Informational Techniques for Urban Sciences

Introduction

Evolution of a city is determined and influenced by different factors. The characteristics of these factors may also have spatio-temporal complexities. That means the characteristics of a certain attribute may change with time. Consequently, a projection made on the basis of that attribute needs to be changed. And the elements which are responsible for variation in the characteristics of those attributes should also be considered for the investigation related to urban sciences. Therefore, we can make an inference from the above discussion that characterization of an urban event needs identification of different attributes which can influence its behavior. In addition, there is an absolute necessity to understand the contexts in which the behavior of these attributes may change. So we can say that characterization of an urban event in the domain of urban science needs to be categorized primarily into two stages. First, identification of the attributes which can trigger or influence the behavior of an urban event. Second, identification of the factors or contexts which can influence the characteristics of the attributes. That means, we primarily need data at two stages. In the first stage, we would be focusing on collection of the data related to different attributes which are responsible for shaping the characteristics of an urban event. In the second stage, we need to collect data about the internal or external factors which can influence the characteristics of the primary attributes. It also needs to be understood that collection of data about the internal or external factors should also be done in two different stages as in the case of collection of data related to primary attributes. That means there is a possibility that an array of data has to be collected for different attributes of an urban system. In addition, at this stage of discussion, it also needs to be highlighted that even historical data has huge significance in urban studies. The historical data is used to understand the behavior of a city in different contexts. That further can be used for generation of future urban scenarios. It means that the data of different dimensions and different time periods has huge importance in urban studies. However, a huge amount of data is generated for such comprehensive study of an urban event. It also needs to be understood that such comprehensive study of an urban event or say, an urban system is needed as it would help to understand the complex relationship of attributes with each other in a clearer way. Otherwise, we would not be able to understand the primary principle which derives the changes in the behavior of an urban system. But, as mentioned earlier that a huge amount of data is generated in this process. In addition, it is not about the amount of data which may become a problem for effective analysis; the main problem is to properly relate the data with each other. Otherwise, there may be a situation where data related to different attributes of the urban system are collected, but these data are not studied in sync with each other. In that case, there is a huge possibility that the study would end with no conclusive results which are practically relevant. If that happens, then we can say, despite having the data, we failed to represent the actual characteristics of an urban event, or say an urban system.