Session 3 - Analyze and Collaborate

Interoperable: The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. (Wilkinson, et al., 2016)

Description

Once the data creation/collection stage has been completed (at least, initially), the data must be analyzed to answer the research question(s) and/or provide additional information for research – whether as a report, visualization, or in some tabular format, to name a few examples. In this stage, we should also consider the best method(s) of documenting the analysis and the steps taken before the research data is ready for analysis. This documentation is not only important for future use and reproducibility but also for sharing out with others in your research group, if working collaboratively.

Questions

  • From “7 Key Ethical Considerations”:
    • Am I approaching this analysis with objectivity, and have I considered all potential sources of bias?
    • Can other researchers reproduce my results based on the information I’ve provided?
  • From Rawson and Munoz (2016) “Against Cleaning”:
    • With those communities [impacted by the data] in mind and even in dialogue, we would ask, what are the concepts that structure this data?
    • And how can this data, structured in this way, point to other people’s data?
  • What distinguishes your “messy” data from “clean” data? Has that difference been documented?
  • Can the “messy” data you’ve encountered be seen in a new way?

Resources

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