I’ve been thinking about this for a while now, but not really got a handle until recently on how to progress this area of research forward. When examining a PhD thesis not long ago, some thoughts on Geo-visualisation specifically and Information Visualisation in general, and the relationship with ASKS (Anomalous States of Knowledge) were brought to the fore, particularly with respect the underlying task. My thoughts were brought into sharper focus when attending a Geo-visualisation tutorial run though more recently.
Why? Lets think about ASKS in terms of information retrieval. A user has a certain level of knowledge when approaching search, which will have an impact on how well they will proceed with the search process and how long it will take them. Lets say we ask two people to search for the effect on hydrogen atoms of the heat generated internally by the Sun. One person is a scientist the other is just someone off the street with a weak knowledge of science. Its clear who will do better in the search process here (no prizes for guessing who).
The task itself has an impact on the search process. A Professor who searches for articles on ‘the effect on hydrogen atoms of the heat generated internally by the Sun’ for background knowledge to their own research will probably be looking for a very different set of documents to a student who wants to write an essay on the same subject, set as coursework by the professor. The student will want more articles with fundamental principles in it than the professor, who is more likely to be interested in cutting edge research.
The information source and the users understanding of it play a very important role on the search process. Our professor above will have a much better handle on the sources than their student.
Ability to understand and use the software is yet another component. How complex is the interface? How well does the user understanding Boolean logic operators to carry out sophisticated searching? A case were an information scientists with knowledge of understanding users information needs and expertise in turning these needs into a search will have a distinct advantage here, particularly if they have been using the software for a while. The students I teach often do these roles, as ‘search intermediaries’.
OK, were are we going with this? What’s the link to information visualisation/Geo- visualisation?
First lets deal with the knowledge which a user brings to the visualisation process. It’s clear that the process will be undertaken with a certain amount of prior knowledge of the domain, whether its visualising maps or multi-dimensional data.
The task assigned has an impact. A professional geographer will be doing very different things to a student who is learning about the process of Geo-visualisation. The profession geographer will be perhaps trying to learn new things in the visualisation process. The student however, is more likely to be learning about things which are well known, and which an educator (perhaps the professional geographer) can help them with. This really came out in the PhD I examined.
The source data as an impact. Our profession geographer may well be working with more complex underlying data than our student trying to understand Geo-visualisation. You’ll be using different data for the different tasks I think. This really came out in the PhD I examined.
The software used has an impact. A Geo-visualisation expert with expertise in the field will have abilities in using the software, which could put them in the kind of role described above in IR – as some kind of ‘visualisation intermediary’. This stuck me in the Geo-visualisation tutorial I attended.
I think there are similarities between information visualisation and information retrieval that I think are worth investigation, in particularly the many information seeking models which are around e.g. Wilson, Ellis etc. Seems to me that IF is a seeking process, and we might be able understand it a little better if we apply these models. I use ASKS above, but information retrieval is not just about problem solving.