Raw data processing

from Wikipedia, the free encyclopedia

In raw data processing (primary data processing), the raw data that arise during an observation , measurement or data collection is checked, prepared, processed and transferred as secondary data into a new format - often with the aim of bringing the data into a form that is human is easier to understand. Raw data processing also means analyzing the raw data and the secondary data obtained, drawing conclusions and thus generating information.

Examples

The measurement of 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 raw data (primary data). The secondary data area with 20 m² and room volume with 56 m³ can be derived from them by calculation (raw data processing) .

In the laboratory, a scientist measures the pressure of a gas in a sealed container at different temperatures . The raw data here are the temperatures and the measured pressures. In the context of raw data processing, natural scientific laws or empirical formulas for the behavior of the gas can be derived from the primary measured values.

A team of doctors collects data on the effects of a drug in a clinical study. The test subjects' blood values, for example, are obtained as raw data. The raw data processing consists of the evaluation of the data and the derivation of statements about the effectiveness and safety of the drug.

Raw data processing in camera and PC

In digital photography, cameras often save the information read out by the photo diodes of the image sensor in raw data format (RAW format). The primary image data are therefore available unprocessed as they were captured by the camera's sensor . In image processing (raw data processing ), the raw data is developed in the camera or externally on a computer (for example with regard to the color space or the dynamic range) and interpreted by the photographer. The edited images are often saved in a compressed format such as JPG .

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

Methods for raw data processing

Raw data are unchecked data; they can be afflicted with errors (e.g. measurement errors ) of various kinds. Untested use can lead to wrong conclusions. Measurement data from complex measuring devices are often incomprehensible to humans without prior processing.

Common methods for processing the raw data are:

Raw data processing is of particular importance in laboratories that have to comply with quality management standards (e.g. testing laboratories). EDP ​​systems that are used in such laboratories for the acquisition, processing, storage and archiving of raw data must be validated .

See also

Individual evidence

  1. ↑ a b Federal Ministry for the Environment, Nature Conservation and Nuclear Safety: Announcement of a consensus document of the Federal and State Working Group on Good Laboratory Practice (GLP) on the subject of "Good Laboratory Practice (GLP) and Data Processing". October 28, 1996, accessed June 16, 2020 .
  2. ↑ a b CFR - Code of Federal Regulations Title 21 PART 58 Good Laboratory Practice For Nonclinical Laboratory Studies § 58.3 - Definitions. April 1, 2019, accessed June 16, 2020 .
  3. ↑ a b c Stefan Luber, Nico Litzel: What are raw data? In: BigData-Insider. Vogel IT-Medien, April 9, 2020, accessed on June 16, 2020 .
  4. ↑ Wikibooks: Digital imaging methods, chapter light conversion. Retrieved June 16, 2020 .
  5. ↑ Tim Aschermann: What is RAW? Explained in a simple and understandable way. In: Chip practical tips. September 7, 2018, accessed June 16, 2020 .
  6. ↑ Bernhard Appel, Christoph Hornberger, Jannis Batoulis, Konstantin Clevermann, Ralf Hössel, Dieter Weiser: Archiving electronic data in the GxP environment Part 3: Implementation of archiving electronic data. In: Pharm. Ind. 73, No. 7, 1207-1215 (2011). 2011, accessed June 16, 2020 .