook the “challenging” aspect, and really focus on the amazing potential of geovisualization.  It’s true that there are a lot of challenges–but each challenge merely brought about excitement for the prospect of these challenges being overcome and the full potential of geovisualization being realized.

If you Google “Digital Earth” you get many various hits, but one in particular that I thought impressively captured an aspect of the integration possibilities with geovisualization is here: http://www.ted.com/talks/lang/en/blaise_aguera.html.  This video is a TED Talk discussing Bing Maps and Digital Earths.  Obviously, there are many problems and questions that must be asked of technology such as this (as MacEachren and Kraak so thoroughly pointed out in their article), but the implications are nevertheless fantastic!

On a more technical note, I think the suggestions presented by MacEachren and Kraak were very interesting, and the emphasis on the interdisciplinary requirements of a task such as this was well noted.  The nature of geovisualization seems to require interdisciplinary work, as it is the integration of many areas of expertise, and data in many forms.  All in all, I am excited to see what the future brings for this rapidly emerging field.

–sah

MacEachren, Alan M, and Menno-Jan Kraak. “Research Challenges in Geovisualization.” Cartography and Geographic Information Science. 28.1 (2001): 3-12. Print.

Geo-visualization seems to present an endless number of opportunities, for both public and private groups and individuals, to partake in data collection, distribution, and analysis.  The issue of metadata seems to be prevalent here, and recalled the discussion on ontologies of last week.  How do we process this immense amount of incoming data when there is not a shared understanding of what it actually is, and how it is being described?  Elwood stressed this need for shared understanding, and I agree that users must be wary when working with this digital spatial data–it is dynamic, heterogeneous, and user-generated.  And not that this is a bad thing, but rather, it just means that the initial intention of the creator may not be as evident as data collected by the USGS, for example, as a way to clarify how the data is being qualified.  So the desire to create ontologies is understandable.  For example, Elwood describes the example of someone who labels an image “close to X location”, and suggests that this “close too” can cause problems.  How do we integrate this qualifications of location that make sense to humans, but not to the traditional mathematics GIS operates with currently?  In my opinion, this is the largest obstacle to overcome.

What the Elwood article also highlighted for me is that there is a huge onus on the public here, and much of this data should come with a big disclaimer.  It seems that this is a technology advancing at a pace much faster than the ability to properly create and cite metadata, and that it is not necessarily being misused, but perhaps more accurately, misinterpreted.  Although, Elwood also mentioned that there did seem to be a blatant misuse in some instances, which means that users must be even more aware when using and interpreting this data, because a mistake may not be honest, but rather intended to misdirect the user.

All that being said, the usefulness of geo-visualization technologies is undeniable, and this is an exciting and interesting field.  As long as there is constant questioning and continued research into the ability to integrate this data into more traditional, established iterations of “GIS”, as Elwood mentions, it can continue to expand in both scope (of content, and possible uses and users) as well as reliability.

–sah

Elwood, S. 2009: Geographic Information Science: new geovisualization technologies — emerging questions and linkages with GIScience research. Progress in Human Geography 33(2), 256-263.

Part of Elwood’s paper considers the implications of using data provided from different users. Data providers stemming from different backgrounds and cultures approach information, its synthesis, and its portrayal in varying ways. This heterogeneous data is further transformed through the manipulations required to make any sense of it. Elwood notes, “data are dynamic, modified through individual and institutional interactions and practices” (259). How can we ensure that the meaning instilled by the original user is carried through all kinds of manipulations and transformations, especially when primarily deciphering the original meaning proves to be laden with complexities?

Elwood provides an overview of many solutions to grapple with a wide array of geovisualisation challenges, but I think we might be getting a little ahead of ourselves. Surely there are a vast number of challenges to be addressed (as seen also in the MacEachren and Kraak article), but can we do it all at the same time? Making sense of original user data seems to be of primary importance before we can assess how it changes through practice and collaboration. While initially seeming counterintuitive to user friendliness, approaches like “standardiz[ing] terms across multiple sources” (258) and using formal ontologies may prove necessary in trying to etch out semantic differences in user provided data.

How can we work collaboratively if we’re talking about different things? We can trace the “modification of concepts in a spatial database as they are used in the process of collaboration” (260), but what do these concepts mean? Can we actually standardize open, user-generated geospatial data in order for it to be interoperable? With the increasing amounts of data sources and data heterogeneity, it looks like there is a long, winding road ahead of us.

Elwood, S. 2009: Geographic Information Science: new geovisualization technologies — emerging questions and linkages with GIScience research. Progress in Human Geography 33(2), 256-263.

-sidewalk ballet

I agree with sah about this article particularly with respect to the need to have task specific ontologies rather than a specific universal ontology of landforms in many cases. Those who study a mountain or require precise definitions of what a mountain is would require an ontology of landforms although they may be the only ones to use such an ontology. In class, it was mentioned that keeping spatial uncertainties present in the data was often very important in representing different views on intangible concepts such as disputed country boundaries. This same thinking can apply in terms of ontologies as well.

An ontology, to me, seems like a dictionary of the spatial meaning associated with a particular word. In this sense, and perhaps I have misinterpreted what an ontology is exactly, an ontology could have multiple definitions of a particular word and the user could select the correct definition for their purposes from the ontology. I compare this to different types of citations available on citation manager software. There are many different ways of representing crucial citation information and the user need only select the one they require. Why could this not apply an ontology of landforms?

-Outdoor Addict