What is data anonymization?
Data anonymization is a procedure that removes clearly identifiable information from data sets rendering it fully secure. It replaces original data with a value that is unrelatable to the original source. It also ensures that this anonymized information can never be reassociated with that original source.
Data anonymization is an essential requirement in the Exfluency workflow. Not only for the purposes of legal compliance with such things as GDPR, but also because we have clients that are dealing with highly sensitive information, unique and ground-breaking research, or completely new advances in their particular field of expertise.
How we work with anonymization
Because the Exfluency Enhancement Editor focuses on the meaning of the content by using Subject Matter Experts (SMEs) rather than translators, the source text only needs to be referred to on the rarest occasions. The way in which Exfluency deploys data anonymization means that sensitive content is replaced with something that keeps the context but is entirely non-traceable.
The following is a summary of the anonymization steps we take during a typical Exfluency enhancement project:
- De-anonymized data is uploaded and stored on a secure server separate from the rest of the platform
- All confidential data is stored in client gated communities that can only be accessed by the Requester and those SMEs specifically cleared to work there
- Only anonymized data is sent to the four NMT engines
- All data sent to NMT engines is first scrambled
- Only anonymized data is sent to the SMEs
- Only anonymized data is stored on the platform
- SMEs cannot copy-paste source data for extraction or use it in other tools
- Files are de-anonymized on the secure server before return to the Requester
- Project files on the secure server are destroyed
- Final versions are not available to anyone but the Requester
Beyond statutory requirements, data anonymization is not always applied, or indeed required. But should it be a necessity for you, we will ensure that your sensitive data is always secure.
There is an additional benefit to highly effective data anonymization: the better anonymized content is, the more it can be reused, and the greater value it can offer in the creation of new, recyclable linguist assets.
