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Data Write-up: The Who, What, When, Where, and Why

You are an investigator. You collect data to test your theory and prove your point.

You and journalists are similar. In writing their articles, journalists are taught to answer five questions: who, what, when, where, and why.

This post tells you how to write the data and methods section of a research article in the social sciences.

What is the data and methods section of an empirical research article in the social sciences?

The data section of an empirical research article in the social sciences must address the who, what, when, where, and why of the data.

These are classic journalist questions that can be applied to the data write-up section of your article.

Let’s define them.


This is the units of analysis (example: Individuals in European Social Survey or countries in a comparative research project that uses World Bank Indicators). Or, who are the participants in the interviews?


This is the type of data: survey, in-depth interview, participant observation, and so on


These are the dates of data collection — can be years, but it can be months, and it can be specific dates, depending on the situation (in-class note: this can be tricky. You have dates of data collection (like interviews) but also the time-span that your research covers.


This is the location of the units of analysis (countries, city/town/village). This can include the “scene” of the interview, and gets close to the “setting”


Justify the choice of the data — the reasons that these data are the best to address the research question

Let’s look at an example from survey data

“Our data are all 30 countries in the European Social Survey data Round 9 (ESS 2018). ESS is a high quality sociological survey with individuals as the units of analysis and has the items we need to address our research question on the relationships between immigration attitudes, employment, and protest across nations.”

This short statement about the data answers the basic questions of the data.

Who: Individuals nested in countries

What: Cross-national survey

When: 2018

Where: 30 countries

Why: High quality survey data that has the right items for the research question

Let’s look at an example from a qualitative article

From: “Latino/a professionals as entrepreneurs: how race, class, and gender shape entrepreneurial incorporation” by Jody Agius Vallejo & Stephanie L. Canizales published in Ethnic and Racial Studies (2016).

“This research draws on a larger study of middle- and upper-class Latino entrepreneurs in Los Angeles. For this paper we control for business sector by limiting our analyses to twenty-three entrepreneurs who own professional services businesses such as finance, insurance, real estate, law, and public relations… Lasting between two and three hours, the interviews were conducted by the authors and a Latina graduate student, either at the subject’s office, home, or in public, between October 2010 and July 2014. The interviews were open-ended, tape-recorded, and then transcribed verbatim.”

Who: Latino/a professionals, i.e. individuals

What: In-depth interviews (lasted ca. 2 hours)

When: 2010 – 2014

Where: Los Angeles, California, USA

Why: They do not say explicitly, but in the introduction, they write that they wanted to explore an “intersectional approach that considers how race, class position, and gender, coalesce to differently shape Latinos/as’ entry into and experiences in the professional business sector.” As such, the data on male and female Latinx are a justification for the data that did not need to be explicitly stated in the data section.

Copyright Joshua Dubrow The Sociology Place 2022

Joshua K. Dubrow is a PhD from The Ohio State University and a Professor of Sociology at the Polish Academy of Sciences.

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