Chapter 5:
This chapter introduces another different form that ArcGIS Web can take, called ArcGIS enterprise, which has been described to be a more private platform of ArcGIS Online. I have noticed that there are key differences between ArcGIS Online and ArcGIS enterprise, such as the database that they run on. ArcGIS online’s data is kept on an online ESRI cloud, while ArcGiS enterprise is maintained on a more user-managed structure. This type of format can be used for organizations, such as governmental programs, that require a non-public cloud or no internet connections. I find it interesting that there is also a hybrid version of GIS that is offered as well that provides personal layers while continuing access to ArcGIS online layers. Through the chapter I had also learned that ArcGIS enterprise is also an on premise tool, which makes sense when considering the lack of internet accessibility that the platform provides. Additionally, it runs on a geospatial content management system called Enterprise portal, which helps to create different types of hosted layers, host web-mapping apps, search for GIS content, and manage your organization’s utility services. There is also an ArcGIS server that helps to host different types of web services, which is quite cool. For ArcGIS online and ArcGIS enterprise alike, there is a way for organizations to collaborate by sharing content in groups. I believe that I remember reading about the hierarchical sharing system within one of the earlier chapters. The chapter had also touched upon visual data aspects, such as the vector and raster layers.
Chapter 6:
Chapter 6 discusses the concept of real-time ArcGIS, which is intended for data that changes on a regular basis and needs to be continuously updated. It makes sense that this platform has been developed as more advancements get created in favor of electronic field data collection, as a database must be created to compensate for it. One type of data type that is housed on real-time ArcGIS is spatiotemporal data, which is data generated from sensors or simulated models, which can consistently generate more data which needs to be entered into the dataset. Spatiotemporal data seems to collect data on factors that change over time, such as transportational objects, events occurring, or environmental changes. That type of data can be further separated into two types, point in time and duration of time. The difference is that point in time observes collective events that occur and when they happen, while the duration of time looks more at the whole start to finish of a continuous event. It also delves into Iot, which is a network of objects attached to sensors that can exchange data at a regular rate. This seems to primarily refer to technological data such as planes and other automobiles. It was interesting to see how much technology tracking is integrated into different aspects of my life that I don’t usually think about. It leaves me wondering what other types of data are being collected from my daily activities.
Applications:
A possible idea that could be pulled from chapter 5 could be to test water quality at different locations of a body of water, which wouldn’t necessarily need on sight GIS data management, as water testing may need to occur within a lab. From within that lab, data could be analysed and entered into a GIS database, in order to visualize the areas in which different types of water quality traits differ, and their adjacence to urban areas. I found coming up with an application from chapter 6 to be quite smooth, as it is a type of data that can have such a wide variety of uses. One of the possible applications could be to collect data based on how many cars pass through areas with notably high deer populations, possibly combining another dataset containing deer sightings in order to form a more full picture. The purpose of this could be to understand which areas infrastructure designers should invest in highway fences, in order to lessen the rate at which deer-related crashes occur.