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6. Data Sharing and Long-Term Preservation
|
What methods/systems, software tools, source code or other types of services are needed to understand, access,and use the data?
|
The data will be published in the Swedish National Data Service (SND). No specific systems/software/codes/services are considered required.
|
8ec1441a11103ca59167b9ed660dc529
|
dmponline.dcc.ac.uk
|
7. Data Management Responsibilities and Resources
|
Who (e.g., role, position, and institution) will be responsible for data management?
|
Rosa Hellman, doctoral student [email protected] , Department of People and Society, SLU, https://orcid.org/0009-0008-3923-3713 Responsible for data management during and after project, for implementing and updating DMP and ensuring DMP is reviewed and revised.
|
8ec1441a11103ca59167b9ed660dc529
|
dmponline.dcc.ac.uk
|
7. Data Management Responsibilities and Resources
|
What resources (e.g., costs and time) will be dedicated to data management?
|
Staff time will be required to perform data management. No additional resources are required.
|
8ec1441a11103ca59167b9ed660dc529
|
dmponline.dcc.ac.uk
|
7. Data Management Responsibilities and Resources
|
What resources (e.g., costs and time) will be dedicated to ensuring that data will be FAIR (Findable, Accessible,Interoperable, Reusable)?
|
Staff time will be required to ensuring the FAIR principles are implemented.
|
8ec1441a11103ca59167b9ed660dc529
|
dmponline.dcc.ac.uk
|
General TU Delft data management questions
|
Name of data management support staff consulted during the preparation of this plan
|
Esther Plomp, TNW Data Steward
|
f2f2e493700dfa71fa9d1cf5a86b8707
|
dmponline.dcc.ac.uk
|
General TU Delft data management questions
|
Is TU Delft the lead institution for this project?
|
Depends on the specific project, some projects are collaborative, some with TUD the only organization.
|
f2f2e493700dfa71fa9d1cf5a86b8707
|
dmponline.dcc.ac.uk
|
General TU Delft data management questions
|
How will you share your research data (and code)?
|
Zenodo
|
f2f2e493700dfa71fa9d1cf5a86b8707
|
dmponline.dcc.ac.uk
|
Data Collection
|
What data will you collect or create?
|
Quantitative Data: 1. Demographic Information:
* Gender, age, years of experience in healthcare, and sector (public or private).
2. Flexible Working Dynamics:
* Type of flexible working arrangement (e.g., remote working, part-time, hybrid).
* Duration of flexible working experience.
* Reasons for using flexible working arrangements.
3. Performance and Well-being:
* Impact of flexible working on job performance, job satisfaction, work-life balance, mental health, and productivity. These would be rated on a scale (e.g., very negatively to very positively).
* Frequency of experiencing technical issues while working flexibly.
4. Benefits and Challenges:
* Benefits such as improved work-life balance, increased job satisfaction, and productivity.
* Challenges such as difficulty in communication, feelings of isolation, and technological issues.
Qualitative Data: 1. 1. Open-Ended Responses:
* Suggestions for improving flexible working arrangements.
* Personal experiences and impacts of flexible working on collaboration, career progression, and physical health.
* Thoughts on the support needed from management and the organisation to improve flexible working conditions. 2. In-depth Interviews:
* Detailed insights into the specific challenges and benefits of flexible working.
* Exploration of how flexible working has impacted professional relationships, team cohesion, and overall job satisfaction.
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Data Collection
|
How will the data be collected or created?
|
Survey responses will be collected online using the Jisc platform interviews will be completed at a location, time, and place convenient to the participant, including remotely if they want.
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Documentation and Metadata
|
What documentation and metadata will accompany the data?
|
Data from both surveys and interviews will be kept confidential and anonymous. Participant details will be collected with the responses and will only be accessible to the lead investigator. Data will only be collected from the relevant participants in the research. Responses will be made available to all researchers but stored with a participant-identifying number known only to the lead investigator. Direct quotes of free-text answers may be used, but these will not be traceable to the participant. All data will be stored within the University of Plymouth cloud-based encrypted files (OneDrive).
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
|
How will you manage any ethical issues?
|
To manage ethical issues, informed consent will be obtained from participants via the JISC survey before they proceed. The survey includes a dedicated page that outlines the purpose of the research, and participants must provide consent to continue. Data will be collected anonymously, ensuring privacy and confidentiality. Additionally, participants will be informed of their right to withdraw at any time without penalty. Ethical approval for the study has been granted, with the necessary documentation signed by both the principal investigator and the supervisor, confirming compliance with ethical standards.
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
|
How will you manage copyright and Intellectual Property Rights (IPR) issues?
|
To manage copyright and intellectual property (IP) issues, the principal investigator will ensure that everything created in this research is original or properly credited. If any materials from others are used, permission will be obtained, and credit will be given. The research data and findings will belong to the IP and the institution. Participants' contributions will remain anonymous, and they won’t have ownership of the research outputs. Any data shared or published will follow copyright and IP rules.
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Storage and Backup
|
How will the data be stored and backed up during the research?
|
All data will be stored on Jisc or within University of Plymouth cloud-based encrypted files (OneDrive) during analysis
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Storage and Backup
|
How will you manage access and security?
|
Only the PI will have access to the raw data
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Selection and Preservation
|
Which data are of long-term value and should be retained, shared, and/or preserved?
|
Response data will only be kept for the duration of the study and will be deleted from OneDrive once the analysis and write-up have been completed (projected end date September 2024). Data may be disclosed in published works posted online for use by other researchers and the community. Research findings might also be presented at required conference or used in future research.
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Selection and Preservation
|
What is the long-term preservation plan for the dataset?
|
Data will only be kept for the duration of the study and will be deleted from OneDrive once the analysis and write-up have been completed (projected end September 2024)
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Data Sharing
|
How will you share the data?
|
Reports and publications for the analysed data.
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
Who will be responsible for data management?
|
Principle Investigator (PI) Participating Researchers (PR)
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
What resources will you require to deliver your plan?
|
Jisc - no cost to researchers as utilising UoP subscription Onedrive - no cost to researchers as utilising UoP subscription
|
17f7ba3ad66893eaf0a4c665621361e1
|
dmponline.dcc.ac.uk
|
4. Data security
|
Address data recovery as well as secure storage and transfer of sensitive data
|
Storing and backup data: Storage on local devices: Personal computer and hard disk Network storage: Mails containing deliverables Cloud storage: Dropbox and google drive personal account The above follows the recommendations for safely working with IT provided by the host institution of this research (Ghent University). The guidelines provide information about: 1) Trustworthiness of devices 2) University account protection 3)Common risks and hazards 4) Central disk storage information 5) Use of internal applications provided by the university (ex. Citrix) 6) The use of external cloud services for confidential data 7) Data leak and IT devices lost The researcher is responsible for backing up data regularly during the course of research activities. Data does not contain any sensitive information or trade secrets.
|
304110bb65179277bb07ac726b982be4
|
dmponline.dcc.ac.uk
|
5. Ethical aspects
|
To be covered in the context of the ethics review, ethics section of DoA and ethics deliverables. Include references andrelated technical aspects if not covered by the former
|
As stated in the grant agreement, REFLOW will respect fundamental ethical principles, including those reflected in the Charter of Fundamental Rights of the European Union, the European Convention on Human Rights and its Supplementary Protocols, and the relevant ethics rules of H2020. Identity protection, data security, data retention, and data sharing will be informed consent forms. In the case of the processing of personal data for this research, ethical standards will be followed such as the Code of conduct for the processing of personal data. This is a document based on Belgian and European privacy and data protection legislation on which Ghent University is governed. These guidelines include as well basic principles such as confidentiality and integrity. For more information: https://www.ugent.be/en/ghentuniv/privacy/code-of-conduct-personal-data.htm
|
304110bb65179277bb07ac726b982be4
|
dmponline.dcc.ac.uk
|
6. Other
|
Refer to other national/funder/sectorial/departmental procedures for data management that you are using (if any)
|
No other national/funder/sectorial/departmental procedures are considered for this stage of the project.
|
304110bb65179277bb07ac726b982be4
|
dmponline.dcc.ac.uk
|
0. Proposal name
|
Enter the proposal name
|
Improving adoption of mental health interventions among low-income university students in Brazil
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
1. Description of the data
|
Format and scale of the data
|
Data will be stored electronically. Qualitative data will be stored either in NVivo 10.0 or similar programmes that are used locally. Quantitative data will be collected and stored via Redcap and analysed either in Stata or R. All statistical programmes used enable sharing and long-term validity of results.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
2. Data collection / generation
|
Data quality and standards
|
All interviewers will undergo rigorous training in administration of the project questionnaires and procedures, including e.g., confidentiality. Project PI (SEL) and Scientific Coordinator (CZ) will monitor data quality and random quality checks will be performed. Any data collected will be periodically downloaded and saved to a secure server at the local university and all data will be transferred to LSE storage via an encrypted channel. The study PI (SEL) and Scientific Coordinator (CZ) have experience in secure methods of data storage and transfer. We will ensure that any person identifiable data processed complies with the General Data Protection Act (GDPR) UK Data Protection 2018 and Lei Geral de Proteção de Dados (LGPD), 2021. Where MP3 recordings are taken for the qualitative elements of the research, notes will assist transcription of any poor-quality audio. During analysis, transcripts will be analysed by an experienced second coder using a structured codebook to assess inter-coder reliability, and both coders will meet regularly to discuss any disputes in the coding process. The quality of data collection will be supervised by senior researchers in the team, with overall supervision by the PI. Quantitative data quality will be reviewed every week by the Data Manager. Built-in validation rules and automated data quality checks within RedCap will be used to minimize errors and ensure data accuracy. RedCap forms will include validation checks to ensure data accuracy and completeness. Periodic data audits and reviews will be conducted to identify and rectify inconsistencies. Data cleaning procedures will involve identifying and correcting errors or inconsistencies in the dataset.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
2. Data collection / generation
|
Consent for data sharing and re-use
|
We will ensure that access to and use of data will be made available in ways that are equitable, ethical and efficient. Data will be shared with collaborators according to predefined access permissions. Data requests will be reviewed and approved by the data management team. Data sharing will follow institutional policies and regulatory requirements. Participants will be informed about the objectives and procedures of data sharing and will provide consent to participate in the study being aware of the data sharing objectives and procedures. They will be aware that data will be de-identified prior to sharing or publication to prevent re-identification.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
3. Data management, documentation and curation
|
Managing, storing and curating data
|
All quantitative data will be stored in RedCap and then exported in text-delimited format, which can be used in all computer platforms or in STATA or R software package file or in any other format needed by the collaborators. Data files will be stored in well- organised folders and file names. Quality checks of the database will take place by double-checking, for example, out-of-range values, double entry of data and performing statistical analyses such as frequencies, means ranges to detect errors and anomalous values. All data will be psudonymised for analysis and will be accessible to the project investigator. Project data will be automatically backed up to local servers. Identifying data will be kept as a separate list with identifying codes which will be used on the research records. The document linking the project identification number with personal data will only be accessible to the study research team. Only anonymised data will be used for analyses. With the permission of participants, qualitative interviews and focus groups will be audio-recorded, will then be transcribed in the local language. Files of anonymised transcripts will be secure.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
3. Data management, documentation and curation
|
Metadata standards and data documentation
|
Metadata will be structured to international standards of schemes such as Data Documentation Initiative (DDI). The metadata for this study will consist of a detailed data dictionary. We will follow the DDI regulations and provide: names, labels and descriptions of variables; records and their values explanation or definition of codes and classification schemes used; definitions of specialist terminology and acronyms used; and codes of, and reasons for, missing values. A research protocol detailing the methods by which data will be generated and collected will be produced at the beginning of the project. All data will be electronically stored and coded in a way that is understandable to researchers outside of the research team, in case data will be shared at a later time point. Analyses of qualitative data will be undertaken using thematic analysis.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
3. Data management, documentation and curation
|
Data preservation strategy and standards
|
As described in the UK archive report (https://us.sagepub.com/en-us/nam/managing-and-sharing-research-data/book240297), we will keep a single master file of data; regulate write access to master versions of data files; record all changes to master files; maintain old master files in case later ones contain errors; archive copies of master files at regular intervals; develop a formal procedure for the destruction of master files. All data will be stored electronically in anonymised form for a minimum of seven years, in accordance with LSE requirements, or in accordance with best practice in Brazil and when no longer required the data will be destroyed, both at study sites and at the co-ordinating centre. Audio data recordings will be destroyed after transcription is complete and verified. All data will be password-protected.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
4. Data security and confidentiality of potentially disclosive personal information
|
Formal information/data security standards
|
Our data management will be fully aligned with MRC Guidance on Personal Information in Medical Research, and MRC information security policy, and with the requirements of all partner institutions. The formal data security standard adhered to is UK Data Protection Act 2018 and Lei Geral de Proteção de Dados (LGPD), 2021.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
4. Data security and confidentiality of potentially disclosive personal information
|
Main risks to data security and how they will be managed
|
Encrypted data from Brazil will be transferred to LSE using RedCap storage service. All files kept in this manner are managed and backed up by the college’s IT department. Study researchers will undergo in-depth training in proper data management, including maintenance of confidentiality and ensuring privacy during data collection. Data will be utilised in conformity with the consent provided by participants. Any data on paper will be kept in a secure cupboard/repository in the project site office. These measures have been used in our previous research projects and have proven feasible and effective. We shall develop and use Standard Operating Procedures in place for all research activities. As part of this protocol, any adverse events that happened within the scope of the project will be systematically documented, reported and reviewed.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
Suitability for sharing
|
It is anticipated that the data generated by the formative research, pilot and RCT will be suitable for sharing. We will align procedures with the Data Sharing Protocol based both upon the data needs of the study researchers, and upon current standards of best practice, and in line with MRC policy. Only anonymised data will be shared within the study team and in accordance with the project data-sharing policy. The study will generate data that may be of interest for other researchers, policymakers or service users within the study and related sites. In principle we shall make data available to others and will create a system to facilitate use of the data. Interested parties will need to complete a proforma that will ask for the specific research question and data needed. The research team will provide an independent view on the scientific merits of the request. We shall ensure that no reasonable request will be refused and there will not be unnecessary delays in providing access. Our data sharing procedure will be guided by: (1) the need to ensure that the datasets are first used to address the primary aims of the project; (2) every effort will be made to offer unrestricted access thereafter, with the only proviso being the continued protection of the anonymity of participants; and (3) due acknowledgement is given by subsequent users to the original source of the data. We will work to ensure that the data, whenever it is to become available to the public, is understandable. Data would be shared only using the anonymous ID number, without any identifying personal information.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
Discovery by potential users of the research data
|
The data archive will be advertised on the project website, MRC gateway, and LSEs RDM. Metadata, and study questionnaires will be on the project website, as will the data sharing policy.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
Governance of access
|
Information on data sharing procedures will be made available upon enquiry by a potential investigator. In principle we shall make data available to others and will create a system to facilitate use of the data. Interested parties will need to complete a proforma that will ask for the specific research question and data needed. Investigators who wish to use the data archive will complete an application form, which will be assessed by the PPIs. Decisions by PI will be guided by the Study team.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
The study team's exclusive use of the data
|
Data will be made available to others outside of the research team after completion of the project (i.e. after 12 months), though data may be made available earlier than that if the reasons for this are well justified and this does not put the publication of data by the research team at risk
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
Restrictions or delays to sharing, with planned actions to limit such restrictions
|
The consent procedures (participant information sheets and consent forms) will highlight that data may be shared with researchers outside of the research team. Participant information sheets and consent forms will have the procedures for data sharing clearly laid out, and any potential risks will be explained to participants. Shared data will be effectively anonymised.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
Regulation of responsibilities of users
|
Users will sign a legally binding data use agreement, the main requirements being not to identify participants, to use the data only for the purposes requested, not to share with other users, and to acknowledge the collectors of the data, and the funders . External users of data will be required to complete a proforma that will ask for the specific research question and data needed. On acceptance, external users will be required to complete a Memorandum of Understanding.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
5. Data sharing and access
|
Working with overseas collaborators or data users
|
Data without personal identification will be shared between partner institutions who will collaborate on data analysis through secure data sharing processes on the REDCap-UNIFESP (Universidade Federal de São Paulo) platform ( https://redcap.epm.br/ ). All data storage and sharing will be maintained in accordance with Brazil’s General Data Protection Law and the United Kingdom’s Data Protection Law. To prevent unauthorized access to data saved on the equipment used for data processing, all computerized data will be stored on secure servers of each partner institution. All researchers with access to the data will receive training on risk management and confidentiality concerning the data and will be required to sign statements agreeing to protect the security, integrity, and confidentiality of the participants.
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
7. Relevant policies
|
Relevant institutional, departmental or study policies on data sharing and data security
|
Policy URL or reference Data Management Policy and Procedures Project-specific procedures are established using the LSE’s frameworks: https://info.lse.ac.uk/staff/divisions/Secretarys-Division/Information-Rights-and-Management/GDPR ; https://info.lse.ac.uk/staff/services/Policies-and-procedures/Assets/Documents/resDatManPol.pdf Data Security Policy https://info.lse.ac.uk/staff/services/Policies-and-procedures/Assets/Documents/datProPol.pdf Data Sharing Policy e.g. a study policy of sharing research data Institutional Information Policy Information Security Policy: https://info.lse.ac.uk/staff/services/Policies-and- procedures/Assets/Documents/infSecPol.pdf Other Data Processing outside EEA by Collaborators – Minimum Standards: https://info.lse.ac.uk/staff/services/Policies- and-procedures/Assets/Documents/internal/staffAndStudents/minStaEEACol.pdf Other General Data Protection Law, Brazil: Lei Geral de Proteção de Dados https://www.gov.br/esporte/pt-br/acesso-a- informacao/lgpd
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
8. Author
|
Author of this Data Management Plan (Name) and, if different to that of the Principal Investigator, their telephone& email contact details
|
Carolina Ziebold, Scientific Coordinator. Telephone: 56958892739, email: [email protected]
|
9772a51d9ecb7371614bcdd93a0d00cf
|
dmponline.dcc.ac.uk
|
Management and sharing data
|
How will you manage and share data collected or acquired through the proposed research?
|
Report on the key findings of the qualitative research of the study to share as a research output within internal knowledge exchange meetings in the DCMS
|
3c1c6affcfb7a329bcd43179b8477c2c
|
dmponline.dcc.ac.uk
|
Administrative Information
|
Project funder or sponsor.
|
Playing for the Planet commissioned this project, a United Nations Environment Programme initiative funded by UK Interactive Entertainment.
|
4ccb3c0fe2da7d3fc88e063e4b1c7057
|
dmponline.dcc.ac.uk
|
Storage and Back-Up
|
Where will your data be stored and backed-up during the project?
|
All live data will be stored on DataStore and Sharepoint as outlined above.
|
4ccb3c0fe2da7d3fc88e063e4b1c7057
|
dmponline.dcc.ac.uk
|
Selection and Preservation
|
Where will the data be stored long-term?
|
The Open Science Framework & DataShare. Players and studios will provide informed consent for the research team to share anonymised data on the OSF and DataShare.
|
4ccb3c0fe2da7d3fc88e063e4b1c7057
|
dmponline.dcc.ac.uk
|
Data Sharing
|
How will you maximize data discoverability & access?
|
We create a DOI in OSF and DataShare and cite these in a data availability statement in the published report.
|
4ccb3c0fe2da7d3fc88e063e4b1c7057
|
dmponline.dcc.ac.uk
|
Responsibilities & Resources
|
Will you require any training or resources to properly manage your research data throughout this project?
|
No. AR and TY have taken data protection and management training through UoE (AR thorugh her role as a research fellow. TY during his MSc course). CW has taken similar training via the CITI Program (Human Subjects Research, Social and Behavioural Human Subjects Research, Responsible Conduct of Research) completed through Pennsylvania State University. He has also reviewed UofE's data protection and data management guidance online. AR will support the research team if any queries arise during this process. Where she is unable to address these queries, she will contact the research data service or data protection team.
|
4ccb3c0fe2da7d3fc88e063e4b1c7057
|
dmponline.dcc.ac.uk
|
A. Describe the research project
|
Name researcher (please, add your full name):
|
Johan Craeymeersch
|
8a90e29415a8b7282e6f753c0f551bb8
|
dmponline.dcc.ac.uk
|
A. Describe the research project
|
What is the name of your chair group(s) or business unit(s)? English name and abbreviation for chair groupsfrom
|
this page ; business units from this page (expand to Wageningen Research and keep expanding to find your specific division / group). Examples: Bioprocess Engineering (BPE) or Contract Research Organization (CRO). -
|
8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
|
A. Describe the research project
|
Describe the organisational context of your research project.
|
DMP version (or date last modified) Supervisor / (co-)promotors Graduate School (WU only) Start date of project 1 sept 2024 End date of project 31 dec 2027 Project number Funding body Rijkswaterstaat
|
8a90e29415a8b7282e6f753c0f551bb8
|
dmponline.dcc.ac.uk
|
A. Describe the research project
|
Give a short description of your research project.
|
Title Nulmeting en monitoring biotiek Boontjes Summary Rijkswaterstaat heeft WMR gevraagd om in het najaar van 2024, 2025 en 2026 bemonsteringen uit te voeren in de vaargeul naar Harlingen. Doel is daarmee het effect van mitigerende maatregelen van het baggeren en verspreiden van sediment in de Boontjes op het bodemleven en sediment te meten.
|
8a90e29415a8b7282e6f753c0f551bb8
|
dmponline.dcc.ac.uk
|
A. Describe the research project
|
List the individuals responsible for the following data management tasks.
|
Data collection Jack Perdon Data quality Jack Perdon, Babeth van der Weide Storage and backup Margriet van Asch, Babeth van der Weide Data archiving / publishing Jan Tjalling van der Wal Data stewardship / support Jan Tjalling van der Wal Any other role
|
8a90e29415a8b7282e6f753c0f551bb8
|
dmponline.dcc.ac.uk
|
B. Describe the data to be collected, software used, file formats and data size.
|
Please describe the data you expect to generate and / or use in the table below. Include reused existing data aswell (as these are files that you manage and store).
|
File contents Data type Software (Open) file format Estimated size of each file (range) Estimated number of files (range) data bemonstering bodemschaaf numerical Access 300 Mb 3 data bemonstering box-corer numerical Access 600 Mb 3 data sediment numerical excel 100 Mb 3
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8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
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D. Structuring your data and information
|
Give a (visual) representation of the folder structure you intend to use.
|
centrale databases: "W:\IMARES\Yerseke\Common\Data\Databases\CSO.accdb" "W:\IMARES\DATA\Benthos"
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8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
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D. Structuring your data and information
|
Describe the file naming conventions you intend to use. Please give one or multiple example(s).
|
We zullen de adviezen gegeven door WUR volgen (organizing files and folders- WUR)
|
8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
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G. Data archiving and publishing
|
What data will be published and made available for reuse via a data repository?
|
all data produced will be published in a data repository
|
8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
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G. Data archiving and publishing
|
Which metadata standard will be used to describe the data during internal archiving and / or depositing in a datarepository?
|
to be decided
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8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
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H. Data management costs
|
What resources (in time and / or money) will be dedicated to data management, data archiving or publication, andensuring that data is reusable? Indicate as well how these costs will be covered.
|
Staff time, related to importing data to central database, and bringing data online
|
8a90e29415a8b7282e6f753c0f551bb8
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dmponline.dcc.ac.uk
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Data Collection
|
What data will you collect or create?
|
We collect opinions and knowledge of 1000 citizens of Austria via an online survey.
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f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Data Collection
|
How will the data be collected or created?
|
The data will be collected by a professional survey company and the research team will resieve only anonymized date.
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Documentation and Metadata
|
What documentation and metadata will accompany the data?
|
The metadata will contain the full questionaire including the coding of the response options.
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Ethics and Legal Compliance
|
How will you manage any ethical issues?
|
All survey participants are required to provide informed consent before the data is submitted to the survey company. An experienced data manager from the Energyinstitute will scrutinize the survey for ethcial issues.
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Ethics and Legal Compliance
|
How will you manage copyright and Intellectual Property Rights (IPR) issues?
|
The foreseen research project is of pure academic interest and all results and collected data will be published without copyright and Intellectual Property Right issues.
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Storage and Backup
|
How will the data be stored and backed up during the research?
|
A professional survey company with a track record in comprehensive storage and backup of data will be selected.
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Storage and Backup
|
How will you manage access and security?
|
see above
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f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Selection and Preservation
|
Which data are of long-term value and should be retained, shared, and/or preserved?
|
All answers to the survey are of long term value and will be publicly shared. Any information potenially leading to the deanonymization of the participants is deleated by the survey company and will not be stored.
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Selection and Preservation
|
What is the long-term preservation plan for the dataset?
|
A dataset is published on https://zenodo.org/ .
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Data Sharing
|
How will you share the data?
|
A dataset is published on https://zenodo.org/ .
|
f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
Who will be responsible for data management?
|
The project's data manager Johannes Reichl is responsible for the data management and suitable resources for his respective duties have been forseen in the project budget.
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f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Responsibilities and Resources
|
What resources will you require to deliver your plan?
|
All resources required are time resources of the data manager.
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f9229afa46bfb33d7cbbb82ec73f440f
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dmponline.dcc.ac.uk
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Data description and collection or re-use of existing data
|
How will new data be collected or produced and/or how will existing data be re-used?
|
The ExSCIP feasibility trial generates new, primary data. The following data will be collected throughout the trial: ● Screening questionnaire (confirmation of diagnosis, Spinal Cord Injury Pain Instrument (SCIPI), confirmation of exoskeleton naivity, confirmation of stable medication regimen, confirmation of no unstable medical/psychiatric condition) ● Demographic data (age, sex, neurological level of injury, ASIA impairment score, etc). ● The full International Spinal Cord Injury Pain Basic Data Set Version 3.0 (ISCIPBDS 3.0) with items addressing pain classification, intensity, interference, mood and sleep. ● Feasibility outcome metrics; recruitment rates, programme adherence, attrition rates and reasons for dropout. ● Neuropathic Pain Symptom Inventory. ● EEG data ● Health related quality of life (EQ-5D-5L) questionnaires. ● Discrete choice questionnaire ● Bespoke ExSCIP health economic questionnaire items relating to; health resource and pharmacotherapy, work presenteeism and absenteeism ● Qualitative data based on focus group discussions and debriefing interviews. This data will be collected in-person by an independent assessor blinded to participants allocation via written questionnaires. Data will be entered into an electronic REDCAP database (password protected) by the researchers, supported by CSTAR at UCD. Security measures include password protected computers, firewall protection, file encryption and access rules, power failure/surge and malware protection. All data collected against each participant will be pseudomymised at point of entry into databases. All quantitative data will be inputted and cleaned in SPSS (version 29) from electronic or paper forms and analysed using this software. Qualitative data garnered from focus group exit interviews will be uploaded, stored and analysed in NVivo software.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data description and collection or re-use of existing data
|
What data (for example the kind, formats, and volumes), will be collected or produced?
|
It is estimated that the project will generate the following types of data: Type of data Collection procedure Purpose of data collection Data format Volume of data Quantitative (pain intensity and pain interference scores) Case report form, standardised questionnaires (Neuropathic Pain Symptom Inventory, ISCIPBDS 3.0, Numerial Rating Scale) To determine and compare the effects of an exoskeleton walking intervention and equally dosed relaxation program on neuropathic pain after spinal cord injury. .xlsx (Excel); .sav (SPSS 29) It is anticipated this data will be collected for 40 participants at 3 time points (baseline, post intervention and 6 month follow up). Quantitative (EEG biomarker) EEG recordings will be measured using the NeuroCONCISE 8 electrode device. Participants will be seated in a dimly lit room shielded from sound and stray electrical fields. Resting EEGs will be recorded with eyes open for 3 minutes followed by eyes closed for 3 minutes. There is evidence to suggest that EEG can serve as a useful biomarker for the presence of chronic neuropathic pain. Continuous NP is associated with an EEG power signal with an increase in theta band and high beta band along with a decrease in the high alpha, low beta band. It is anticipated this data will be collected for 40 participants at 3 time points (baseline, post intervention and 6 month follow up). Quantitative (Feasibility
* outcomes) Data will be collected on the following feasibility outcomes:
* Total number of eligible
* participants with moderate to severe neuropathic pain after SCI recruited.
* Recruitment rates disaggregated by SII and NRH
* channels (recruitment capacity at named sites).
* Trial uptake rates.
* Retention and follow- up/attrition rates i.e. those that provide data at 13 weeks and 6 months.
* Adherence with the
* programme over time (attendance and total number of steps taken).
* Any safety/adverse events.
* Feasibility of stratified randomisation.
* Feasibility of assessment procedures.
* Availability of baseline data required.
* Time needed to collect and analyse data. This data will be collected to determine whether progressing this feasibility trial to definitive trial across multiple centres is warranted and feasible. Threshold criteria for onward progression to a definitive trial is determined as the following:
* Successful intervention uptake, with recruitment rates of ≥35% of eligible rates.
* Loss to follow up/attrition rates ≤20%.
* Process evaluation and qualitative data that indicates that EXSCIP is
* an acceptable intervention to
* individuals with NP following SCI and to physiotherapists delivering the intervention, where no insurmountable barriers were
* identified.
* Safe and successful implementation of the EXSCIP intervention: no serious adverse
* events and average programme
* adherence of ≥ 80% of all sessions.
* A non-inferior effect is observed in comparison with the control arm
* and the Minimal Clinically Important Difference (MCID) for
* the NP pain intensity in an SCI population (1.74 points decrease on NRS) is observed within the 95% confidence interval for mean change for the intervention arm. .xlsx (Excel)
* Pain related measures will
* be collected for 40 participants at 3 time points as outlined above. The remaining data
* related to feasibility will be
* collected after delivery of the intervention. Quantitative (Health Economic Evaluation) Bespoke data collection tools will be prepared. These will include resource use and include work (paid and unpaid) absenteeism and presenteeism. participants. The intervention will be costed with consideration of time and resource use related to planning, training, implementation and running costs. Direct cost of the ExSCIP programme and average for each participant will be estimated. Downstream resource use and costs will be obtained from participants by means of a retrospective questionnaire. We will measure quality of life using the EQ-5D-5L questionnaire including quality-adjusted life years (QALYs), and assess the subsequent down- stream use and cost of health and social care resources. The available data will be presented in a cost-effectiveness framework to enable assessment of the ExSCIP programme’s value for money. The analysis will explore Value-of Information to describe the potential benefit from future research and in particular allow opportunity to explore how we might devise a discrete choice experiment in a future clinical trial. .xlsx (Excel); .sav (SPSS 29) It is anticipated this data will be collected for 40 participants at 3 time points (baseline, post intervention and 6 month follow up). Qualitative (Participants) Qualitative focus group discussions with participants will be conducted and recorded following the intervention to ascertain their experiences of the EXSCIP programme
* The qualitative semi-structured question schedule will be developed
* in collaboration with our PPI panel. A
* person unknown to the participants will complete the exit discussions. As perceived pain is multidimensional and often dependent on factors such as attitudes, self-efficacy and thoughts, inclusion of a qualitative study is important to inform additional development and improvement to the intervention. Key areas to be discussed will be;
* satisfaction with and acceptability of the EXSCIP programme,
* perceptions of exoskeleton use,
* barriers and facilitators to attendance and implementation
* and sustainability of a walking programme following intervention Transcripts (.docx); Audio recordings
* (.MP4, .AVI) This data will be collected in 3-4 focus groups consisting of 5-6 people (15-20 people total) after the delivery of the intervention. There will be
* 3-4 transcripts and audio recordings associated with
* this portion of the data
* collection. Qualitative (Staff) Qualitative focus group discussions will be conducted and recorded following the intervention with staff who delivered the EXSCIP
* intervention to evaluate
* physiotherapists’ perspectives of
* delivering an exoskeleton walking
* programme for pain. The following questions will be addressed in relation to the perspectives of staff who delivered the ExSCIP intervention:
* Beliefs
* Views on implementation
* Therapist burden
* Skill level required to deliver an intervention of this nature Transcripts (.docx); Audio recordings (.MP4, .AVI) This data will be collected in 1-2 focus groups consisting of 2-4 people total after the delivery of
* the intervention. There will
* be 1-2 transcripts and
* audio recordings
* associated with this portion of the data collection.
|
098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Documentation and data quality
|
What metadata and documentation (for example the methodology of data collection and way of organising data) willaccompany data?
|
An appropriate metadata standard will be used to describe the data. Zenodo will be used to preserve and share the research data after the project. On Zenodo, each record contains a minimum of mandatory terms, with optionally additional DataCite recommended terms and Zenodos enrichments to enable discovery and re-use. Metadata will be openly licensed with a CC0 license. The data collected from this study will be stored on UCD’s secure institutional infrastructure for a total of 10 years as required by UCD’s research data management policy. Personal data will be pseudonomised and the pseudonomised key will be stored for a total of four years, within a separate folder. The key will be deleted after four years and data will be stored as anonymised. The non- specific personal data and data concerning health will be stored on a separate encrypted Google Drive folder. All data will be deleted after 10 years. The documentation for this study that will be stored are as follows: ● Consent form ● Participant Information Leaflet ● Screening Questionnaire ● Ethical Approval This will be accompanied by a README text file (.txt) which will aid in explaining the datasets and linking the documentation. It will outline the following: ● Name of dataset ● Name of researchers involved in data acquisition ● Brief description of the dataset ● Contact information of the PI for queries related to data acquistion or the protocol. ● References of published works. ● Conflicts of interest. Other text files (.txt) will include: ● CLINICAL_INFO.txt which will be defined age, neurological level of injury, ASIA impairment scale and number of each participant. No identifiable personal data will be provided. ● RECORDS.txt file where is defined the names of all data files and documents that create the dataset with a brief description of what contains each file/document. ● EMG_FILE_INFO.txt file describing the software, devices used to collect the electromyography data, characteristics of the signal (frequency, sample size), and the structure of the file. ● USAGE.txt file text where is described what the data has been used for and possible ways and disciplines where it is useful to use this data. Suggestions of tools to change file formats and recommended software to use will also be mentioned.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Documentation and data quality
|
What data quality control measures will be used?
|
Data collection will use standardized tools where possible and research staff will be trained in their use. This will help to ensure uniformity in data collection, minimize data omissions and streamline collection and storage process. Examples include: ● Pain intensity and interference will be measured using the ISCIPBDS 3.0 ● Health related quality of life (HRQOL) will be measured using the EQ-5D-5L ● Neuropathic pain symptom severity will be measured using the NPSI ● Screening questionnaire will be completed over the phone to confirm study eligibility criteria. ● Anthropometric measurements (height, weight, hip width, leg length) will be assessed in person to confirm compatibility with the exoskeleton. Data collection and data management training for research staff by CSTAR is included, standardising both the collection and the filing/storing of all data and meta-data. Published data collection tools with validity and reliability will be utilised specific to SCI NP, where available. Published standards for the design, conduct and reporting of trials (e.g. CONSORT, SPIRIT, etc) will be used, optimising validity. Researchers will be certified for Research Integrity Training; Good Clinical Practice, Data Management Training and GDPR Fundamentals. Research data will be handled in line with data protection statutory requirements. Existing institutional infrastructure will be used for the storage of electronic research data, using both encryption and password protection for security purposes with regular back-ups. Approximately 10% of paper-based proforma will be independently cross-checked against electronic files foraccuracy. Data discrepancies will be discussed with the researchers and amended accordingly. Assoc. Professor Ricardo Segurado will provide training on data management to the researchers.
|
098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Storage and backup during the research process
|
How will data and metadata be stored and backed up during the research process?
|
All members of the research team will install operating system and application updates when they are available, install Sophos endpoint protection software provided by UCD and use a secure network connection when connected to the Internet. While on campus either the cabled network or the Eduroam Wi-Fi network will be used and when off-site the Staff Virtual Private Network (VPN) will be used to secure the network connection . Data will be entered into an electronic database (password protected) by the researcher, supported by CSTAR at UCD. Security measures include password protected computers, firewall protection, file encryption and access rules, power failure/surge and malware protection. Existing institutional infrastructure (Google Drive and Novell Drive (Net Storage)) will be used for the storage of electronic research data, using both encryption, password protection and Multi-Factor Authentication for security purposes with weekly back-ups to both google drive and external hard drives.
|
098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Storage and backup during the research process
|
How will data security and protection of sensitive data be taken care of during the research?
|
Ethical approval is in place from UCD HREC and NRH HREC. All research will be guided and conducted in line with the UCD Policy on Research Ethics, UCD Code of Good Practice in Research with Humans and Animals and UCD Research Integrity Policy. Written informed consent will be obtained from every participant for data collection and any future use of data prior to collection of any data. When transferring data between users, HEAnet FileSender will be used as a secure application which provides for end-to-end encryption. Data will be entered into an electronic database (password protected) by the researcher, supported by CSTAR at UCD. Security measures include password protected computers, firewall protection, file encryption and access rules, power failure/surge and malware protection. 1 year after the conclusion of the project, the master sheet will be destroyed and anonymised files will be deposited in a trusted data repository (e.g. Zenodo) with a permanent identifier (DOI) and available to the wider research community with an open license (CC0). Participants will have an opportunity to consent or not to anonymised data archiving. In line with HRB Open Research Policy, repositories hosting the data will be cited in research papers. All obtaining, use and storage of data will be in line with GDPR legislation and UCD data protection policy. All researchers will be certified for Research Integrity Training, Data management training and GDPR fundamentals.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Legal and ethical requirements, codes of conduct
|
If personal data are processed, how will compliance with legislation on personal data and on security be ensured?
|
All collection and future use of data will be fully in line with the terms of written informed consent obtained from participants. All collection and future use of data will be guided by and in line with GDPR regulations and UCD's data protection policy. All personal data will be pseudonymised/anonymised when transferred from case report forms to electronic softwares (REDCAP, Google Drive, Novell Drive, SPSS, NVIVO, etc.) Data collection from participants will be completed by an independent assessor not involved in the delivery of the interventions. Associate Professor Ricardo Segurado from UCD Centre for Support and Training in Analysis and Research (CSTAR) will be overseeing that data collection, data use and data analysis is conducted in line with all aforementioned relevant legislation and policies including providing training on data management to all researchers who will be involved in this activity.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
|
Legal and ethical requirements, codes of conduct
|
How will other legal issues, such as intellectual property rights and ownership, be managed? What legislation isapplicable?
|
Participants in this study who provide their personal data will be owners of their data. When providing written informed consent, they provide permission to the research team for compliant collection, use and sharing of their data in line with what was agreed within the consent process. Publication of research articles/thesis, presentation of posters and any other dissemination of information associated with this research to third parties external from UCD will be compliant with terms and conditions of research funding provided by the HRBI, the UCD authorship policy and the UCD IP policy.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data sharing and long-term preservation
|
How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?
|
An inter institutional data sharing agreement will be developed and approved by UCD legal to allow data to be shared with RCSI for the health economic evaluation work package of this project. This will be a controller-processor agreement. A data sharing agreement (controller-controller) will also be developed with the National Rehabilitation Hospital (NRH) to enable sharing of health demographic data pertaining to participant's injury if the participant does not know this information themselves (time since injury, neurological level of injury and ASIA impairment score). All data sharing will be conducted using secure, encryption protected HEAnet software. Data and the encryption key will be stored on separate drives (i.e. one on Novell Drive, one on Google Drive) and the encryption key will be sent via separate means to the data to minimise any risk of data breaches. Data sharing agreements are with organisations within Ireland and the EU so no restrictions or embargos apply. However, data sharing will be implemented in line with GDPR legislation namely the data minimisation principle. This data will be retained for a minimum of 10 years in line with UCD's RDM policy. A Data Availability Statement relating to underlying data needed to validate the results presented in scientific publications will be included with publication outputs at the time of publication or as soon as possible. At the end of the project, data selected for preservation will be archived in Zenodo repository. As outlined above, metadata and documentation describing the data and research process will also be made available, in compliance with the FAIR data principles.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data sharing and long-term preservation
|
How will data for preservation be selected, and where data will be preserved long-term (for example a data repositoryor archive)?
|
1 year after the conclusion of the project, the master sheet containing patient data will be destroyed and anonymised files will be deposited in a trusted data repository (Zenodo) with a permanent identifier (DOI) and available to the wider research community under a CC0 license. Participants will have an opportunity to consent or not to anonymised data archiving. In line with HRB Open Research Policy, repositories hosting the data will be cited in research papers. This data will be retained for a minimum of 10 years in line with UCD's RDM policy.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data sharing and long-term preservation
|
What methods or software tools are needed to access and use data?
|
It is not envisaged that any special software will be required to access the datasets on Zenodo.
|
098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data sharing and long-term preservation
|
How will the application of a unique and persistent identifier (such as a Digital Object Identifier (DOI)) to each data setbe ensured?
|
Anonymised files will be deposited in a trusted data repository (Zenodo) which automatically assigns a permanent identifier (DOI)
|
098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data management responsibilities and resources
|
Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?
|
UCD and the PI Assoc Professor Olive Lennon will be the data controllers with responsibility for the data collection, storage, use as per consent, and compliance with FAIR data principles supported by UCD data protection champions. CSTAR will be responsible for data and metadata management. DMP's and data sharing agreements will be curated for UCD, NRH and RCSI who will be involved in data management. This will be done in collaboration with the Data Protection Officer (DPO) of each institution. The PI will be responsible for implementing and updating the DMP as necessary.
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098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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Data management responsibilities and resources
|
What resources (for example financial and time) will be dedicated to data management and ensuring that data will beFAIR (Findable, Accessible, Interoperable, Re-usable)?
|
Within the scope of the grant provided by the HRB, funding has been allocated to acquiring the necessary hardware and software for the creation & reuse of data and deposition & preservation and to prepare the data for sharing/preservation (data curation). Funding has also been allocated to the costing of a repository for future use of data. Breakdowns are as follows: Data science costs (use of CSTAR resources): €1800 Data collection and management training provided by CSTAR: €2250 Data and metadata management (CSTAR): €3750 Ethics application and approval (UCD Clinical Research Centre): €1888 GDPR compliance/DPIA approval (UCD CRC): €2350
|
098876b7134f53965c40dc7c19bad162
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dmponline.dcc.ac.uk
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General Information
|
Name applicant and project number
|
‘Labour Integration of Somali Women in Western Europe, 1980-2022’ by Yowali Kabamba
|
abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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General Information
|
Name of data management support staff consulted during the preparation of this plan and date of consultation.
|
Research Data Management Support from Utrecht University
|
abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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1. What data will be collected or produced, and what existing data will be re-used?
|
If new data will be produced: describe the data you expect your research will generate and the format andvolumes to be collected or produced.
|
Two types of new data will be produced. 1. A questionnaire-based survey on migration history, integration process and labour integration of Somali men and women residing either in Britain, Belgium or the Netherlands. It is expected the survey will reach at least 100 respondents. The data will be formatted into a spreadsheet (.xlsx) and anonymised, so respondents cannot be identified. 2. Semi-structured interviews on migration history, integration process and labour integration of Somali men and women residing either in Britain, Belgium or the Netherlands. 45 to 60 interview transcripts (.doc) are expected, of interviews lasting up to two hours. Audio recordings will be deleted after transcription.
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abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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1. What data will be collected or produced, and what existing data will be re-used?
|
How much data storage will your project require in total?
|
It is expected the data storage will reach over 10 GB with the audio recordings of the interviews, which will however be deleted after transcription.
|
abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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2. What metadata and documentation will accompany the data?
|
Indicate what documentation will accompany the data.
|
1. A "readme" text file (.doc) will be produced alongside the spreadsheet. It will include the survey questions and corresponding question codes in the spreadsheet. 2. A "readme" test file (.doc) will be produced alongside the spreadsheet. It will include the date and location of each interview.
|
abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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3. How will data and metadata be stored and backed up during the research?
|
Describe where the data and metadata will be stored and backed up during the project.
|
1. The questionnaire's answers will be stored under the researcher's Qualtrics account. Once the survey has been closed, all the data will be downloaded and saved onto Utrecht University's networked storage One Drive. 2. The audio recordings of the interviews will be stored first on the researcher's phone. The audio files will then be transferred and saved onto Utrecht University's networked storage One Drive.
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abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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4. How will you handle issues regarding the processing of personal information and intellectual property rights and ownership?
|
How will ownership of the data and intellectual property rights to the data be managed?
|
Only the members of the research team (the principal investigator and the supervisor) have access to personal data. These members are obliged to keep the data confidential. We will make the personal data anonymous as much as possible, after which we may share it with other researchers or organizations. The anonymized data may be used by other SCOOP researchers, who are all bound by the Collective Bargaining Agreement (“CAO”) of Dutch universities.
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abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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5. How and when will data be shared and preserved for the long term?
|
When will the data be available for re-use, and for how long will the data be available?
|
Anonymized personal data will be stored on One Drive, a well-secured computer system of Utrecht University. Dutch universities have agreed to keep these data for at least 10 years. Other researchers can then check whether we conducted our research properly. We may pass the data on to other researchers.
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abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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5. How and when will data be shared and preserved for the long term?
|
In which repository will the data be archived and made available for re-use, and under which license?
|
Our data package will also be deposited in an online SCOOP data repository and accessible to other SCOOP researchers.
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abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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6. Data management costs
|
What resources (for example financial and time) will be dedicated to data management and ensuring that data willbe FAIR (Findable, Accessible, Interoperable, Re-usable)?
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All associated costs are shouldered by the SCOOP network.
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abc47cb43ed072d4fc182c423ba86952
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dmponline.dcc.ac.uk
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1. General features
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Please fill in the table below. When not applicable (yet), please fill in N/A.
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DMP template version 30 (don't change) ABR number (only for human-related research) n.a. METC number (only for human-related research) n.a. DEC number (only for animal-related research) n.a. Acronym/short study title DysplaCT Name Research Folder 22U-0170_DysplaCT Name Division Heelkundige specialismen Name Department Orthopedie Partner Organization St Maartens Kliniek Nijmegen Start date study 15-02-2023 Planned end date study 15-02-2025 Name of datamanager consulted* Nivard Koning Check date by datamanager 28-3-2023
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
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2. Data Collection
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Give a short description of the research data.
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Subjects Volume Data Source Data Capture Tool File Type Format Storage space Human 200 PACS/CT CT-scanner Imaging .dcm 150-1000 GB Human 200 eCRF SPSS measurements .sav <1GB
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
|
2. Data Collection
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Describe who will have access to which data during your study.
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Type of data Who has access Raw CT-scans (without identifying data)* N. Koning (data manager) B.C.H. van der Wal (Principal investigator) M.F.T. Hüsken (Coordinating researcher) J. Magre (researcher) Measurements derived from CT-scans N. Koning (data manager) B.C.H. van der Wal (Principal investigator) M.F.T. Hüsken (Coordinating researcher) J. Magre (researcher) V. Arbabi (researcher) Explanation: * The raw CT-scans will be ripped of all direct and indirect identifying data by the radiology department of the St Maartens clinic Nijmegen or UMCU. The CT scans will be coded according to the order of entry. There will not be a key-linking table to enable patient re-identification.
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
|
2. Data Collection
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Specify data management costs and how you plan to cover these costs.
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Type of costs Division ("overhead") Funder Other (specify) 1. Time of data manager x 2. Storage and archiving x* 3. Data Capture Tool license fee (SPSS) x Explanation: * The cost of the storage in the Research Imaging Architecture (RIA) will be funded through a larger project on hip dyplasia (3D-Hip)
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
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2. Data Collection
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State how ownership of the data and intellectual property rights (IPR) to the data will be managed, and whichagreements will be or are made.
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Sint Maartens Kliniek Nijmegen is the owner of the raw CT scans that originate from their hospital. The UMC Utrecht is allowed to use the CT scans to collect data for this study and to analyse the dysplastic pelvic for future treatment developments. UMC Utrecht is and remains the owner of all collected data for this study. Our data cannot be protected with IPR, but its value will be taken into account when making our data available to others. This is contractually agreed upon in a Data Transfer Agreement.
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
|
3. Personal data (Data Protection Impact Assessment (DPIA) light)
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Will you be using personal data (direct or indirect identifying) from the Electronic Patient Dossier (EPD), DNA, bodymaterial, images or any other form of personal data?
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The original scans are tranfered and stored in a RIA-container without personnel data nor re-identifying key. Name, date of birth or any other high risk specifics from these patients will not be available to the researchers.
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
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3. Personal data (Data Protection Impact Assessment (DPIA) light)
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Describe how you manage your data to comply to the rights of study participants.
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The data will be transferred and stored using the Research Imaging Architecture (RIA) of the UMC Utrecht. The raw data in terms of the CT scans will be handled confidentially and will be coded according to the order of entry. CT-scan from the Sint Maartens Clinic will be transferred without identifying data. Only the clean Pelvic CT scans will be available for the research team. Confidentiality will be maintained at all times, participant information will not be available for the researchers and can therefore not be disclosed to third parties. Derived data and measurements will be reused and stored in secure research folder on network disc of the division. All generated (meta)data will be stored in a designated secure research folder with RFS for access control. There wil be no key-linking table to enable patient re-identification, so patient data will never again be accessible. Right of Access We have to refuse participant's right of access. It wil not be possible, because there will not be a key to re-identify patients. Right of Rectification We have to refuse participant's right of rectification. It wil not be possible, because there will not be a key to re-identify patients. Right of Objection A “Objection check” will be performed during selection of the patients and before transferring to the UMC Utrecht. Right to be Forgotten Removal of collected data from the research database cannot be granted because this would result in a research bias.
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828856ecd121a60c206ba53ff2082165
|
dmponline.dcc.ac.uk
|
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