Computers, Society, and Nature

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

GIS is known to have its pre-defined categories and way of being in the world. In fact, GIS has its own ontology, or even ontologies (as we can’t even decide if it is a tool or a science, we must have different ways of thinking about GIS). The question that must be asked is when is a parcel of land part of a river network, and how can this be represented in GIS today?

Smith and Mark outline in their paper that ways of thinking about mountains differ from culture to culture and language to language, this is also true when thinking of GIS.  GIS has a certain way of thinking about real-world phenomena that may differ from aboriginal perception of the same phenomena. Sieber once mentioned that in GIS, a river network is constrained to the line segment that represents it, but for aboriginals, the river might also continue as part of the land over which they portage their canoe.

The same can be said for other geographic phenomena, such as mountains, as in Smith and Mark’s article. Mountains are represented in reality as continuous landforms indicated by a steep elevation gradient, though the commons will identify a single mountain as an object, and even offer it a name.  Aboriginal peoples may attribute spiritual value to a mountain, or be the basis of their world view, as quoted in Smith and Mark. However, in GIS a mountain can be represented as a gridded digital elevation model, a point or a polygon.

Ontologies represent reality for a certain group, and also relates to GIS as a field.

-rsmithlal

The first thing I noticed was that Smith & Mark start with a much more philosophical definition of ontology, as being focused on describing “the constituents of reality…in a systematic way”, as opposed to Kuhn’s definition diving straight into specification of conceptualisations through language which bypasses the question of existence. It was interesting to see the two approaches – one from the domain based ontology and the other from the more holistic approach.

Smith and Mark provide a good overview of ontology, especially primary and secondary theory and the separation of the two. However, their actual suggestions on the future of geospatial ontology is quite scarce, apart from stressing the need for an all encompassing ontology that is general enough to be used in any scenario, but also able to be tweaked as well.

Kuhn on the other hand goes through the interesting process of creating an ontology, and puts more detail into concepts such as affordances. The methodology he goes through is interesting, but still very much dependent upon a textual source. The choice of that source is absolutely crucial – choosing a text in a certain language is probably already resulting in a loss in ‘resolution’ (if that term may be appropriate here), but it is after all, a domain specific ontology, in which case – why translate it to English in the first place (I must note at this point that I am definitely not an expert in the field of ontology).

What I would like to question though is whether or not having separate ontologies is necessarily a big problem. The ontologies used everyday I think are very much a cultural phenomenon in such that they are and should be flexible and malleable according to what humans do and the scale at which we are able to perceive things. In trying to create a formal ontology (an ontology that is unbiased and constant, independent of content), one is probably (as madskiier suggests) limiting the ability to express oneself. The nature of the world is dynamic and human knowledge increasing, so perhaps it is the nature of ontologies to grow, rather than be static. I do agree however that issues of translation and cataloguing are very reliant on ontology, but having separate domain based ontologies should still be the way to go, in order to preserve as much detail as possible.

Finally – what would a formal geographic ontology do for the imagination and communication? It may make the world a slightly more boring place

-Peck

*yes. cold desert environment.

The concept most fascinating to me in Kuhn`s paper was that of grounding which explained that the “claims of any domain theory need to be based on some observation in that domain”. This makes intuitive sense; one must know the domain in question and have some reference material to be able to begin to assemble the domain theory and an accompanying ontology. However, Kuhn refers to the “observation” as being “tangible” which may not always be the case. In Kuhn’s methodology, the basis for information is from a textual source compiled by experts. This assumes experts have the most appropriate grasp of how to assemble the concepts of a domain into some textual reference and then ontology. Yet this neglects two things: public participation and non-tangible reference material.

Public participation would be crucial in cultural studies where experts may not actually be of the culture they study and so may miss some cultural distinctions as a result of their own cultural influences. This reflects a need for the public to participate in defining concepts and objects as they see them and not only as these things are seen by experts or, as Kuhn mentioned, by the knowledge engineers often creating the ontologies.

Closely related to public participation are non-tangible references for a subject such as oral histories of some cultures. The history or stories told may remain relatively stable over time yet the words used to tell a particular history or story may change from telling to telling making it difficult to pin down exactly the meaning of a single concept in the story and to place this in an ontology.

-Outdoor Addict

In his article, Kuhn states that ontology design is performed by knowledge engineers that are not specialized in the domains they are designing ontologies for (Kuhn, 619; emphasis added).  Furthermore, he states that ontology design is carried out in consultation with domain experts through informal interviews, as well as incorporation of documents detailing the ontology requirements and existing databases on the subject of the domain(619).

I feel that these knowledge engineers would be able to create a more in depth and meaningful ontology if they were to actually undertake the grueling and likely expensive task of specializing in the domain that they with to create an new ontology for.  Borrowing from the field of Anthropology, you could think of this concept as a type of Ontological Fieldwork.  The premise of fieldwork is to be able to learn the subtle nuances of a culture, or in this case – a domain, through integration and participation in the life and events of a particular culture, or in our example, domain.  I view this current generation of Knowledge engineers as the equivalent of Armchair Anthropologists, those is in the pre-Boasian era of anthropology would study, and subsequently define, a culture based on explorer, missionary or colonial reports.  This of course lead to a the prevalence of ideas about cultures that were sometimes very far from reality.

In order for the effective and meaningful ontology design, I propose the following five steps to be undertaken by Knowledge Engineers before attempting to define a new ontology for a domain, over a period of at least a year.

1. Designers should identify and chose a mentor from one of the established researchers in the designers domain of interest.
2. Designers should study their mentor’s work, and subsequently explore the work of other established and up-and-coming researchers in the domain of interest.
3. Designers should attend or organize conferences or round tables designed to bring to light a collective picture of what the particularities of the domain of interest.
4. Designers should synthesize their findings and prepare a report, or ethnography, of the domain of interest.
5. Designers should commence work on designing an ontology to represent the domain of interest, taking into consideration nuances of the domain and other findings discovered during domain fieldwork.

In conclusion, I feel that ontology design would benefit from an added level of familiarity with the domain of interest. This would aid in illuminating meaningful nuances that may otherwise be overlooked when researching a domain using conventional, non-committal methods.

– rsmithlal