Older researchers like I am are likely to have numerous boxes or filing cabinets filled with records from prior research projects. These boxes or file folders include printed transcripts, fieldnotes, or drafts of manuscripts writing up findings, and copies of published articles relative to the topic. For scholars in 2022, however, records are likely to be stored electronically in folders on hard drives. In this blog post, I’ll talk about some of the steps that we can take to develop an organizational system to keep track of records.
Establish a filing structure at the beginning of a project.
There is no one right way to store and organize materials. The ability to store files electronically can be a tremendous help to researchers, though, since this enables searches of a large volume of files, and speedy re-arrangement of files in chronological or alphabetical order. Some thought should be given to whether a project merits the inclusion of different folders on the basis of data source (e.g., interviews, field notes, documents, consent forms, etc.), chronology (e.g., phase 1, phase 2, and phase 3 of a study), or case (e.g., a particular context or participant).
Protect the confidentiality of data.
Ensuring that data remains confidential will require that any files that include personal names that identify participants of a project are password protected. I find it a useful strategy to anonymize transcriptions at the point of transcription. This might include the removal of any contextual information that might reveal a participant’s identity (e.g., deletion of other individuals or omission and/or anonymization of place names).
Protect data by regularly backing up data on an external storage device.
Be sure to protect yourself against theft of your data (yes, I’ve seen this occur when a laptop was stolen from a vehicle), or a computer crash (not a matter of if, but when!) by regularly scheduled backups of your project.
Use a Qualitative Data Analysis Software (QDAS) program.
Various software applications such as NVivo, MaxQDA, Atlas.ti and Dedoose provide organizational systems and tools to not only manage large amounts of data but to analyze and write up reports. For example, these sorts of programs provide “memo” tools that enable researchers to link comments (in addition to codes) directly to particular data sources and assist with not only making connections among data sources but keeping track of these. These QDAS programs do not necessarily speed up the process of analyzing qualitative data. They do make possible storage of project data in one place, however. Time-stamping tools within these programs support researchers’ note-taking concerning decision-making and can help with keeping track of the research process. QDAS programs are not for everyone, however. I know researchers who prefer to work with printed copies of their data sources. If that’s the case for you, some form of paper filing structure will assist you to locate the materials you need efficiently.
One researcher’s organizational strategy is unlikely to look the same as another’s.
The key thing to remember in deciding on how to develop a structure for organizing a project has to do with what works most effectively. Identify the organizational strategies that work for you. By keeping track of research data, research literature, and the research process in an organized way, researchers will be better situated to come back to a project should their work be interrupted by other life events. The organizational structure selected should support systematic analysis and interpretation of a data set, whatever analytic approach is employed. One strategy that I have found helpful for students is to write an inventory of their data sets as they work on analysis and interpretation of a project’s data. These are the questions I ask students to respond to:
• Research Purpose
• Research Questions
• Definition of Terms
Study design and methods
• IRB procedures
• Participants (how many? How were they recruited? What criteria were used for sampling?)
• Duration of study (when was the study conducted, and what was the duration of the study?)
• Data Description (how much data do you have?)
• transcripts of interviews/video (how many pages?)
• documents, online, or archival material, artifacts (list what the documents are? how many?)
• field notes (condensed, expanded; how many pages?)
• audio/visual material
• Research context: Describe the context of your study and settings as appropriate
• Chart with a summary of data (no. of pages, date of collection)
As you can see from these questions, this information is typically included in research design and methods statements in published articles, so can provide a helpful overview when writing up the findings of a study.