5 Easy Steps to Good Data Management

1-This week’s lecture states, “A qualitative study has no hypotheses, and the research question is usually very broad. Questions will evolve as the study progresses. Therefore, the researcher looks for data to form impressions; this type of research is not measurable” (Grand Canyon University, 2012.). To some people such as myself, not having a definite “plan” and or question as to what will be studied can be stressful. Qualitative data comes as you go and begin your research. Qualitative data is not so much numbers, but interviews and pictures. This can leave the researcher with a lot of data to sort through and may now know how to begin organizing. One way is to highlight certain information with a different color highlighter so you know certain data is a different color or even using different color paper. Even separating data into different piles. Different things will work for different people. According to an article in Johns Hopkins Bloomberg School of Public Health:

5 Easy Steps to Good Data Management

  • Choose and follow a clear file naming system
  • Develop a data tracking system
  • Establish and document transcription/translation procedures
  • Establish quality control procedures
  • Establish a Realistic Timeline

Reference:

Grand Canyon University. 2012. Research Ethics and Research Process Components: Problem, Question and Literature Review. Retrieved from https://lc-ugrad3.gcu.edu/learningPlatform/user/users.html?operation=loggedIn#/learningPlatform/loudBooks/loudbooks.html?viewPage=current&operation=innerPage&currentTopicname=Research%20Ethics%20and%20Evaluating%20Qualitative%20Research&topicMaterialId=c62190ed-c404-444c-bc29-954269d5bbe5&contentId=f614cda6-1cf4-4875-b0b9-82cdd77d5c34&

John Hopkins University. 2018. Managing your Qualitative Data: 5 easy steps. Retrieved from http://ocw.jhsph.edu/courses/qualitativedataanalysis/PDFs/Session2.pdf

 

 

2-Having a plan for organizing the data before all of the data has been obtained is going to make the data that is collected far less overwhelming to organize later. The organization process needs to be done in a manner that allows there to be an element of openness to the data that is collected while also have an element of structure. Questions asked to participants should be clear and should imply that concise information be written, but that all questions are answered fully (Johnson et al., 2010). There is an important balance between obtaining enough information and not being inundated with information that is unnecessary that must later be sifted through in order to find something useful. Software will also be helpful with the organization process in which everything is divided into categories and the information can be used in both a quantitative and qualitative manner. Organization is something to be maintained throughout a study (Talanquer, 2014).

References

Johnson, B. D., Dunlap, E., & Benoit, E. (2010). Organizing “mountains of words” for data analysis, both qualitative and quantitative. Substance Use & Misuse , 45 (5), 648-670. doi:10.3109/10826081003594757

Talanquer, V. (2014). Using qualitative analysis software to facilitate qualitative data analysis. ACS Symposium Series , 83-95. doi:10.1021/bk-2014-1166.ch005

 

3-Labeling the themes into categories is going to be an important method for later quantifying the qualitative data into something that can be used to show a pattern. Entering the different categories into software and ensuring that they are going to be easily used and referenced later is important. There are software available as a tally system for the information that can allow one to explain what the different respondents agreed and disagreed upon (Johnson et al., 2010). For example, if there are three respondents who have a similar symptom, one respondent with a unique symptom, and eight respondents who have a different symptom, then that can be quantified and tallied based on the respondents experiences. Having enough information is going to be just as important as not getting superfluous information, so it will be necessary to be clear about exactly what information is needed before questioning the respondents so that nothing is missed (Talanquer, 2014).

References

Johnson, B. D., Dunlap, E., & Benoit, E. (2010). Organizing “mountains of words” for data analysis, both qualitative and quantitative. Substance Use & Misuse , 45 (5), 648-670. doi:10.3109/10826081003594757

Talanquer, V. (2014). Using qualitative analysis software to facilitate qualitative data analysis. ACS Symposium Series , 83-95. doi:10.1021/bk-2014-1166.ch005

 

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