A gap currently exists between how data is presented by researchers and how the average person understands data. Thus, although an abundance of good research data is available for free online, it can be difficult to impossible for laypeople to access and make sense of it on their own. The issue of data accessibility and interpretability is consequently preventing open science goals from being reached. Data exploration systems can provide people with limited data expertise an entrance point into complex data and help remedy this problem. This paper presents design principles that can be applied when creating a data exploration software system.