Prior to reading Langran and Chrisman’s article, my understanding of temporal geographic information was limited to time lapse videos of static snapshots, which visually display change. After reading the article, however, I was able to better comprehend the importance of temporal models that enable direct comparisons of how objects are changing. Models such as these allow for a greater understanding of how change is occurring at specific times, whereas snapshots seem to merely illustrate the general notion of change.
Outdoor Addict questions how decisions are made as to what constitutes an event and I think this is a valid concern. In abiding by data storage limitations, for example, we may deem a change to be irrelevant and discard it. However, what if this change is considered to be important at a future date? Perhaps the idea of examining snapshots is still holding me back—certain technologies that allow changes to be constantly tracked might need to be considered to a greater degree. In thinking about this, a parallel may lie in a Geography 407 class discussion, where dialogue revolved around sensors designed to continually track animals in forests. In this case, every motion that is detected is recorded, while durations of no motion are not. Can anyone else think of similar examples?
From the motion detection example, yet another concern arises—there will inevitably be information that sensors cannot detect. In addition, relating to the lecture on scale, the issue is not merely about deciding what objects to include, as previously mentioned, but it is also about determining what level of detail is appropriate. In other words, there is such a thing as too much information. The easy way out would be to yet again rely on the “future technological advances will render this concern irrelevant,” argument, but due to the inescapability of uncertainty, I posit that context and judgement are two of the most important considerations.
Lastly, in answering CimateNYC’s question about the distinction between real time and database time with regards to streaming data, Madskiier_JWong states that information may be incorrect or incomplete and in need of updating at a future date. I would like to add to this that technical issues often arise when dealing with streaming of data. For example, glitches in communication systems or backlogs of data can result in differences between real time and database time. This type of information is valuable, however, as it enables insight into how systems can be better designed.