Secondary data

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Secondary data are those data that result from primary data through processing steps ( primary data processing ). It is derived or processed data that is the result of primary data processing. In contrast to this are the primary data that are obtained directly during an observation , measurement or data collection and that are still unprocessed.

Typical methods for processing primary data into secondary data are ( primary data processing )

In the social sciences and medicine in particular , the term secondary data refers to the reuse of data in the context of a secondary analysis or in secondary research . Here, data from already available sources is collected and re-evaluated. This saves time and money; because the data is already available and does not have to be collected with great effort. The use of secondary data harbors risks such as inadequate timeliness and the quality of the data that cannot be checked, as this data was originally collected for a different purpose.

Examples

Measuring a room results in a length of 5 m, a width of 4 m and a height of 2.80 m. These three values ​​are the primary data . The secondary data area with 20 m 2 and volume with 56 m 3 can be derived from them by calculation ( primary data processing ) .

In the laboratory, a scientist measures the pressure of a gas in a sealed container at different temperatures . The primary data here are the temperatures and the measured pressures . From the primary measured values, secondary data can be derived within the framework of primary data processing, which show the behavior of the gas as a function of temperature in the form of diagrams or empirical formulas.

An opinion research institute determines the popularity of political parties as part of a voter survey. The primary data here are information on the people surveyed (age, gender, etc.) and the people's answers. The primary data processing includes anonymization , evaluation and interpretation of the primary data obtained during the survey and enables forecasts of the election result.

Another polling institute does not conduct a direct voter survey, but uses secondary data from an earlier study for its election forecast, which questioned people's attitudes to current political issues.

trouble

If primary data are not sufficiently distinguished from secondary data (derived data), working with secondary data often leads to falsified or inadmissible conclusions such as: B.

  • the intersection of differently accurate data;
  • the interpretation of data about whose accuracy , reliability, timeliness, etc. little or no information is available;
  • the wrong understanding of data coming from other subject areas or
  • have multiple assigned names (designations).

In some cases - especially in the case of complex measurements with computer-controlled devices - a clear separation between primary and secondary data is often difficult because the electronics or the software of the devices can already prepare (preprocess) the primary data .

In the case of statistical calculations, secondary data can usually no longer be divided into the individual units and thus make some calculations such as correlations impossible.

See also

Primary data (raw data)

Primary data processing (raw data processing)

Research data

Individual evidence

  1. ^ Michael Franke: Research data management. In: Max Planck Digital Library. University of Applied Sciences for Public Administration and Justice in Bavaria, 2014, accessed on June 28, 2020 .
  2. ↑ Prof. Dr. Oliver Schöffski: Quantitative health services research with secondary data . Bavarian State Office for Health and Food Safety, June 18, 2018, accessed on June 28, 2020 .
  3. ^ Ashley Crossman: Pros and Cons of Secondary Data Analysis. ThoughtCo, June 13, 2019, accessed June 28, 2020 .
  4. ↑ Dr. Florian Becker: 6. Primary data, secondary data and meta-analysis as a data source in market research. In: Technical texts research process. Business Psychological Society Munich, accessed on June 28, 2020 .