Importance of Data Integrity in the Data Life Cycle

For all systems which store, process, and retrieve data – such as thermal analyzers – data integrity is paramount.

“Data integrity is the degree to which data are complete, consistent, accurate, trustworthy, reliable and that these characteristics of the data are maintained throughout the data life cycle. The data should be collected and maintained in a secure manner, so that they are attributable, legible, contemporaneously recorded, original (or a true copy) and accurate. Assuring data integrity requires appropriate quality and risk management systems, including adherence to sound scientific principles and good documentation practices.”

From MHRA GXP Data Integrity Guidance and Definitions; Revision 1: March 2018

Data integrity is a central issue in all laboratories which are regulated by Good Manufacturing Practice (GMP). However, even research laboratories and industries which are not regulated can recognize that the benefits of establishing good data management practices outweigh the costs.

Features and Benefits

Access control – access to the system is restricted to only those individuals who are authorized to access it

User Level Management – allows for the customization of user access profiles in order to minimize the likelihood of data manipulation

User group specific data access – data is protected against misuse or manipulation

Data classification – the confidentiality of electronic data across the entire system is guaranteed

Dr. Bob McDowall, a data integrity expert, points out that there are two phases to the data life cycle – inactive and active. The majority of laboratory work occurs during the active phase, from acquisition to data use and short-term retention. However, this is also the life cycle’s shortest part.

For the remainder of the record retention period, the data and records are stored in the inactive phases. This phase lasts for as many as 30 years in certain instances.

Regulatory ALCOA+ Criteria: Ensuring Data Integrity

Five criteria have been introduced by regulatory authorities for ensuring data integrity, known by the acronym ALCOA. The European Medicines Agency (EMA) has expanded these criteria to 9 in total for GxP data. This framework is used extensively as the framework for guaranteeing Good Documentation Practice (GDP) and data integrity.

ALCOA+ Meaning
1. Attributable
  • Attributable means information is captured in the record so that it is uniquely identified as executed by the originator of the data (e.g. a person or a computer system).
2. Legible
  • The term legible refers to the requirements that data are readable, understandable, and allow a clear picture of the sequencing of steps or events in the record so that all GXP activities conducted can be fully reconstructed by the people reviewing these records at any point during the records retention period set by the applicable GXP.
3. Contemporaneous
  • Contemporaneous data are data recorded at the time they are generated or observed.
4. Original
  • Original record: Data as the file or format in which it was originally generated, preserving the integrity (accuracy, completeness, content and meaning) of the record, e.g. original paper record of manual observation, or electronic raw data file from a computerized system.
  • Written observation or printout or a certified copy thereof.
  • Electronic record including metadata of an activity.
5. Accurate
  • Data are correct, truthful, complete, valid and reliable.
6. Complete
  • All data from an analysis including any data generated when a problem is observed and resolved. For hybrid systems, the signed paper output must be linked to the underlying electronic records used to produce it.
7. Consistent
  • All elements of the analysis such as the sequence of events follow on and data files are date and time stamped in the expected order.
8. Enduring
  • Recorded on authorized media e.g. laboratory notebooks, numbered worksheets for which there is accountability or electronic media.
9. Available
  • The complete collection of records can be accessed or retrieved for review and audit or inspection over the lifetime of the record.


All of the necessary functionality for a total data integrity solution is provided by the STARe software. Electronic records are completely protected against unintentional or intentional modification, as they are kept in a secure, relational database.

Additionally, all evaluations performed on curves are saved as a copy automatically with a new date, making sure that the original record is preserved. Occasionally, the conditions of the experiment (for instance, gas flow) depart from the method’s defined parameters. In these cases, potentially invalid results are highlighted as the measurement results are marked in brackets.

The STARe database keeps a total record history in line with the principles of ALCOA+. It does so by linking the operator to the measured record, the evaluation, method, instrument, adjustment data, and experimental conditions.

Crucial in order to comply with regulatory guidelines and the data integrity of laboratory computerized systems, four functionalities are provided by the STARe software option, “Data Integrity”.

User Account for Access Control

User Account

Access control via user accounts limits system access to authorized individuals only. User accounts in STARe are password protected and uniquely tied to specific individuals.

User Roles Determine Permissions

User rights

Up to 33 different rights can be assigned as appropriate to an unlimited number of different user roles. In this way, each user is granted specific permissions depending on their user role.

User roles

Each user is assigned a user role (e.g. administrator, lab manager, lab technician, operator, etc.).

Restricted Data Access: Protects Electronic Data Against Misuse

User Group Specific Data Access

Users can access data which belongs to user groups of which they are members, or to their home group.

The static functional organization and the more dynamic project organization can be represented by user groups.

Data Classification Protects Confidential Data

In terms of data security, risk management, and compliance, data classification is of vital importance. In order to guard electronic records against unauthorized viewing, modification, or access, 10 different levels can be applied.

This information has been sourced, reviewed and adapted from materials provided by Mettler Toledo - Thermal Analysis.

For more information on this source, please visit Mettler Toledo - Thermal Analysis.


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