Computers, Society, and Nature

No process in GIS perfect. There are always limitations, many of which can be ignored, while others must at least be acknowledged. The application of the results of an analysis can have a drastic impact on whether errors are ignored, acknowledged, or painstakingly resolved. Consider  the difference between geocoding addresses at the national level to analyze socioeconomic trends. The power of numbers will outweigh the error generated during the processing, but it is enough to acknowledge the limitation. On the other hand, the example of the Enhanced 911 system requires that all addresses be geocoded as precisely as possible for times of emergency.

As a way of increasing the accuracy of geocoding processes, would it be sufficient to input a number of intermediary points as a way to accommodate for the uneven distribution of addresses within a given address segment. It would essentially act as the middle ground between leaving the results entirely up to geocoding and digitizing all addresses manually. After all, why do the corners of blocks have to act as the only reference point? It’s possible that there is an inherent topology that would be lost if this was to be implemented, but I cannot speak to that.

While reading Goldberg et al., one geocoding nightmare kept running through my head. It surprised me that it was not touched on directly. How has Japan addressed the situation? As an OECD country, it likely possesses sufficient GIS infrastructure. If I’m not mistaken, though, house addresses are not based on location so much as time. Within prefectures, addresses are assigned temporally, whereby the oldest structure has a lower value than a newer structure, even if they are immediately adjacent, two structures can have significantly different addresses. Just a thought.

AMac

Geocoding, like many of the concepts that we study in GIScience, is very dependant on the purpose of the process. The act of geocoding is often confused with address matching, which is sometimes correct, however it can also be georeferencing any geographic object and not just postal codes. This implies that the perception of geocoding will affect the ways that we go about doing it.

There are many ways to geocode, as described by Goldberg, Wilson, and Knoblock, and no single one of them is universally correct. Each method uses different algorithms to try to match some identifier to a geographic reference. For example, it might find the length and endpoints of a street and then use a linear interpolation to find the location of a given postal code. The geographical context also bears a great importance in determining which algorithm to use. For example, the method described above may work better in a city with short, rectangular blocks, however it may be less applicable in rural China. These are some of the things that one has to consider when choosing a method of geocoding.

The future of geocoding is perhaps less certain than many of the other GISciences, because as technology and georeferencing becomes more ingrained in our society, the algorithms used to match these objects with a geographic location will become less important. Things like GPS are becoming more and more commonplace in many appliances, however this brings up questions of privacy. Ultimately, the future of geocoding will be a balancing acts of tradeoffs between public acceptance of technology and the development of more powerful and purpose-driven algorithms.

Pointy McPolygon

The article of Roongpiboonsopit and Karimi highlights the fact that ubiquitous mapping and new practices facilitated by the technology allow everybody to geocode data without really knowing what is happening ‘behind’ the geocoder tools (Geocoder.us, MapQuest, Google, MapPoint, and Yahoo!).

Coding is defined in the article as “applying a rule for converting a piece of information into another”. But who controls the rules ? Users have little control over the process since they don’t interact with the geocoding algorithms and the reference databases.

The authors’ analysis shows the importance of questioning the tool used to produce data because errors and uncertainties related to the data produced have an impact on further analysis and decision making. These points relate to the neogeography literature and critics of GIS discussed during the class. More specifically the debates over ethics and practices of ‘open participation’ as a democratization or as an exploitation of user-generated production of surplus of data. In VGI, is geographic information being produced by ‘citizen censors’ or by ‘cognizant individuals’ as mentioned by Andrew Turner (in Wilson and Graham, 2013)? The two different terms underline the question of how aware citizens are when they produce data and geocoding information. This leads to the question of accuracy and how much we need accuracy. It is probably not always important to achieve a perfect accuracy. However, I think that it is crucial to be aware of the lack of accuracy and to make the uncertainties explicit in contrast of leaving it ‘behind’ the tools.

Furthermore, the uneven results generated by the geocoding processes depending on location can also be linked to the debates discussed earlier in class about the digital divide in GIScience. Data are more accurate in urban and suburban areas than in rural areas due to the quality of reference databases in urban areas. Again, I think that there is a need to make these differences more explicit to users or/and producers in order to bridge the gap between experts and amateurs’ production of knowledge.

Wilson, M. W. et M. Graham (2013). Neogeography and volunteered geographic information: a conversation with Michael Goodchild and Andrew Turner. Environment and Planning A, 45(1), 10-18.

S_Ram

Goldberg et al. provides an overview of geocoding and touches on several aspects that relate to GISci. For instance, the authors elaborate on how the evolution of the reference dataset has allowed for more complex and resourceful queries to geocode postal codes, landmarks, buildings and so on. The underlying cause of the shift has been attributed to the reference dataset. Not only have datasets become more complex, the increasing technological power has paved the way for intricate matching algorithms, and interpolation processes. Perhaps the next shift within the geocoding realm will be the increasing integration of context aware technologies. Now that people are progressively contributing geospatial content, issues of cost, money and time are significantly reduced. The authors suggest that once GPS technology is accurate (and affordable) enough to be equipped in all mobile phones, postal codes may become obsolete. But instead of rendering postal addresses obsolete, are we at the moment where LBS and AR can add to the accuracy of reference files, especially if volunteered geographic information is on the rise? I’m curious to see how the new ways in which data is being provided/created (in large amounts, provided by many people) intersects with geocoding today. Now that we’ve seen an evolution in the data models and algorithm complexities that contribute to geocoding, I can imagine that volunteered geographic information from a large number of people can be a new method to geocode but ultimately bringing with it a new set of complexities in data accuracy and reliability issues.

-tranv

I think Geocoding is one of the most central issues in GIS (science and systems) and yet is probably one of the less well understood issues for lay people and non-experts who use spatial data (along with map projections). As the authors mentioned, there has been research in public health and epidemiology on the accuracy of street addresses. In fact, a PhD student in my lab lead a research project on this very issue here in Montreal (Zinszer et al. 2010, cited below). The team found that address errors were present in about 10% of public health records, the same ones that were used to perform spatial analysis to look for space-time clustering of campylobacteriosis in Montreal. Geocoding has all kinds of repercussions in public health research; while errors are an issue, anyone who performs epidemiological research with administrative databases are prepared to have some amount of error. However, when the error becomes differential with respect to some factor of interest, this can result in a huge problem (bias). For example, as mentioned in the discussion, the accuracy of geocoding was differential between urban, suburban, and rural areas. There is a lot of spatial epi research done with the urban-rural health divide in mind, and differential accuracy in geocoded addresses like this could pose a huge problem. I think papers like this one by Roongpiboonsopit and Karimi are very useful for people outside of GIS because they help us understand the scope of the issue. I also think Roongpiboonsopit is a super awesome name.

Zinszer K, Jauvin C, Verma A, Bedard L, Allard R, Schwartzman K, de Montigny L, Charland K, Buckeridge DL (2010). Residential address errors in public health surveillance data: A description and analysis of the impact on geocoding. Spatial and Spatio-temporal Epidemiology. 1(2-3): 163-168.

-Kathryn

Before I read this paper, I was not very familiar with the concept of location based services. There are of course lots of commercial uses of geographic information but this direct discussion of spatial information translating directly into business is very interesting and not something I had thought about. This subject seems like another interesting area that intersects with the topics we have already discussed, such as augmented reality, where location can be used via say, GPS, and various software and hardware to augment individuals surroundings that could direct effect sales and be used for marketing. As mentioned in the paper, privacy is of course another theme that has surfaced often in class and again is an issue here, but there is also a lot of potential for creative uses of spatial information in ways that individuals would appreciate. Looking forward to seeing how others perceive the utility of LBS.

-Kathryn

Even though this article is not new, it seems like the field has not advanced incredibly since it was written. Being able to efficiently and effectively store, retrieve and particularly visualize the temporal aspects of data in GIS continues to be a major limitation of spatial analysis. In spatial statistics, models that account for space-time variation rather than static spatial information are usually just logical extensions of the same spatial models. But spatial stats doesn’t have to deal with the same data model issues that GIScience has to address, nor does it have to attempt the visualization aspects that GISystems are expected to handle. I am interested in seeing what the current state of the art is, in case there have been major advanced that I somehow missed since my masters.

-Kathryn

I feel like the LBS development are focused on marketing purposes and privacy issues might be underestimated in this domain. Profit is a major interest and priority before individual’s privacy concerns. The article of Rao and Minakakis shows that the way that LBS can be profitable and worth the developments in this field is by gathering information, conducting data mining and ‘business intelligence activities’ to extensively understand consumer’s profiles and shopping habits. The authors recognize that there are ethical and privacy issues related to the use and disclosure of information to third parties but do not engage with this topic. I’m wondering if developing business models on one side and leaving the privacy issues to privacy advocates on the other side is a good approach in the development of the technologies and LBS…

S_Ram