Collecting data is an essential activity in almost all (empirical) research. Data are typically needed to answer your research questions, test your hypotheses, and/or substantiate your claims. Exceptions may include, for instance, purely conceptual articles or book reviews. These may however be difficult Getting published, especially for PhD students.
As types and sources of (research) data are almost endless, it seems impossible to provide a brief yet comprehensive guide on what data to collect. Useful base distinctions include (see this guide for more info):
Different data may be appropriate to different research aims. For instance, quantitative data are typically more suitable for testing theory (hypotheses), whereas qualitative data are typically more suitable for developing theory.
Different types of data can be collected from different sources and through different Methods. The “how” of data collection is highly dependent on your research aim and the Methods you choose. To facilitate your research and your eventual Writing process, consider the following generic tips:
Below you find a super brief comparison of some common data collection methods (non-exhaustive list). All these methods can be used for collecting both qualitative and quantitative data, depending on how you apply them - though some methods are more geared towards qualitative data collection (interviews), some more towards quantitative data collection (surveys/questionnaires).
| Data collection method | Particularly suited for … | “Richness” of data | Difficulty of access | Interpretability | Time consumption |
|---|---|---|---|---|---|
| Archival documents/ Literature review | Identifying “status quo” of knowledge/ thought | Low (text) to high (e.g. video) | Very low (public data) to high (private data) | Low (quant) to high (qual) | Low to medium (high scalability) |
| Surveys/ questionnaires | Capturing people’s opinions and feelings (breadth) | Medium | Low to high (depends on population) | Low (quant) to high (qual) | Low to medium (high scalability) |
| Interviews | Capturing people’s opinions and feelings (depth) | High | Medium to high | Low (structured interviews) to very high (unstructured interviews) | High |
| Observations | Deeply understanding local social phenomena | Very high | Very high | Very high | Very high |