Glossary

Adressing service

Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which indicates which parties participate in which functions and how to address them

Anonymize

Anonymized data are personal data that is processed so that the identifying features are irreversibly removed/hidden so that it is no longer possible to trace it back to a person

API

An API (Application Programming Interface) is used by software components to exchange data in a formalized way

Application overview

Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which provides an overview of who has done what with personal health data.

Authorative source

An authorative source is a record of data that is considered the primary source of that information.

Catalogue

The roles article refers to the Data Guide Role. This refers to the Catalogue, as implemented in the Health-RI hub as a National Health Data Catalogue. This role performs services that allow a data user to find existing health data that can be used for research with the functions

• Collect decentralised metadata; with the Find and discover existing health data action, the catalogue requests the latest status from all FAIR data points that are registered in the FAIR data point Register.

• Publish metadata

• Make metadata discoverable

Central data provider review commitee

Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), responsible for:

• Creating and managing generic terms of use

• Testing whether a analysis to be performed meets the conditions of use of the requested dataset(s)

• Testing (cross-source) data request for traceability of personal data

• Keeping track of case law

Citizen

In the context of the Health-RI ecosystem, a citizen is an individual who controls his or her data in the context of research and innovation.

Related roles: client, patient, subject

More: https://health-ri.atlassian.net/wiki/spaces/HNG/pages/997467851/Roles#Citizen

Clinical data

Clinical data is data that has to do with the health or treatment of people. They may come from clinical research, where treatments or other medical interventions are tested on human subjects, or from clinical practice, where Healthcare Professionals or patients collect data about their patients or in the case patients themselves.

Clinical (patient) research

In this research, an attempt is made to learn more about the condition by conducting research with patients. Examples of clinical research are the collection of clinical data to gain a good insight into the course of a condition. Also comparing the most efficient epilepsy or sleeping medication or identifying the best communication technique are examples of clinical research.

Source: https://encore-expertisecentrum.nl/

Cohort

A group of people who share certain characteristics or traits and are the subject of a study or dataset.

Data-archiver

A data archiver archives data in order to guarantee continuity of data provision in the event of the potential termination of original data source of a data producer.

The data archiver role is one of the roles that must be done by the data retention role. The data holder is the controller of the data that the data archiver archives.

Datacentric approach

A way of looking at where the data is central and not the purpose for which it was collected or used.

Data cleansing

The process of detecting and correcting or removing corrupt, duplicate, incomplete, incorrect, or irrelevant data from a dataset, table or database.

Data dictionary

A data dictionary is a collection of names, definitions, and attributes about data elements that are used or captured in a database, information system, or part of a research project. It describes the meanings and purposes of data elements within the context of a project and provides guidance on interpretation, accepted meanings, and representation. A data dictionary also provides metadata about data elements. The metadata included in a data dictionary assists in defining the scope and characteristics of data elements, as well as the rules for their usage and application.

Source: Everything You Need to Know About a Data Dictionary

Data Governance Committee

The Data Governance Committee is preferably one authorized coordinating party that draws up a standard data dictionary for a relevant domain, together with domain experts.

The data governance committee determines and manages:

• Standardized treatment process and protocols

• Minimal dataset with associated metadata set

• Unity of language for relevant dataset (coding and modeling); In which the relevant data governance committee is the mouthpiece to the (international) standard holders to implement possible harmonization adjustments, in order to prevent loss of quality in data transformation as much as possible.

• FAIR metadata templates

• Mapping definitions between different target groups within unity of language.

The Data Governance Committee is related to the generic features

More https://health-ri.atlassian.net/wiki/spaces/HNG/pages/997467851/Roles#Generic-features

Data guide

The data guide provides services that allow a user to find existing health data that can be used for the research with the functions

• Acquire decentralized metadata; under the find and discover existing health data action, the data guide requests the latest state of affairs from all FAIR data points that are registered in the addressing service.

• Publish metadata

• Making metadata traceable

Also known as: catalog

Data holder

A data holder is a person or organization responsible for the management and storage of health data within the Health-RI ecosystem for research and innovation. This can be, for example, a (collection of) hospital(s), a healthcare institution, a government agency, or a research organization that manages and stores health data.

The data holder is a collection of roles that correctly make original health data available to the Health-RI ecosystem:

• Local review committee data-offering

• Data producer

• Data Preparator

• Data archiver

• Data Provider

• Federated analysis

More https://health-ri.atlassian.net/wiki/spaces/HNG/pages/997467851/Roles#Data-holder

In GDPR the term 'data controller' is used as well for the data holder

Data management plan

A Data Management Plan (DMP) is a formal document developed at the beginning of your research project that describes all aspects of data management, both during and after the project. It contains, among other things:

• what data will be collected (type, size)

• where the data is stored, who has access to it and how access is arranged

• how often the data is backed up

• how the data is documented

• the version control strategy and the folder structure that will be used

• whether there are privacy and ownership issues

• whether and how the data will be archived and shared.

source: uu.nl

Data minimisation

Data minimisation means that a dataset does not contain more data than is necessary for the purpose for which the dataset was requested.

Data Preparator

Based on the data-centric principle, the data preparator separates the original health data from the original application and prepares the original health data, where necessary, for multiple use (including for use for research and innovation) in a persistent data platform.

The data preparator role is one of the roles that must be filled by the data holder role. The data holder is the controller of the data that the data preparator transforms.

Meer Roles | Datapreparator

Data processor

Within the Health-RI ecosystem for research and innovation, there are two forms of "Data Processing":

• Making data suitable for multiple use at the data holder: Preparing data

• Analyzing data at the data user: data analysis processor

Data producer

The data producer produces, creates and stores the original health data, preferably with

• Context information

• Terms of Use

• Coding and modeling according to unity of language

• Quality and usability characteristics

• Version control

For original data sources, where the data user does not have the basis to know personally sensitive information (researchers data sources), the data producer will store the original health data in a pseudonymized or anonymized manner.

The data producer role is one of the roles that must be done by the data holder role The data holder is the controller of the data that the data producer produces.

Dataprovider

The dataprovider sets up the delivery process of the dataset based on the terms of use of the data preparator and the target transformation.

The dataprovider role is one of the roles that must be done by the data holder. The data holder is the controller of the data made available by the data provider.

More Roles | Dataprovider

Data-request register

Data request and issue register, in which the reseearch data request service manages the requests.

Dataset

A dataset is a collection of similar data relating to a group of data subjects. The collection has a certain uniformity, such as the presence of certain data items or data types, and similar data acquisition and processing techniques, so that it makes sense to view the dataset as a group that can be drawn upon for reuse.
A dataset can be static, which means that the dataset no longer changes after delivery. On the other hand, a dataset can also be dynamic: the dataset is then subject to change and/or can be supplemented. In that case, the list of data subjects described by the dataset may also change

Datasubject

A datasubject is an identifiable natural person, whose health data is collected, processed, stored or shared within the Health-RI ecosystem. This could be, for example, a patient whose medical data is stored and shared between different healthcare professionals, researchers or government agencies.

Data user

A data user is a natural person who has access to health data within the Health-RI ecosystem for research and innovation, for the performance of specific tasks or purposes. For example, a data user may be a researcher who needs data for scientific research, a public authority that needs data for monitoring public health or a healthcare professional who needs access to health data for diagnosis or treatment.

Data user institute

A data user institute is the organization to which the data user belongs. The institute is legally responsible/liable for what happens to the data and also the contracting party for any agreements.

Data visiting

A form of data processing on one (existing) dataset at one location (e.g. Plugin)

(De-) identification service

Generic feature which pseudonymizes or anonymizes data.

Distributed processing

In the case of distributed processing, the data user instructs from a central point to perform processing on one or more environments that are set up under the control of each of the data holder(s) concerned.

Economy of scale

Economies of scale refers to the phenomenon whereby average costs per unit decrease as the scale of production increases.

FAIR Data Point

FAIR Data Points are used to describe your data sets in a FAIR way, using standard metadata and make them available through simple web protocols.
More info: https://www.fairdatapoint.org/

FAIR principles

FAIR is an acronym used in the context of data management. FAIR stands for Findable, Accessible, Interoperable and Reusable.
More info: What is Fair?

FAIRification

FAIRification is the process of improving a dataset’s alignment with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This can apply to both new data, where FAIR principles are integrated from the start, and to existing data, where efforts are made to enhance its findability, accessibility, interoperability, and reusability through modifications such as better documentation, metadata, and standardisation.

Feasibility study

A feasibility study is an assessment that determines how likely it is that a dataset will provide added value to a study. If a study concerns, for example, the elderly and they are not included in the dataset or are only included to a limited extent, the researcher may decide not to request the dataset in question.

Federated analysis coordinator

The federated analysis coordinator provides the tooling to submit the analysis question (in the case of a federated analysis) and ensures that the analysis question becomes available to the federated analysis implementers and that the results of the federated analysis are collected.

Federated analysis performer

The Federated analysis performer ensures that an applicant's assignment federated analysis is executed locally at a data holder, by

• Request action on (meta)data from data provider

• Receive data from data provider within environment data holder

• Calculate data using computing power within environment data holder

• Return results calculation to applicant federated analysis

Federated processing

Federated processing is a way of processing that does not depend on a centrally coordinated structure, so has no single point of failure or single point of power.

Generic Features

The nodes from the Health-RI ecosystem use generic features. Preferably, these generic features are also used in healthcare itself (primary use). This promotes transparency and consistency of the application of these services and avoids unnecessary multiple costs for implementing and managing the solutions.

The following generic features can be provided to the nodes of the Health-RI ecosystem:

• Identity registers

• System manager Health-RI

• Data Governance Committee

• Data inverter

• (De-)identification service

• Linking service

• Terms of use service

• Application overview

• Addressing service

• Central review committee data-offering

• Research data request service

• MDR certification provider

Health data

Health data is healthcare data + research data + all other data applicable to health (IoT data and citizen-generated data).

Health data access body (HDAB)

A legal entity designated by a Member State of the European Union to manage access to health data for research, policy and innovation. The role of an HDAB is to facilitate access to health data while ensuring the protection of personal data and privacy rights.

The tasks of an HDAB include:

• processing applications (assessing applications and granting permits)

• providing access control of the processing environment

source: EHDS Regulation

Healthcare data

Healthcare data is data that is used to support the care processes and/or is recorded during the care processes Healthcare data is a form of health data.

Healthcare Organisation

A healthcare organization is a provider and/or recipient of data and services in the field of research and innovation.

Healthcare Professional

A Healthcare Professional is a natural person who provides medical or health-related services to patients or clients, whose purpose is to promote the health of patients or clients, to prevent, treat and cure diseases, and to support them in maintaining or restoring their functional skills and quality of life.

Health-RI ecosystem

The integrated health data infrastructure for research and innovation that complies with the Health-RI Architecture.

The Integrated Health Data Infrastructure for Research and Innovation refers to the totality of all parties involved and elements in scientific research and how they interact with each other. This includes not only the technological resources and facilities, but also the social, cultural, economic and political environment in scientific research. Within the ecosystem, involved parties can exchange health data with each other in a secure way.

Health-RI foundation node

The Health-RI Foundation Node is a Nationwide node, which initially provides for the data user role. In time, this node will also provide the data-holding role for parties who cannot, may and/or do not want to make their original health data available through existing nodes.

Horizontal partitioning of data

With horizontally partitioned health data, each source contains data from different patients/ citizens/ participants (the rows) and each source contains the same characteristics (the columns)).

IAA

IAA stands for Identification, Authentication and Authorization. These are steps in the access control process.

See the articles Identification and Authentication Service and Authorization Service for more information.

Identity repositories

Different target groups use the Health-RI ecosystem. These different target groups each have specific roles and attributes. The NEN standard is currently looking at identification and authentication of healthcare professionals, which also faces the challenge that not all different groups of healthcare professionals fall under the UZI identification register. The Health-RI Foundation advocates a national approach or standardization of identity registers, in which the design of roles and attributes is looked at across domains and internationally. This also makes it easier to combine socio-economic information from ODISSEI with health data from the Health-RI ecosystem for prevention purposes.

The target groups that we distinguish for the Health-RI ecosystem are:

• Healthcare professionals

• Researchers

• Policy makers

• Citizens

Identity registers fall under the Generic features

Infrastructure

Infrastructure is the set of facilities (organization, process, information, application and technology) for processing, storing, securing, managing and transporting digital data.

Innovator

The Innovator is a special researcher who produces reusable research results and algorithms for data users who want to have simplified access to health data, such as healthcare professionals, policy makers and citizens. Tasks that an innovator performs are

• Research;

• Certify MDR on Algorithms

• Publish Algorithms;

Linking service

Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), to be able to combine data of a person over various sources (data linking) based on identifiers or keys.

Local review committee data providing

The local review committee data providing

• draw up in advance terms of use for the provision of the original data on data, preferably recorded with the data producer, or else with the data preparator.

• Performs review of a data research request for the original data source

Local review committee research

The organization to which the researcher or the data is affiliated has a review committee that determines whether studies that affiliated researchers want to start can be assessed on ethical and legal grounds.

Make data FAIR

This process involves assigning unique and persistent identifiers to the data, enriching metadata, and registering or indexing this data in searchable resources.

Making data comply with FAIR principles

This refers to the process of assessing existing data against the FAIR principles and making any necessary adjustments to meet these principles.

This may involve adding missing metadata, improving the discoverability of data, standardizing formats, and so on.

The goal is to transform the data so that it fully meets the FAIR criteria.

Mapping service

The mapping service is a generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which ensures that data is consistently translated between the different target groups of data holders and data users. In case of change in coding and modeling of standards within the unit of language, it is implemented once here.

MDR Notified Body

Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which grants Medical Device Registry (MDR) certification

Medical Research Ethics Committee (MREC)

A Medical Research Ethics Committee (MREC) assesses medical research with test subjects under the Medical Research Involving Human Subjects Act (WMO). The purpose of this assessment is to safeguard the rights, safety and well-being of the participants. A study can only be conducted after an approved MREC as issued a positive recommendation.

See also: TZW, CCMO

Metadata

Metadata is data about the data. It gives people and systems information about the context of the data. This context is needed to make the data easier to find, understand, and relevant. It also helps to get a better grip on the data.

Metadata provides people and systems with information about the context of the data. That context is necessary to make the data more findable, understandable and relevant. It also helps to get a better grip on the data.

Metadata can concern both datasets and data points.
Dataset metadata describes, for example, how much of which type of data is contained in a dataset. See Minimal (meta)dataset for further description.

Metadata about data points describes the context about a specific data point, for example a blood pressure measurement or image recording.

The term metadata can have different meanings in different processes. Something that is 'metadata' in the primary care process can be 'data' in secondary use, for example the time or the measuring device that is recorded during a blood pressure measurement in the primary care process.

Multiple use

Use both within healthcare (so-called primary use) and outside it, such as research and innovation (so-called secondary use). The responsibility for making data suitable for multiple use is shared between the data holder and the data user (in the role of data holder).

Alternate term: further use

National contact point for secondary use of electronic health data

An organizational and technical gateway enabling the cross-border secondary use of electronic health data, under the responsibility of a Member State of the European Union. The NCP-2nd-use is also responsible for ensuring interoperability and compatibility and for providing guidance and support.

source: EHDS Regulation

National node

A National node provides the role of connecting and/or applying nationally oriented specific data sources from the Health-RI ecosystem. The Health-RI Foundation is currently exploring a national categorical hub specifically for oncological health data.

Node

A node forms the access to the Health-RI Ecosystem of the role of Data holder and/or Data user. There are several types of nodes: