What is data extraction in research?

What do you mean by data extraction?

Data extraction is the process of collecting or retrieving disparate types of data from a variety of sources, many of which may be poorly organized or completely unstructured.

What are the examples of data extraction?

Unstructured data extraction Examples of data sources include web pages, emails, text documents, PDFs, scanned text, mainframe reports, or spool files. However, it's crucial to remember that the information contained within them is no less valuable than that found in structured forms!

Why are data extraction forms important?

Data extraction forms link systematic reviews with primary research and provide the foundation for appraising, analysing, summarising and interpreting a body of evidence. This makes their development, pilot testing and use a crucial part of the systematic reviews process.

What should be included in data extraction?

From each included study, the following data may need to be extracted, depending on the review's purpose: title, author, year, journal, research question and specific aims, conceptual framework, hypothesis, research methods or study type, and concluding points.