What does ordinal data allow researchers to do?

Ordinal data is a type of categorical data where the categories have a defined order or ranking. This allows researchers to not only classify data into distinct categories but also to establish a hierarchy among them. For instance, in a survey where respondents rate their satisfaction level as "satisfied," "neutral," or "dissatisfied," researchers can rank these responses to understand which category is regarded more favorably. Therefore, ordinal data is specifically valuable for conveying information about relative positions or performances among different groups or items.

The other options, while relevant in data analysis or GIS contexts, do not pertain specifically to the properties of ordinal data. Determining exact values typically refers to interval or ratio data, which allows for precise measurements and calculations. Analyzing spatial relationships is often related to spatial data types and metrics, not specifically to ordinal rankings. Lastly, visualizing in 3D relates more to the representation of data and spatial features and is not a function unique to ordinal data. Thus, the core utility of ordinal data lies in its ability to rank data points effectively.