Effective date: 27 November 2018
OpenRiskNet is a project funded by the European Commission within Horizon 2020 EINFRA-22-2016 Programme (Project number 731075) aiming to develop an open e-infrastructure providing resources and services to a variety of scientific communities requiring risk assessment.
Definition of terms used in this document
Anonymisation = data are considered to be anonymised where they are fully (unlinked) anonymised or linked (coded, pseudo-) anonymised where the linkage code (cipher) is not held by, or accessible to, the researchers/research establishment. ‘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 reasonably possible for the researcher to identify the individual to whom the data relates.
Linked anonymised (or pseudo-anonymised 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.
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.
Data = the term ‘data’ in this document may refer to biological data, toxicity data, 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.
Personal Data = data which may be used to identify a research participant. (Note: although in some EU jurisdictions personal data may also be used to describe human biosamples, in the context of this document, it relates to identifiable data only).
Data Owner = the ‘data owner’ is the individual researcher or investigator or body of researchers or investigators that produced the original data.
Data Provider = the ‘data provider’ is the individual researcher or investigator or body of researchers or investigators that makes data available for access and use within the OpenRiskNet e-infrastructure.
Data User = the ‘data user’ is the individual researcher or investigator or body of researchers that processes data through the OpenRiskNet e-infrastructure.
About the OpenRiskNet e-infrastructure
OpenRiskNet is an e-infrastructure for the harmonisation and improved interoperability of data and software tools in predictive toxicology and risk assessment. It aims at supporting safe-by-design product development and risk assessment of drugs, chemicals, cosmetic products and nano materials by integrating existing toxicology databases and in silico tools and combine them to workflows for predicting hazard, exposure and finally risk.
- Web services providing data or analysis, processing and modelling tools communicating over well-defined and harmonized application programming interfaces (APIs);
- An interoperability concept and framework for general and specific services integration by consortium members and associated partners;
- A featured platform for predictive toxicology and risk assessment for end users (e.g. toxicologists, risk assessors and regulators using case studies).
OpenRiskNet e-infrastructure includes data management systems that make available existing and open data sources mainly from in vitro human and animal and in vivo animal experiments to all stakeholders in a harmonised way.
Data providers and data users of OpenRiskNet e-infrastructure
Data providers and users of OpenRiskNet e-infrastructure have a number of responsibilities and obligations, such as the obligation to respect participant confidentiality. Researchers and data managers accessing the data and even more providing data as a OpenRiskNet service have a custodian role, to ensure the careful and responsible management of the information. They have an obligation to operate in conformity with the requirements of their own institution, and fulfil all necessary national and international regulatory and ethical requirements during data generation (in vivo, in vitro and in silico), preparation for sharing and ongoing management of the resources. They also have obligations to the OpenRiskNet e-infrastructure, the integrity of their own research, as well as the funders and the wider research community, to carry out high quality, ethical research.
Use of OpenRiskNet e-infrastructure
- All users have an obligation of confidentiality and must conform to data protection principles to ensure that data is processed in compliance with the legal and ethical requirements.
- The data owners must ensure that they have sought and obtained, where necessary, all appropriate approvals, ethical and legal, for the data collected. OpenRiskNet will provide information on the approval procedure and status, whenever this is provided by the data owner or data provider and collection is technical feasible. Listing of the information does not imply that OpenRiskNet guarantees the accuracy of any provided information.
- For animal data, the data owner must ensure that national guidelines for their welfare and care during the collection of data have been followed.
- OpenRiskNet does not guarantee the accuracy of any provided data.
- OpenRiskNet has implemented appropriate technical and organisational measures to ensure a level of security which we deem appropriate, taking into account the sensitivity of data we handle. However, the data provider holds sole responsibility for the usage and distribution of data.
- OpenRiskNet requires all data provided or used in the OpenRiskNet infrastructure being anonymised before submission. This does not limit the use of the OpenRiskNet infrastructure installed locally with suitable security measures prohibiting unauthorised access.
- Computing of personal and sensitive data on OpenRiskNet e-infrastructure should be run internally by the users on their secure cloud infrastructures under appropriate firewalls. OpenRiskNet will not hold any liability for any loss or damage to data.