When it comes to the quality of geospatial data, one of the questions arising is how credible and reliable these data are in terms of representing the real world. The greater the difference, the poorer the quality of data and, consequently, the lower the actual value of the data. Quality is illustrated by several criteria, including geometric accuracy and geometric precision, but these two terms need to be distinguished from one another.
In the fields of science, engineering and statistics, accuracy is the degree of closeness of measurements/calculations of a quantity to that quantity’s actual (true) value. Accuracy signifies how reliable the measured or calculated quantity is. In relation to geospatial data, accuracy is the criterion which tells us to what extent the data, e.g. in the plan (e.g. the geographical position), match the values in the real world.
Precision, on the other hand, is the degree to which repeated measurements or calculations show the same or similar results. Precision therefore signifies the degree to which the same or similar result of the measured or calculated quantity can be reproduced.
Calculation or measurement results can be accurate but not precise, they can be precise but not accurate, they can be both, or simultaneously inaccurate and imprecise. The result is valid if it is both accurate and precise.
A target can serve as an example to clarify the difference between accuracy and precision. For this purpose, the measurements are arrows being shot into the target. Accuracy describes how close to the centre of the target the arrows have landed. The arrows closer to the bullseye are more accurate. Precision, however, denotes how close in relation to one another the arrows have landed in the target. If all arrows are close together, the bunch is precise as all of the arrows are gathered at (nearly) the same spot. This spot is not necessarily close to the bullseye, i.e. the shooting was precise, but not accurate.