Computers, Society, and Nature

The concept of geospatial cyberinfrastructures seems to draw from all aspects of GIS: where it came from and where it is going.  The Yang et al article was a very thorough introduction to GCIs and their uses and limitations.  It also seemed to incorporate much advancement in GIS that we have read about over the last few weeks, and presented an opportunity to visualize how all these technologies may work together, their strengths, and their weaknesses.

This topic seems very current, as you hear more and more today of cloud computing, information being held and hosted on the world wide web, and so on.  It emphasized even more the need for shared knowledge and languages, good metadata, and fast processing.  The wealth of possibilities for GCI, as well as the inclusion of domains where it is already useful, was an interesting aspect of this article as well.

What I found to be the most important limitation, that seemed to run through not only most domains and uses mentioned in this article, but recalled as well many of the other tools we have discussed, was the difficulty in dealing with immense amounts of constantly flowing, real-time data.  This issue in itself seems to incorporate many of the needs mentioned above, and is really the crux of what, in my reading, GCIs are about: the ability to successfully, quickly, and knowledgeably share information, questions, and expertise, analyze and upload data, and more.  However, I agree with Madskiier in their suggestion that GCIs are very global by nature, and thus would presume that, through adequate cooperation, this could be a task undertaken by many, as opposed to just a few.

As a student, I found this prospect incredibly interesting, and it drew my mind to the countless hours spent searching for geospatial data for simple research projects.  While students perhaps a fewer connections than established scientists, we also have the power of McGill behind us–and yet finding (good) data is still tremendously time consuming and challenging in many cases.  The idea of a large infrastructure supporting free global geospatial data is quite appealing, and something I hope to see come to fruition.

–sah

Mapping as cartographer James Cook knew it is no more, but yet still fully present. Confused? Let me explain. In their paper entitled “Research Challenges in Geovisualization”, Maceachren and Kraak state that maps of the past were designed to be not only a visual aid to navigation, but also to be a database of spatial information (pg 3) such as place names, bays, coves, cities and related information such as their position (absolute and relative) and the distance between them and neighbouring features, to name a few.

Today, mapping is still very much a graphical aid to data visualization, but unlike in the past, maps are not just a static database of places and locations.  Today’s Geo-Web 2.0 and data visualizations platforms like Google Earth can do so much more than display local data, they have the whole internet as a database (pg 3) and can draw on information located in servers and on subjects all over the world with a single URL or script.

This means that the possibilities of today’s cartography are endless, we are not even limited to two, or even three dimensions any more.  Visual Earths (a 3D surface) can display 2D map data, 3D details such as buildings and topography and most importantly, changes over time with time sequenced raster playback.  In fact, display of change over time in Virtual Earths, rudimentary as it is, is still as good as, if not better than, many of the solutions proposed by GIScientists for use in traditional GIS analysis.

In conclusion, mapping today is just as useful as traditional maps, but more so.  We may not all be Cook, but we have access to a very powerful set of geo-visualization and analysis tools today that can only spell great things for our future and the future of GIS.

-rsmithlal

One strategy suggested by Elwood is that “enriching data with information will help the user assess heterogeneity” although to me this does not seem to assist with solving or managing the problem of data heterogeneity. It has been mentioned in class that data is not typically well documented in GIS and that one way to provide information about it is to create metadata. In the world of the internet where massive amounts of data now have spatial references, and in many cases change rapidly, it is not practical to try to provide more information about every piece of data to try to reduce heterogeneity and standardize the data. Since additional data about data would provide even more information to sift through, this also seems rather counterintuitive. While I recognize there is heterogeneity in data, I do not understand the use of assessing heterogeneity but see instead much more use in actually working with heterogeneous data and focusing more time and effort in promoting methods to do this such as in particular contexts as mentioned by Elwood.

-Outdoor Addict

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