Informed decision-making about spatial data selection and reliability is a fundamental part of spatial literacy. The proliferation of spatial data on the internet and the large quantity of user-generated data increases the
chances of integrating unreliable data into research. This chapter focuses on evaluating spatial data using the Currency, Reliability, Authority, and Purpose (CRAAP) test with additional focus on the importance of Margins of Error (MOE) in American Community Survey (ACS) data. Reviews have shown that the ACS MOE is often overlooked during research or unreported in academic papers, resulting in misleading or invalid results that significantly impact policy and planning.

The goals of the decision-making process in selecting existing data include: finding information that is most relevant to the research question; gaining a comprehensive understanding of available data and what it represents; comparing similar datasets; planning strategies for processing, integrating, and using data that are not a perfect match for project needs; and, ultimately, determining if a meaningful conclusion can be adequately derived from it.

The CRAAP Test is a flexible and general framework for evaluating information resources in many disciplines and venues. To focus on specific concepts relevant to data capture in GIS using the CRAAP Test, we expand the basic concepts of the test and examine how they can be used to evaluate data sources in GIS.

This activity is associated with a chapter in Spatial Literacy in Public Health: Faculty-Librarian Teaching Collaborations (ACRL, 2024).