Data collection is the process of gathering and measuring
information on variables of interest, in an established systematic
fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes. The data collection component of research is common to all fields of study including physical and social sciences,
humanities, business, etc. While methods vary by discipline, the
emphasis on ensuring accurate and honest collection remains the same.
The goal for all data collection is to capture quality evidence that
then translates to rich data analysis and allows the building of a
convincing and credible answer to questions that have been posed.
Regardless of the field of study or preference for defining data (quantitative, qualitative), accurate data collection is essential to maintaining the integrity of research. Both the selection of appropriate data collection instruments (existing, modified, or newly developed) and clearly delineated instructions for their correct use reduce the likelihood of errors occurring.
A formal data collection process is necessary as it ensures that data gathered are both defined and accurate and that subsequent decisions based on arguments embodied in the findings are valid.[2] The process provides both a baseline from which to measure and in certain cases a target on what to improve.
Consequences from improperly collected data include:
Distorted findings result in wasted resources and can mislead other researchers to pursue fruitless avenues of investigation. This compromises decisions for public policy, and causes harm to human participants and animal subjects.
While the degree of impact from faulty data collection may vary by discipline and the nature of investigation, there is the potential to cause disproportionate harm when these research results are used to support public policy recommendations.[3]
Regardless of the field of study or preference for defining data (quantitative, qualitative), accurate data collection is essential to maintaining the integrity of research. Both the selection of appropriate data collection instruments (existing, modified, or newly developed) and clearly delineated instructions for their correct use reduce the likelihood of errors occurring.
A formal data collection process is necessary as it ensures that data gathered are both defined and accurate and that subsequent decisions based on arguments embodied in the findings are valid.[2] The process provides both a baseline from which to measure and in certain cases a target on what to improve.
Consequences from improperly collected data include:
- Inability to answer research questions accurately.
- Inability to repeat and validate the study.
Distorted findings result in wasted resources and can mislead other researchers to pursue fruitless avenues of investigation. This compromises decisions for public policy, and causes harm to human participants and animal subjects.
While the degree of impact from faulty data collection may vary by discipline and the nature of investigation, there is the potential to cause disproportionate harm when these research results are used to support public policy recommendations.[3]
See also
 |
Wikimedia Commons has media related to Data collection. |
- Scientific data archiving
- Data management
- Experiment
- Observational study
- Sampling (statistics)
- Statistical survey
- Survey data collection
References
- Lescroël, A. L.; Ballard, G.; Grémillet, D.; Authier, M.; Ainley, D. G. (2014). "Antarctic Climate Change: Extreme Events Disrupt Plastic Phenotypic Response in Adélie Penguins". In Descamps, Sébastien. PLoS ONE 9: e85291. doi:10.1371/journal.pone.0085291.
- Data Collection and Analysis By Dr. Roger Sapsford, Victor Jupp ISBN 0-7619-5046-X
- Weimer, J. (ed.) (1995). Research Techniques in Human Engineering. Englewood Cliffs, NJ: Prentice Hall ISBN 0-13-097072-7
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
No comments:
Post a Comment