Planning A Data Jam
Data Jams are collaborative workshops for research project teams to engage in the qualitative data analysis process. These workshops build capacity in qualitative data analysis while providing a space for teams to advance their research/evaluation project through rigorous team-based analysis.
We typically facilitate Data Jams for researchers or evaluators who have collected survey or interview data and don’t quite know how to get their team started with the analysis. Data Jams help orient the team to the data, and they help the team to create a shared understanding of the analysis goal and analysis approach. Through this, Data Jams are setting a foundation for future analysis.
Preparation is crucial for the success of a Data Jam. Make sure to work with the individual who owns the data (such as a principal investigator, lead evaluator, or educational program manager) ahead of the Data Jam. The key task here is to narrow down a question for the Data Jam, the scope of the data to be analyzed, and the product that analysts are tasked with producing.
Keep in mind that Data Jams are capacity building; you should not expect to be “done” with analysis as a result of a Data Jam. Rather, the Data Jam is a training and event that will help a team in setting up and aligning collaborative analysis.
In preparation for the Data Jam, the project team should establish the following:
Roles
Data Jam organizer
Plans event, manages communications and day-of logistics
Data owner
Owns data; will clean/prepare/anonymize data for the Data Jam
Facilitator
Facilitates the Data Jam experience (e.g., leads discussions, manages agenda)
Software/methods expert
Prepares analysis files, introduces software, provides technical support
Note: One person may take on more than one of the above roles (e.g., the organizer may also be the software/methods expert)
Main research question and analysis question(s) to focus on
Typically the research question is larger in scope, and the analysis questions are narrower. When planning a Data Jam, make sure to clarify the question scope with the data owner. An overly broad question will prevent your teams from creating a meaninful analysis product.
Example research question
What are the challenges and supports our community experiences?
Example analysis questions
What types of health concerns are described by community members? What types of financial concerns are described by community members?
Data scope
When planning a Data Jam, make sure to clarify the data scope with the data owner. An overly broad question will prevent your teams from creating a meaningful analysis product. How many interviews or surveys will you explore in your Data Jam? This is likely only a sample of your project’s dataset.
Anticipated end product
What output will be produced from the Data Jam?
Narrowing and clarifying this product is crucial for the success of a data jam — your teams will need to know what they are working towards.
Example end product
Established coding scheme for our research question with well-defined code memos and subcode memos.
The project team should coordinate the day-of logistics for hosting an in-person Data Jam:
Plan to work in groups of 2–3. At least one participant should be familiar with MAXQDA and serve as facilitator.
Consider whether available spaces have enough displays for group work and a larger display for demonstrations. Plan to have additional display cables or charging cables as needed.
If planning a virtual or hybrid Data Jam, agree on the platform (e.g., Zoom, Teams).
We recommend the following timeline when planning your Data Jam:
- Identify roles
- Contact and schedule Data Jam dates with potential participants
- Confirm room/space reservations
- Identify research and analysis questions
- Prepare data for analysis (cleaning, anonymizing, etc.)
- Email registrants with Data Jam details and required reading
- Identify any equipment required for the reserved room/space
Create and share a cloud-based folder (e.g., Google Drive, Box, etc.) for the Data Jam:
- Share the agenda
- Create a shared document for the research and the analysis questions
- Make accessible the dataset that will be used for the Data Jam
This information is also available in a version specifically designed for print