ABSTRACT
This chapter presents a scientific approach to data collection, its rationale and relevance, how and why data are collected, potential gaps in the data collection, and the accompanying processing needed to ensure high quality and accuracy. This chapter introduces learners to how we make scientific observations and take measurements. This is an intentional systematic process of acquiring data and knowledge about phenomena of interest. It is done either directly through the use of our human senses or by recording information using tools and instruments. At the present time, science and technology have become a way of life whereby on a daily basis we are using mobile devices or sensors (e.g., citizen sensor) to measure our locations, daily activities, building heights, or body weights. The data are measured using a specific metric that consists of a nonnumeric or numeric attribute with a unit. Our curiosity to learn and gain knowledge about our environment inspires us to ask specific research questions, formulate hypotheses, design experiments and ensure proper collection of primary data, and validate or reject the hypothesis using observations. Furthermore, this chapter discusses scientific concepts, especially focusing on the hypothesis-driven process through which we observe, collect, and analyze spatial data. Four scales of measurement and two main scientific approaches for data collection and sampling are presented, as well as hands-on knowledge and skills development for data processing.
