Data Triangulation: How the Triangulation of Data Strengthens Your Research

View Worksheet

Data triangulation validates your data and research by cross verifying the same information. This triangulation of data strengthens your research paper because your data has increased credibility and validity.

The triangulation of data occurs when multiple theories, materials or methods are used. The following are a few of the most common approaches:

Data source triangulation—Using evidence from different types of data sources, such as primary and secondary research or interviews, documents, public records, photographs and observations

Methodology triangulation—Combining multiple methods to gather data, such as documents, interviews, observations, questionnaires or surveys, when conducting primary research, at different times and in different places

Theory triangulation—Using more than one theoretical approach (theory) to interpret and support data

Benefits of data triangulation

The triangulation of data strengthens your research and allows you to write a better research paper because of the following benefits.

  • Additional sources of information often give more insight into a topic
  • Inadequacies found in one-source data is minimized when multiple sources confirm the same data
  • Multiple sources provide verification and validity while complementing similar data
  • More comprehensive data is obtained
  • Data and information is supported in multiple places/types of research, which makes it easier to analyze data to draw conclusions and outcomes
  • Inconsistencies in data sets are more easily recognized

A closer look at types of data triangulation

Understanding how the triangulation of data works is important to using this method to strengthen your research. Below each of the types of triangulation identified above with examples of how you could combine data.

Data source triangulation:

If you were utilizing information and data obtained through secondary research, finding data sets that complement one another is accomplished by using multiple types of sources. Increasing the credibility of your research is done, for example, by complementing something in a written document with relevant statistics from public records or visual confirmation with a historical photograph.

Methodology triangulation:

If you were conducting primary research and wanted to use data triangulation, you might combine two different types of interviews: conversational interviewing and structured-question interviewing. By using two different methods, or approaches, to collect your data, you obtain different information that (hopefully) provides data sets that complement one another. If both approaches yield results that support your hypothesis or theory, your data is naturally more valid. You could even combine those data sets with results from conducting an observation, or combine it with another study by using data source triangulation.

Theory triangulation:

This type of data triangulation is a bit different because it does not so much integrate results that show more validity; instead, it helps give you a better understanding while you make sense of data and information. For example, you might find a theory that undermines the credibility of a data set when another theory is applied. When this occurs, the strength of the data for your research purposes is hindered. When two competing theories can both support data, the information is appropriate to include in your paper; when they do not, the information is better left out of your paper. While sometimes competing theories might support the findings under each other, this does not normally occur with this type of data triangulation.

However you employ the process of the triangulation of data, it strengthens your paper by increasing the overall validity and credibility of the data sets and information you use. This method of combining different aspects of research from multiple places, theories or methods is easily undertaken for any type of research you conduct.