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‘-omics’
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Study of a field of biology in its entirety; e.g. genomics studies the entire genome of an organism
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Anonymised
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Anonymised data do not contain any identifiable information such as, for example, name, address, phone number, full date of birth, national health or social insurance numbers, full postcode, etc., and it is not possible for the researcher to identify the individual to whom the data relate.
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API - Application Programming Interface
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Text-based means of interacting with a computer programme normally accessed by visual interaction
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BBMRI - Biobanking and Biomolecular Resources Research Infrastructure
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Infrastructure for the integration of biobank and molecular research data from humans and model organisms
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BMB - BioMedBridges
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A project to develop data e-infrastructure for biomedical data exchange between ten European biomedical research infrastructures
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BMS - Bio-Medical Sciences
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Refers to the European research infrastructures covering biology and medicine
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CMPO
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Cellular Microscopy Phenotype Ontology
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Copyright
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Copyright is an automated right that lasts 50 to 70 years (depending on the country of origin) after the death of the originator. Copyright protects literary and artistic works, including music, from use and copying from others without permission.
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Data
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In the context of the BioMedBridges project, the term data may refer to genomic data, anonymised images, metadata, etc. It does not refer to data that contains identifiable information such as name, phone number, or date of birth.
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Data controller
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A data controller is a person who (either alone or jointly or in common with other persons) determines the purposes for which and the manner in which any personal data are, or are to be, processed.
In the context of BioMedBridges, data controllers are located with the project partners providing data (where applicable).
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Data Integration
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The process of combining multiple sources of data into a unified form
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Data Interoperability
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The process of allowing data resources and software to interface together
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Data loss
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The term data loss describes a condition in which information is destroyed by failures or neglect in storage, transmission or processing.
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Data management plan
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A data management plan describes how data is handled during a project and what happens to the data once the project is completed or how long-term preservation is organised. Preparation of a data management plan before data are collected ensures that data are in the correct format, organized well, and better annotated.
In the context of BioMedBridges, data management is up to the data providers.
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Data processing
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The term data processing refers to "any operation or set of operations which is performed upon personal data, whether or not by automatic means, such as collection, recording, organization, storage, adaptation or alteration, retrieval, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, blocking, erasure or destruction;" (see also Article 2b of the EU data protection directive)
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Data processor
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The data processor is any person (other than an employee of the Data Controller) who processes data on behalf of the Data Controller.
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Data provenance
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Data provenance encompasses documentation about the origin of data and includes the description of processes relating to data creation, transformation, and copying.
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Data provenance model
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There are two models of provenance concerning data: workflow and data provenance. Workflow provenance describes processes relating to data creation and transformation (i.e. a scientific experiment and its result); data provenance models concern small pieces of data and describe its origin, e.g. from which database data has been copied from (e.g. a wrong phone number of a patient at a doctor’s practice may come from inaccurate dictation or copying from an inaccurate database – what data provenance needs to understand is where the error came from: when and where was it entered, who copied it).
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Data provider
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The data provider is the individual researcher or investigator, or body of researchers or investigators (or, in the context of the BioMedBridges project, the project partner) that makes data available for access and use within the BioMedBridges project.
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Database
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A database is a structured collection of usually large amounts of data with the aim to provide a system of rapid search and retrieval
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EATRIS - European Infrastructure for Translational Research
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Infrastructure aimed at aiding the move of biomedical technologies into clinical practice
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ECRIN - European Clinical Research Infrastructure Network
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Infrastructure for the integration and interoperability of data from research and clinical trials
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Elixir
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Infrastructure to create a system for the integration, safeguarding and provision of European life science data
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EMBRC - European Marine Biology Resource Centre
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Infrastructure for improving access to organisms and techniques for marine research
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ERIHNA - European Research Infrastructure on Highly Pathogenic Agents
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Infrastructure to develop capacity for research into highly-pathogenic micro-organisms
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ESFRI – European Strategy Forum on Research Infrastructures
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A strategic instrument to develop the scientific integration of European research
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Ethics committee
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The term Ethics committee in this document [NB. The Ethical Governance Framework] refers to a committee which has given ethical approval for a study which has collected data that will be subsequently made available by the data provider within the BioMedBridges project. (It does not refer to the BioMedBridges Ethical Governance Committee.)
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EU-OPENSCREEN - Open Screening Platforms for Chemical Biology
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Infrastructure to support platforms for high-throughput chemical screening, chemical libraries, drug optimisation and chemoinformatics
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Euro-BioImaging
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Infrastructure for creating a distributed network of biological and medical imaging facilities
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FIMM
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Finnish Institute of Molecular Medicine
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GUI - Graphical User Interface
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Visual means of interacting with a computer programme as an alternative to text-based programmes
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HPO - Human Phenotype Ontology
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Ontology covering abnormal phenotypes seen in human disease
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HTS
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High-Throughput Screening (chemical screening)
High-Throughput Sequencing (DNA sequencing)
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INFRAFRONTIER
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Infrastructure for phenotyping and archiving of model mammalian genomes
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INSTRUCT
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Infrastructure for the integration of structural bio-molecular data with clinical data
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Linked, anonymised
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Linked anonymised (or pseudoanonymised or coded) data are fully anonymous to the researchers who receive or use them, but contain information or codes that would allow others (e.g., the clinical team who collected them or an independent body entrusted with the safekeeping of the code) to link them back to identifiable individuals.
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OMIM - Online Mendelian Inheritance in Man
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Online resource providing information on inherited genetic disease
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Ontology
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In informatics and computer science, an ontology is a representation of shared knowledge. It is a model of the common entities that need to be understood. They aid software and users to function and communicate at the level required for a set of tasks. An ontology provide the intended meaning of a formal vocabulary used to describe a certain conceptualisation of objects in a domain of interest. An ontology describes the categories of objects described in a body of data and the relationships between those objects and the relationships between those categories. In doing so, an ontology describes those objects and sometimes defines what is needed to be known in order to recognise one of those objects. By controlling the labels given to the categories in an ontology, a controlled vocabulary can be delivered; though an ontology is not a controlled vocabulary. When represented as a set of logical axioms with a strict semantics, an ontology can be used to make inferences about the objects that it describes and consequently provides a means to symbolically manipulate knowledge.
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Ontology, application
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An application ontology is built towards a specific use case, such as for tooling or database needs. A reference ontologies may be used to construct an application ontology, with terms that are not required removed for simplicity.
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Ontology, components
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An ontology may contain several structural components. These include: Individuals, Classes, Attributes, Relations
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Ontology, reference
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A reference ontology is built with the aim of becoming an authority on a given domain. An example is the Gene Ontology, that covers gene and gene product attributes across species and databases. OBO (www.obofoundry.org) lists the major reference ontologies in the biological and biomedical sciences.
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Participants
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The term ‘participant’ refers to an individual whose data are accessed within the scope of the BioMedBridges project. Participant in this document [NB. The Ethical Governance Framework] is equal to “data subject” in applicable EU legal documentation.
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Patent
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A patent is a form of intellectual property that protects new inventions from production, usage, import and selling from others without permission for up to 20 years. It describes in detail how the invention works, what it does and how it does is, what it is made of and how it is made.
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Personal data
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Personal data concerns any piece of information that can identify a natural person, directly or indirectly, in particular by reference to an identification number or by one or more factors specific to their physical, physiological, mental, economic, cultural or social identity. In other words, data are "personal data" when someone is able to link specific information to a person, even if the person (or body) holding the data cannot make this link.
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Phenobridge
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WP7 - bridging mouse and human phenotype data
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Phenotator
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WP6 user-facing annotation tool
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PM - Personalised Medicine
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Medical treatments tailored to the individual patient
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RDF - Resource Description Framework
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Methodology for the description or modelling of information in a computer-accessible format
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REST - Representational State Transfer
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Computer architecture commonly applied in the development of web-based services
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RI – Research Infrastructure
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The facilities, resources and related services used as part of research in a scientific field
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Trade secret
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A trade secret, in some countries referred to as confidential secret, is any piece of confidential information (manufacturing, industrial or commercial secret) that allows a business a competitive advantage.
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Un-linked, anonymised
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Unlinked anonymised data contain no information that could reasonably be used by anyone to identify the individuals who donated them or to whom they relate.
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UniChem
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Database 'resolver' for cross-linking chemical structure identifiers
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Use case
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Scientific
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Use case, ontology
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Outline of interactions between a user and a system. Examples include: interactions with data, a system or an ontology
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