Research studies are largely based on data, and how you manage it also plays a role in determining the quality of result you obtain. However, at the PhD level, you have to deal with extensive datasets and participant groups. So, managing data will not be easy. You have to take help of certain techniques and tools to ensure that you do not lose any important data, or get confounded with frivolous data.
First it is important to understand the scope of data. For any research, data is not just limited to numerical records; it also encompasses information collected through observation, experimentation, mapping, measurements, images, etc.
Some steps that must be followed for proper data management and documentation are:
• Data Entry: it is the first stage of recording data for your report. Every figure is entered carefully in tables and tools used for data entry include excel sheets, SPSS modules, etc. This step becomes complicated when there are multiple people working on the same project, or when data is being collected from various locations. In some cases, transcription or logging may be needed.
• Data Cleansing: once you have entered all the data, you have to ensure that there are no missing data. Also, all misleading, confusing and meaningless data has to be removed from your records, so that it does not affect the research results.
• Data Backup: taking a reliable back up of the data is essential so that you don’t lose critical information in middle of research. However, while taking a backup, pay attention to security of sensitive or confidential data.
• Data Documentation: the process of documentation starts with labeling and coding of data. You have to explain the coding and classification to enable easy understanding by readers. There can be some data that is derived after basic analysis or experimentation. All such data must be classified separately and some information provided about them.
• Double check: it is best if data is checked by different persons. It eliminates chances of any lapse or mistake in recording and coding of data.
To be certain that you make the best use of data, it is advisable to take help from professional data management experts and statisticians.