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Edward Flagg
Department of Physics and Astronomy
Eberly College of Arts and Sciences
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Stages of a Research Project

A research project will progress through many stages from its conception through publishing the results. Below is a mostly ordered list of the stages of an experimental research project in our laboratory. Sometimes these stages will be done in a different order, or they may repeat, or they may blend into one another. Different fields of physics and different types of research (i.e., computational or theoretical) will likely have a different order or different stages. If you are part of our research group, you can use the outline below to evaluate and plan your projects. 

  1. Conception/inspiration
  2. Development/feasibility study
    1. Literature review
    2. Simulations
  3. Experimental design: Outline both the measurements to be done and the equipment that is necessary to do them.
  4. Experimental setup, calibration, tests, troubleshooting: Construct and arrange the experimental equipment to do the planned measurements. This can take the majority of the time spent on an experiment.
  5. Preliminary steps
    1. Preliminary experimental measurements: Figure out how to do the measurements. This may require going back to steps 3 and 4 a few times.
    2. Preliminary data analysis: Figure out how to analyze the raw data. This may require going back to steps 3 and 4 a few times.
    3. Preliminary writing, essay-style: Start writing the paper because "writing is thinking". This is a first attempt at explaining the experiment and results. Use it to see what is missing, what additional data to take, and what additional analyses to do. This should continue throughout the rest of the project.
  6. Pipeline development: This is an outgrowth of the preliminary steps above.
    1. Experimental pipeline development: We often need to take all our data from one quantum dot (QD), and a given QD can't be easily re-found if the sample is changed. The experimental pipeline is an efficient method to collect all the data in a short amount of time. It takes time and effort to develop the procedures and programs to enable that.
    2. Raw data analysis pipeline development: To ensure the data being collected is valid, it needs to be analyzed immediately so a human can evaluate it for validity. The analysis pipeline is code that raw data can be put through immediately after collection, and which produces plots and figures that enable human evaluation. Similar to the experimental pipeline, it takes time and effort to develop the analysis method and code for this task.
  7. Experimental measurements directly into raw data analysis pipeline: This is when the data that will be used in the final analysis is recorded. This setup can take very little time if the experimental and analysis pipelines are well functioning. If the pipelines are not well functioning, then this step might be performed incorrectly and need to be repeated after redevelopment of the pipelines.
  8. Analysis of processed data: If the preliminary writing and data analysis were done well, then this step can be straightforward. If it is not straightforward, then we may need to return to the preliminary steps again.
  9. Writing: The order of writing is different from the order of the eventual paper. The order below starts with the easiest parts to write and ends with the hardest.
    1. Experimental setup/methods: Equipment (figures); kinds of measurements (archetypal examples); data analysis methods. As the graduate student who did the experiment, this section is the easiest to write because you just describe what you did.
    2. Data presentation/analysis: It is sometimes necessary to present all of the raw data, but sometimes the archetypal examples in the previous section are sufficient.
    3. Results and discussion: Plots and models of information extracted from raw data. This includes analysis of processed data.
    4. Conclusions: (Re)State main results and explanation. Describe how this fulfills the knowledge gap (see below) and enables useful and/or interesting things (outlook and future directions).
    5. Here we show: Summary of experiment. Preview of conclusions.
    6. Motivation and introduction: Why do this? Why is it interesting/useful? Describe the state of the field. Set up and describe the "gap in knowledge" that your work fills.
    7. Abstract: ("to draw out from") Take out the most essential parts of the manuscript.
    8. Reorder sections: The sections above are presented in the final manuscript in a different order than they are written: (1) abstract, (2) motivation and intro, (3) here we show, (4) experimental setup/methods, (5) data presentation and analysis, (6) results and discussion, (7) conclusions.
  10. Submission