Module 8: Data Collection and Acquisition

Essential questions 

What experimental conditions are applied to the subject of studies?

How to select a representative group for experimental work?

Data collection is one of the key steps in experimental research. It is a process of gathering, recording and systemic analysis of the experimental outcomes that can be used to address research questions, test hypothesis, or compare the results.

Integrity of the research depends largely on the accurate data recording by the appropriately calibrated instruments that are properly used.

If the data were collected improperly, the research questions cannot be addressed adequately and are not reproducible. This may be misleading to other researchers and can impede the ability to solve the research problem in hands. In the extreme cases, inappropriate data collection can be harmful to the research subjects or researchers themselves.

Data integrity can be compromised by systemic or random errors, or, in the extreme cases, by deliberate falsifications. The two main approaches to ensure data integrity are:

• Quality assurance – that includes all appropriate activities prior to the beginning of data collection
• Quality control – that takes place during and after data collection in experimental research.

Data collection errors can be avoided by following the proper experimental protocol and checking for possible errors in individual data items. Systemic errors can be due to the problems with instrument calibration, experimental setup, or study design.

Digitization of research data can be the source of errors, e.g., by introducing spurious information into large data sets that are not carefully examined. Digital data can be easily distorted and, in the worst-case scenario, fraudulently manipulated, misrepresented, or even fabricated.

Federal regulations that were developed by the Office of Science and Technology Policy, identify scientific misconduct as fabrication, falsification, or plagiarism of research results (2).

Suggested readings

Whitney C.W., Lind B.K., Wahl P.W. (1998). Quality assurance and quality control in longitudinal studies. Epidemiologic Reviews, 20(1): 71-80.

Office of Science and Technology Policy, Federal Policy on Research Misconduct. Available at http://ori.dhhs.gov/education/products/RCRintro/c02/b1c2.html.