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EtherCIS (Ethereal Clinical Information System) is an Open Source platform compatible with the openEHR standard. It is design to allow simple interactions with clients using RESTful API and persist clinical data in a separate DB engine. Clinical data are exchanged using different formats:

FLAT JSON: which is a flatten representation of access path along with the corresponding field value
Canonical XML: representing an openEHR composition in standard XML
For more details on data representation in openEHR see this page


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ARX is a comprehensive open source software for anonymizing sensitive personal data. It has been designed from the ground up to provide high scalability, ease of use and a tight integration of the many different aspects relevant to data anonymization. Its highlights include:


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MOLGENIS is a modular web application for scientific data. MOLGENIS was born from molecular genetics research (and was called 'molecular genetics information system') but has grown, thanks too many sponsors and contributors, to be used in many scientifc areas such as biobanking, rare disease research, patient registries and even energy research. MOLGENIS provides researchers with user friendly and scalable software infrastructures to capture, exchange, and exploit the large amounts of data that is being produced by scientific organisations all around the world.


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OBiBa software consists of a suite of stand-alone applications that support various study's data management activities. These modular applications can be integrated to create a comprehensive information management and analysis system for individual studies.

As part of the Maelstrom Research program, OBiBa suite includes advanced software components enabling data harmonization and federation for study networks that aim to harmonize and share securely data among their members.


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Mainzelliste is a web-based first-level pseudonymization service. It allows for the creation of personal identifiers (PID) from identifying attributes (IDAT), and thanks to the record linkage functionality, this is even possible with poor quality identifying data. The functions are available through a RESTful web interface.

The following article describes the underlying concepts of Mainzelliste and the motivation for its development. Please cite it when referring to Mainzelliste in publications:


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OpenSpecimen (formerly known as caTissue Plus) is a Free & Open Source biobank/biospecimen management software. At the heart of OpenSpecimen is that “biospecimens without high quality data is of no value”.

OpenSpecimen is used across the globe in some of the most respected biobanks of various sizes and diseases. OpenSpecimen streamlines management of biospecimens across collection, consent, QC, request and distribution. Finally, OpenSpecimen is highly configurable and customizable. E.g., adding a custom field or form can be done in minutes by a non-IT person.


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The MediPi Telehealth System is a simple implementation of a Telehealth patient/client system. It has been developed to be flexible and extensible.

IDRT - Integrated Data Repository Toolkit

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i2b2 has turned out to be a very valuable component for secondary use of routine clinical data. Its pragmatic database schema allows merging of data from heterogeneous data sources, and the intuitive user interface enables easy querying and powerful processing. However, it's a component rather than a complete solution: The user is facing several barriers when integrating i2b2 into the operational workflow.


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Usagi is a software tool created by the Observational Health Data Sciences and Informatics (OHDSI) team and is used to help in the process of mapping codes from a source system into the standard terminologies stored in the Observational Medical Outcomes Partnership (OMOP) Vocabulary (


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ACHILLES is a platform which enables the characterization, quality assessment and visualization of observational health databases. ACHILLES provides users with an interactive, exploratory framework to assess patient demographics, the prevalence of conditions, drugs and procedures, and to evaluate the distribution of values for clinical observations.

ACHILLES is intended to be implemented by organizations that have patient-level observational health databases available in their local environment.


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