1.1.11.1.1.1What is the purpose of the data collection/generation and its relation to the objectives of the project?Up to three lines of text that summarise the type of study (or studies) for which the data are being collected.
1.1Type of study
1.2.11.2.1.1What is the origin of the data?Types of data to be managed in the following terms: quantitative, qualitative; generated from surveys, clinical measurements, interviews, medical records, electronic health records, administrative records, genotypic data, images, tissue samples...
1.2Types of data
1.3.11.3.1.1What types and formats of data will the project generate/collect?File formats, software used, number of records, databases, sweeps, repetitions… (in terms that are meaningful in your field). Do formats and software enable sharing and long-term validity of data?
1.3Format and scale of the data
1Description of the data
2.1.12.1.1.1What internationally recognised licence will you use for your data?
2.1.22.1.2.1trueWill you use naming conventions for your data?
2.1.32.1.3.12.1.3.2URL/Name
2.1Methodologies for data collection / generationHow the data will be collected/generated and which community data standards (if any) will be used at this stage.
2.2.12.2.1.1truetrue2.2.1.22.2.1.3trueWill you use standardised vocabularies?
2.2.22.2.2.12.2.2.2URL/Description
2.2.32.2.3.1truefalseWill you use standardised formats for some or all of your data?
2.2.42.2.4.12.2.4.2trueWhich standardised data formats do you plan on using?
2.2.52.2.5.12.2.5.2Standardised formatsIs the structure of the file(s) provided in a standardised format?
2.2.62.2.6.12.2.6.22.2.6.3Please describe the formats you plan to store your data in, including any URLs to documentation.
2.2.72.2.7.1Will you provide metadata describing the quality of the data?
2.2Data quality and standardsHow consistency and quality of data collection / generation will be controlled and documented, through processes of calibration, repeat samples or measurements, standardised data capture or recording, data entry validation, peer review of data or representation with controlled vocabularies.
2Data collection / generationMake sure you justify why new data collection or long term management is needed in your Case for Support. Focus in this template on the good practice and standards for ensuring new data are of high quality and processing is well documented
3.1.13.1.1.1Briefly describe how data will be stored, backed-up, managed and curated in the short to medium term. Specify any community agreed or other formal data standards used (with URL references).
3.1Managing, storing and curating data
3.2.13.2.1.1truetruetrue3.2.1.23.2.1.3trueWill you use metadata to describe the data?
3.2.23.2.2.13.2.2.2URL/Location
3.2.33.2.3.1Will your metadata be harvestable?
3.2Metadata standards and data documentationWhat metadata is produced about the data generated from the research/innovation? For example, descriptions of data that enable research/innovation data to be used by others outside of your own team. This may include documenting the methods used to generate the data, analytical and procedural information, capturing instrument metadata alongside data, documenting provenance of data and their coding, detailed descriptions for variables, records,etc.
3.3Data preservation strategy and standards
3Data management, documentation and curation
4.1.14.1.1.1truefalse4.1.1.2If your organisation is ISO compliant? If yes, please state the registration number.
4.1.24.1.2.1Identify formal information standards with which your study is or will be compliant.
4.1Formal information/data security standards
4.2.14.2.1.1keptoninsecureWhat do you plan to do with research data of limited use
4.2.24.2.2.1Please describe why the data will be kept on insecure, unmanaged storage
4.2Main risks to data securityAll personal data has an element of risk. Summarise the main risks to the confidentiality and security of information related to human participants, the level of risk and how these risks will be managed. Cover the main processes or facilities for storage and processing of personal data, data access, with controls put in place and any auditing of user compliance with consent and security conditions. It is not sufficient to write not applicable under this heading
4Data security and confidentiality of potentially disclosive informationThis section MUST be completed if your data includes personal data relating to human participants. For other research/innovation, the safeguarding and security of data should also be considered. Information provided will be in line with your ethical review. Please note this section concerns protecting the data, not the patients.
5.1.15.1.1.15.1.1.25.1.1.3trueHow will the data be made available?Identify any data repository (-ies) that are, or will be, entrusted with storing, curating and/or sharing data from your study, where they exist for particular disciplinary domains or data types.
5.1.25.1.2.15.1.2.2URL/Name
5.1.35.1.3.1somenoneWill all your data be openly accessible?Is the data you propose to collect (or existing data you propose to use) in the study suitable for sharing? If yes, briefly state why it is suitable. If No, indicate why the data will not be suitable for sharing and then go to Section 6.
5.1.45.1.4.15.1.4.25.1.4.3Data type/ Reason/ URL
5.1.55.1.5.15.1.5.25.1.5.3Data type/ Reason/ URL
5.1Suitability for sharing
5.2.15.2.1.1As part of the consent process, proposed procedures for data sharing should be set out clearly and current and potential future risks associated with this explained to participants.
5.2Restrictions or delays to sharing, with planned actions to limit such restrictionsRestriction to data sharing may be due to participant confidentiality, consent agreements or IPR. Strategies to limit restrictions may include data being anonymised or aggregated; gaining participant consent for data sharing; gaining copyright permissions. For prospective studies, consent procedures should include provision for data sharing to maximise the value of the data for wider research/innovation use, while providing adequate safeguards for participants.
5.3.15.3.1.1truetrueAre there any methods or tools required to access the data?
5.3.25.3.2.15.3.2.2Please provide links describing the methods for accessing the data.
5.3.35.3.3.15.3.3.2Please provide links describing the tools for accessing the data.
5.3.45.3.4.1How widely accessible is this depository? Indicate whether your policy or approach to data sharing is (or will be) published on your study website (or by other means).
5.3Discovery by potential users of the research/innovation dataIndicate how potential new users (outside of your organisation) can find out about your data and identify whether it could be suitable for their research/innovation purposes, e.g. through summary information (metadata) being readily available on the study website or in databases or catalogues.
5.4.15.4.1.1falseWill you identify a data manager to manage your data, if not who will be responsible for the management of your data?
5.4.25.4.2.1Identify the people or roles that will be responsible for the management of the project data
5.4Governance of accessIdentify who makes or will make the decision on whether to supply the data to a potential new user. Indicate whether the data will be deposited in and available from an identified community database, repository, archive or other infrastructure established to curate and share data.
5.5.15.5.1.1What are the timescale/dependencies for when data will be accessible to others outside of your team?Summarize the principles of your current/intended policy.
5.5The study team’s exclusive use of the dataUKRI’s requirement is for timely data sharing, with the understanding that a limited, defined period of exclusive use of data for primary research/innovation is reasonable according to the nature and value of the data, and that this restriction on sharing should be based on simple, clear principles.
5.6.15.6.1.1Indicate whether external users are (will be) bound by data sharing agreements, setting out their main responsibilities.
5.6Regulation of responsibilities of users
5Data sharing and access
6.16.1.16.1.2Apart from the PI, who is responsible at your organisation/within your consortia for
6Responsibilities
7.17.1.1Complete, policies which are relevant to your study, and are in the public domain, e.g. accessible through the internet. (Data Management Policy & Procedures, Data Security Policy, Data Sharing Policy, Institutional Information Policy)
7Relevant institutional, departmental or study policies on data sharing and data security
8.18.1.1falsetrue8.1.2Is Author of this Data Management Plan different to that of the Principal Investigator?
8.28.2.18.2.28.2.3Author of this Data Management Plan details
8Author of this Data Management Plan (Name) and, if different to that of the Principal Investigator, their telephone & email contact details