Action completion

Action completion


The MAPA Action has run through the middle of the first, second and third waves of the pandemic, ending in December 2021 at the beginning of the 6th wave (omicron). Undoubtedly, the first lockdowns that took place in Europe from March 2020 had an effect in the way the project had to be managed (full remote) and of course in the in-person gatherings for national dissemination that had to take place.

Nevertheless, and despite the above, MAPA has not experienced any major deviations in the final results, deliverables and objectives, with the large language community and European institutions being aware of the importance of anonymisation and MAPA becoming a reference point as the first truly multilingual open-source software available for Public Administrations with reference Use Cases. The MAPA docker is a usable, solid piece of software that can be used as set of language independent engines or as a general multilingual piece of software that can be integrated in document processing or other processes for general-purpose anonymisation, with a specialism in the legal and health domains.

MAPA can be deployed easily as all engines are fully dockerised. The integrity for use at Public Administrations has been independently tested by partner LIMSI (CNRS) as a specialist in de-identification software and tried at the engaged Use Cases (Spanish Ministry of Justice, Complaints Watch by DG-Justice). The security features are standard internet https:// compliant and those of a docker system as use in all cases has been internal to each organisation. An AS4 Domibus compliant connection is possible as planned for SaaS implementations. The docker can easily be connected to popular Computer Assisted Tools (CAT) used at Public Administrations to speed up the work of translators or build on them for full anonymisation during document translation processes, for example. Another use is as implemented by Complaints Watch (anonymisation of Excel files) or Spanish MoJ (documents, with document reconstruction taking place externally).

The consortium’s sustainability plan is designed to lead potentially to a source of revenue having European Public Administrations as clients and potentially fork out and further develop the tool to create other distributions and commercial solutions in the future. Furthermore, the Action has engaged several organisations as part of an interest group: members of the language association GALA, users of the European Language Grid. Several language service providers have expressed their interest in getting hold of the open-source version in GitLab (December 2021-January 2022). The set of engines are for free for European Public Administrations and the general public at large to download and implement (through ELG or GitLab). Consultancy and/or maintenance contracts may add to the software maintenance and product viability and sustainability as well as anonymisation engine updates.

All partners are committed to the maintenance of the product as part of its software portfolio offering. The anonymisation engines are and will remain an open-source MT engine system that can also be used as an academic benchmark to further the state-of-the-art.  MAPA, as a set of anonymisation engines and a private deployment is possible either in a European cloud or with on-premises deployments when privacy requires no outside connections.

Project Kicks Off in Valencia

The consortium met in Valencia at PangeaMT’s facilities to confirm the working plan, work packages and discuss the best strategies for data acquisition, word-embeddings and multilingual approaches to anonymisation

Click in the image below to see more info about the project.

Why Anonymize Data?

GDPR has changed multinational organisations keep and share personal data and it obliges them to protect citizens’ data so it is not released to 3rd parties. 

MAPA anonymisation will provide the means to share language data through a toolkit designed to protect personal or sensitive data. The project will focus on practical applications by justice departments, health authorities (Public Administrations). One of the aims of MAPA is to be able to provide access to data and manage an anonymisation strategy. A byproduct of anonymisation, for example, can be the release of large amounts of anonymised data that can help the community to have more AI training data. 

Most importantly, MAPA will satisfy GDPR requirements at scale. Although no software can guarantee 100% accuracy in anonymization, just as perfect machine translation does not exist (yet), it will make document sharing and keeping personal details private a straight-forward exercise.

Technical Approaches to Anonymisation

At its core, the MAPA anonymisation toolkit will use Named-Entity Recognition and Classification (NERC) techniques using both Deep Learning techniques and neural networks.

In addition, thanks to the transfer learning capabilities shown by new types of Deep-Learning models, new systems can be trained using relatively small datasets of manually labelled data. The knowledge acquired for a given domain or language can be transferred and re-used cross-language  or cross-domain. MAPA will be trained to detect named entities that involve sensitive information.

Use cases

MAPA is committed to implement Use Cases at a national level by several consortium members. These Use Cases will engage public institutions in Spain, Malta, Latvia, and eTranslation as an institution, with the focus being in the health domain and one for the legal domain, where the Spanish Ministry of Justice has already shown interest in its results. Both domains were selected given their strong anonymisation requirements as they are sensitive to personal details leak. 

The system will be tailored to the specific needs of the relevant institution.

MAPA is funded by the Connecting Europe Facility (CEF) programme, under grant No A2019/1927065, and will run from January 2020 until December 2021.