Research Documentation

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When publishing research, it is important to make documentation available so that readers can understand the details of the research design that the work reports. This includes all of the technical details and decisions that could influence how the findings are read or understood. Usually, this will involve producing a document along the lines of a methodological note or appendix. That document will describe how a given study was designed and how the design was carried out. The level of detail is in such a document should be relatively high. This page will describe some common approaches to compiling this kind of material and retaining the needed information in an organized fashion throughout the life of a research project.

Read First

  • Research documentation provides the context to understanding the results of a given research output.
  • There is no standard form for this documentation, and its location and format will depend on the type of research output produced.
  • For academic materials, this documentation often takes the form of a structured methodological appendix.
  • For policy outputs or online products, it may be appropriate to include an informative README webpage or document.
  • The most important process for preparing this documentation will be retaining and organizing the needed information throughout the life of the project, so that the team will not have to search through communications or data archives for small details at publication time.

What to include in research documentation

Research documentation should include all the information that is needed to understand the underlying design for the research output. This can include descriptions of:

  • Populations of interest that informed the study
  • Methods of sampling or other sources of data about selecting the units of observation that were actually included in the study
  • Field work, including data collection or experimental manipulation, such as study protocols and monitoring or quality assurance information
  • Statistical approaches such as definitions of key constructed indicators, corrections or adjustments to data, and precise definitions of estimators and estimation procedures
  • Data completeness, including non-observed units or quantities that were planned or "tracking" information

All of the research documentation taken together should broadly allow a reader to understand how information was gathered, what it represents, what kind of information and data files to expect, and how to relate that information to the results of the research. Research documentation is not a complete guide to data, however; it does not need to provide the level of detail or instructions that would enable a reader to approach different research questions using the same data.

Documentation will take different forms depending on the information included. Much of it will be written narrative rather than, for example, formal data sets. Understanding research documentation should not require the user to have any special software or to undertake any analytical tasks themselves. Relevant datasets (such as tracking of units of observation over time) might be included alongside the documentation, but the documentation should summarize in narrative form all the information from that dataset that is likely to affect the interpretation of the research.