2.3.1 Generation, recording, handling and archiving of raw data

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​​​​​​​​​A. Background & Definitions

This item refers to one of the Core Requirements (Core Requirement 6 - "Generation, handling and changes to data records must be documented​​") and is, therefore, considered as essential.

Raw data means all original records and documentation, which are the result of the observations and activities in a study.

Raw data may include:

  • photographs, videotapes, blots, chromatograms, computer readable media, dictated observations, recorded data from automated instruments, or any other medium capable of providing secure storage of information for a time period required by law or other applicable regulations;
  • data directly entered into a computer through an automatic instrument interface, which are the results of primary observations and activities in a study;
  • copies of original laboratory records and documentation that are complete and of good quality.

As raw data may also be recognized the processed result of original observations when these latter cannot be stored for technical reasons, e.g.:

  • a research tool conducts pre-processing of original observations (example: movements of a rat in an open field are recorded by means of the photobeam breaks; research software may present the raw data as a movement track or a calculated distance traveled rather than a sequence of photobeam breaks);
  • a research tool records data in a specific format that may or may not be readable at a later time point (e.g. if the license to use this research tool expires) and therefore pre-processing supports long-term accessibility of the original observations;
  • a research tool generates exceptionally large volumes of data that are technically difficult to store without pre-processing to reduce the storage volume (e.g. imaging data).

Experimental Record: A research diary entry for an experiment giving access to or information about location of raw data and pertinent details of an experiment such that a peer could repeat the experiment.


B. Guidance & Expectations

Implementation and maintenance of processes related to raw data is one of the main responsibilities of the 1.5.2.3 Process owner or other scientist(s) to whom Process Owner delegates this task.

Processes related to raw data as well as the associated roles and responsibilities should be described in the study protocol (or protocols for specific research methods). If not such formal description is available or possible, Process Owner should ensure that the desired practices are in place and are verifiable.

Generation and recording of raw data:

  • All equipment and computerized systems used for data generation must be fit-for-purpose (please check item 3.3.2).
  • Every research unit has to define what is regarded as raw data for the experiments conducted in that particular research unit.
  • All records should bear a 2.1.2 Unique study ID and must be dated and signed / initialed by the person making the entry; this can be done electronically or on paper.
  • Data should be recorded at the time of generation (meaning that any delay should be justifiable by the study protocol or associated working procedures) ( 3.1.2)

Handling of raw data:

  • The processing of raw data records must be transparent (for details please check the items 3.1.2.1 and 3.1.2.2) and understandable by a third person.
  • Any changes to the data records must be documented, reason for a change must be explained, dated, signed and saved; for details see the item 3.1.2.

Storing of raw data:

  • The storage of raw data must ensure readability and protection from loss, modification, destruction and unauthorized access (link to 3.1.3).
  • Raw data should be stored in a read-only mode according to legal, contractual or other obligations.
  • If raw data cannot be saved in an electronic or paper notebook (e.g. because of the volume or format), experimental record must contain a reference to the location where raw data is stored.

Common Data Elements (CDEs): In preclinical research, the use of CDEs receives increasing attention and is encouraged as it can facilitate data sharing across research projects and provides opportunities for comparison and combination of data sets from multiple studies. CDEs are standardized key terms or concepts, established to be used in experimental studies, so that research findings can be generalized with respect to different research institutions, diverse populations, different regions, and interventions.

More detailed information can be found here:


​PLEASE DO NOT FORGET

  • ​To check whether storage of raw data will not endanger traceability (i.e. whether raw data can be traced back from the reports and publications)
  • To make sure that the duration of storage and accessibility of raw data is not determined by presence of a specific employee or student​
  • To consider adding this subject to a training program for new employees or refresher training
  • To update the Documentation Plan when any changes are made to the way raw data are handled


C. Resources



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Next item: 2.3.1.1 Converting non-electronic information into an electronic form