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Storage and backup
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How is storage and backup of data and metadata safeguarded during the research process?
|
The main database is hosted by Registercentrum Norr at Region Västerbotten, with support from Umeå University ITS. The database is kept behind a firewall and password protected. Additional databases are stored in a secure storage area ("Trygg Filyta") hosted by Umeå University, with a backup on a non-network-connected hard disk kept in a locked room at the Department of Clinical Sciences. A full time data manager is responsible for secure data handling. Description in Swedish of 'Trygg Filyta': ’Trygg Filyta’ utgör en säker och lokal lagringsplats/filyta för digitala dokument. Servermiljö Underliggande servermiljö ligger i Umeå universitets lokala hallar och innanför ett skalskydd, larm och inpasseringskontroll, dit bara de av ITS utsedd personal har access. Servers är logiskt separerade och innanför perimeterskydd (Brandvägg). Användare De användare som ska ha access till Trygg Filyta måste ha Swamid AL2 samt multifaktorautentisering(MFA) aktiverat. Inloggning Inloggning sker via webgränssnitt (TLS) och MFA, dvs. användarkonto + lösenord + engångskod från en annan enhet. All inloggning och filöverföring är krypterad via TLS. Access Accesstilldelning styrs helt av informationsansvarig för respektive filyta. Behörigheterna på dokument kan vara fullständiga, redigera eller läsa. För att fler ska få access till ytan måste informationsansvarig beställa access för dessa användare som också de måste uppfylla kravet på Swamid AL2 Dokumenthanteringssystem Tjänsten som används för att underlätta dokumenthanteringen är SharePoint 2019, som är ständigt säkerhetsuppdaterad. SharePoint 2019 är konfigurerad enligt rekommendationer för hög säkerhet ex. begränsat möjlighet att dela dokument. All åtkomst loggas så att det finns spårbarhet vem som har laddat upp, sökt, öppnat eller laddat ned en fil. Backup Backup tas dagligen. Vid återläsning av backup krävs en dekryptering för åtkomst till data.
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f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Storage and backup
|
How is data security and controlled access to data safeguarded, in relation to the handling of sensitive data andpersonal data, for example?
|
The main database is kept behind a firewall and password protected. Additional databases are stored in a secure storage area ("Trygg Filyta") hosted by Umeå University, with a backup on a non-network-connected hard drive, kept in a locked room at the Department of Clinical Sciences. A full time data manager is responsible for secure data handling. Personal data (name, personnummer, address) is kept separate from the main database, which uses only study ID.
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f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Legal and ethical aspects
|
How is data handling according to legal requirements safeguarded, e.g. in terms of handling of personal data,confidentiality and intellectual property rights?
|
All data collection and data handling is approved by the Ethical committee and by informed consent from the study participants. All data handling is done in accordance with GDPR.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Legal and ethical aspects
|
How is correct data handling according to ethical aspects safeguarded?
|
All data collection and data handling is approved by the Ethical committee and by informed consent from the study participants. All data is removed upon request from study participants.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Accessibility and long-term storage
|
How, when and where will research data or information about data (metadata) be made accessible? Are there anyconditions, embargoes and limitations on the access to and reuse of data to be considered?
|
Metadata will be published at the Swedish National Dataservice (SND) repository within the project period.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Accessibility and long-term storage
|
In what way is long-term storage safeguarded, and by whom? How will the selection of data for long-term storage bemade?
|
Long-term storage is planned for all data. Our data manager is responsible for data storage, in collaboration with Registercentrum Norr, Region Västerbotten and Umeå University ITS.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Accessibility and long-term storage
|
Will specific systems, software, source code or other types of services be necessary in order to understand, partake ofor use/analyse data in the long term?
|
Long term storage of data will be done in generic formats for easy access also in the future.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Accessibility and long-term storage
|
How will the use of unique and persistent identifiers, such as a Digital Object Identifier (DOI), be safeguarded?
|
Unique and persistent identifiers of individual data points are only available to study coordinators and the data manager within our closed database. DOIs for datasets will be provided by SND.
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f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Responsibility and resources
|
Who is responsible for data management and (possibly) supports the work with this while the research project is inprogress? Who is responsible for data management, ongoing management and long-term storage after the researchproject has ended?
|
The project data manager is Richard Lundberg. Yulia Blomstedt is responsible for the databases within Registercentrum Norr. Dan Harnesk is responsible for information security at Umeå University.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
Responsibility and resources
|
What resources (costs, labour input or other) will be required for data management (including storage, back-up,provision of access and processing for long-term storage)? What resources will be needed to ensure that data fulfilthe FAIR principles?
|
A full time data manager employed by the PI is required. Access to secure servers at Region Västerbotten and Umeå University is required. Resources are needed to publish metadata according to the FAIR principles.
|
f6be7eaf4af46c17081dcadf510087b2
|
dmponline.dcc.ac.uk
|
1. General features of the project and data collection
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Project leader contact details
|
Prof. Dr. Sandra Van Dulmen Coordinator research program Communication in Healthcare at Nivel; endowed professor 'Communication in healthcare', Radboud university medical center, the Netherlands; adjunct professor at the University of Borås, Sweden email: [email protected]; tel.: 0302729703
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e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
1. General features of the project and data collection
|
I have composed my DMP with the assistance of a data stewardship (or management) expert. List his or her name,function, organisation/department, phone number and email address.
|
drs. Carlijn Hofhuizen Data steward/coordinator ‘ondersteuningscluster panel- en surveyonderzoek’ Nivel +31(0)302729781 [email protected] The data steward participated in the FAIRdata workshops in the ZonMw Covid-19 bottom-up. funds. She was involved as data- steward in two other ZonMw projects. Furthermore, the data steward has 11 years of experience in collecting research data, data quality management, process control and privacy policy. Mercedes Beltrán, M.I. (Mercedes) Data steward, Faculty of Science, Utrecht University +31 6 81031356 [email protected] Trained by Research Data Netherlands (RDNL) and Landelijk Coordinatiepunt Research Data Management (LCRDM). GCP Certified (Good Clinical Practice).
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e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
1. General features of the project and data collection
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I will be reusing or combining existing data, and I have the owner's permission for that.
|
Data (pseudonomyzed transcripts of recorded medical visits) were obtained using consent as legal basis with permission for data re- use. This is unpublished data collected by the Department of informatics at Utrecht University. The original data are safely stored at Nivel. There are no technical restrictions nor need for data conversion, data are already in the format needed for re-use.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
1. General features of the project and data collection
|
I am a member of a consortium of 2 or more partners. Clear arrangements have been made regarding datamanagement and intellectual property. (also consider the possible effect of changes within the consortium on issuesof data management and intellectual property)
|
The means and rights of consortium members to the data and software is delineated in a consortium agreement (Articles 9, 11 and Appendixes 2) and Nivel privacy regulation ‘Databank Communicatie in de Zorg’ Appendix 3 of the consortium agreement.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
1. General features of the project and data collection
|
During the project, I will have access to sufficient storage capacity and sites, and a backup of my data will beavailable. (please elaborate briefly)
|
Questionnaire data are stored in the secured environment on the datacenter of PQR (IT service provider). Access is reserved for authorized employees only. The data backup runs daily. The daily back-ups are incremental and stored at 2 different locations, the original data is hosted in the data center of PQR. This guarantees long term storage of the data, as well as sufficient storage space. The original video- and audio-recordings will be stored in the same secured environment, however, due to the sensitive nature of these files, these are only accessible from a PC on the premises of Nivel. Permission to access the files can only be granted with an agreement. For the purpose of generating automated summarizations of medical visits, a technical programmer from Utrecht University will develop and implement a stand-alone transcription and pseudonymization service at Nivel. This transcription and pseudonymization application will be executed for the audio/video data by a Nivel project member at the Nivel building. Posteriorly, pseudonymized data (pseudonymized transcripts of recorded visits) will be shared with co-applicants at Utrecht University, Department of Informatics. WP1 Utrecht University (Department of Informatics) will receive de-identified data (transcripts of audio-recordings and written reports of geriatric visits). All data will be stored and preserved in Yoda. Yoda is Utrecht University's institutional research data repository, registered as such with re3data.org. Yoda complies with Utrecht University's Information Security policy for data classified as public, internal use or sensitive. Data along with its metadata will be shared within a closed user group, accessible to authorized users. All Yoda data are stored in at least two geographically spread locations. The data are stored and transmitted in encrypted format. Yoda complies with Utrecht University's Information Security policy for data classified as public, internal use, sensitive and critical. Data transfer between Nivel and UU will be done via Yoda. A specific research folder will be created in Yoda environment for data sharing as Yoda enables collaboration with partners outside the UU.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
2. Legislation (including privacy)
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I will be doing research involving human subjects, and I will protect my data against misuse.
|
Privacy by design will be incorporated in the project using both data-oriented and process-oriented strategies. Only personal data connected to the research purpose will be collected. Personal data will be stored securely at Nivel premises (see 1.10). Nivel questionnaire data are stored in the secured environment of the datacenter of Nivel’s IT service provider. Access is reserved for authorized employees only. The original video-recordings will be stored in the same secured environment, however, due to the sensitive nature of these data, these are only accessible from a PC on the premises of Nivel. To this purpose, Nivel hosts a special, secured room where the privacy-sensitive video-recordings can be accessed and coded. Permission to access the recordings can only be granted after researchers, only those involved in the particular project, have signed a nondisclosure agreement. A data steward and a statistician participate in the project to make sure regulations, storage and access are handled in the right way. For WP1 Audio data will be transcribed, pseudonomyzed and masked using pseudonymization and masking software developed by the Department of Informatics at Utrecht University. The application of the transcription and pseudonymization software will be executed for the audio/video data by a Nivel project member at the Nivel building. The pseudonymization key will be kept separately to the research data. Personal data (pseudonymized transcripts of audio files and pseudonymized written reports) will be transferred securely between UU and Nivel using Yoda Repository, where data are stored and transmitted in encrypted format. Yoda complies with Utrecht University's Information Security policy for data classified as public, internal use, sensitive and critical. Access to these data will be controlled by the responsible researcher at UU via Yoda. Only restricted group members will have access to personal data. A complete privacy risk assessment regarding the processing of personal data at Utrecht University in WP1 will be performed together with a data steward and privacy officer of the Faculty of Science at Utrecht University.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
3. Making data findable
|
The data collection of my project will be findable for subsequent research. E.g., on a catalogue, a web portal, orthrough the search enginge of the repository (note: this is key item 3, which you should report to ZonMw at the endof your project).
|
Our research uses the research data management systems of Nivel for the storage and management of video recordings and questionnaires, and the Yoda system of Utrecht University (yoda.uu.nl) for the storage of pseudonymized transcripts and derived data. WP 1 For WP1, Utrecht University will publish project metadata and de-identified, aggregated data, where possible, in Yoda repository (yoda.uu.nl), in compliance with the FAIR principles and will be made findable via its DOI persistent identifier. Software developed at the UU will be developed on a git-based code repository. Software documentation and partial code will be made available in archive like Zenodo, supporting software citation (DOI) and to increase findability and visibility we will use a software registry, the Research Software Directory (https://research-software-directory.org/ ).
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
4. Making data accessible
|
Once the project has ended, my data collection will be publicly accessible, without any restrictions (open access).
|
Due to the characteristics of the collected data (personal data from patients, caregivers, health practitioners) only project metadata and de-identified, aggregated data (where possible) will be published, so that the data is not tracible to individual respondents. Access to data will be done upon request and under restricted access. Request for access to the data have to be approved by the steering committee. The steering committee will take into account: - the nature of the research - the quality of the requiring researchers - the nature of the requested data - if the interest of applicants can be harmed - the planning of applicants’ own publications Privacy sensitive data will not be shared.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
4. Making data accessible
|
I have a set of terms of use available to me, which I will use to define the requirements of access to my datacollection once the project has ended (please provide a link or persistent identifier; also note that this is a key item 4,which you should report to ZonMw at the conclusion of your project).
|
- The application does not interfere with other current or planned activities - The application does not harm the interests of the participants - The requested data is suitable for answering the relevant research questions - The results of the research must be publicly accessible - The applicant must provide prior access to the draft publication, and allow all consortium partners 30 days for commenting on the publication - At least one employee of consortium partners had to be actively involved in the publication - Consortium partners and funder mentioned as source in the publications - The end product will contain a short privacy section, provided by Nivel A set of term for access to data collection is delineated in Article 10 of the collaboration agreement.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
6. Making data reusable
|
I have a number of selection criteria, which will allow me to determine which part of the data should be preservedonce the project has ended. (see also question 1.9 and 6.1)
|
Data that contain privacy sensitive information will be stored separately, and destroyed after the project has ended apart from the recordings themselves which are stored at Nivel in conformity with Nivel regulations, without deadline.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
6. Making data reusable
|
Once the project has ended, I will ensure that all data, software codes and research materials, published orunpublished, are managed and securely stored. Please specify the period of storage.
|
All software codes and research materials will be stored for at least 10 years after the end of the project. The audioand video- recordings of geriatric visits will be stored at Nivel without any deadline.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
6. Making data reusable
|
Data management costs during the project and preparations for archival can be included in the project budget.These costs are:
|
Costs aren't specified for this project, but are covered in the standard working processes of Nivel projects. For WP1, Utrecht University will cover the costs for data storage and preservation in Yoda.
|
e61b1905d0b22b730c4375de9007f87d
|
dmponline.dcc.ac.uk
|
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?
|
Data are recorded by GPs during the consultation with their patients with the use of a PMS. Each GP practice will have a server on which they save the database including all PMS tables. To extract data, upload to the CARA data models and visualise through the dashboards, CARAconnect was created . The data extraction and loading process encompasses selecting relevant data from the practice database, data de-identification, and de- identified data upload to the CARA remote servers. In order to conduct this process in an automatic, structured, and secured way, a desktop application was developed to streamline this task and assist the GP. CARAconnect was envisaged as an easy-to-use application once the practice was registered. The link to download CARAconnect is sent in an email to the practice secure email account (see CARA registration process below) and can easily be downloaded and initiated by a double click. Upon activation, CARAconnect identifies the practice server(s). On the GP server, the database is identified and selected fields from different tables are automatically extracted and securely uploaded to the infrastructure and processed before saving into the new data models during the data transformations steps. At each stage, confirmation by the GP is requested to start extraction and to finalise and upload/send the data. Through extensive exploration and elimination, a basic understanding of practice databases was developed, which was tested with a reference (anonymous) dataset to finalise specific tables needed to fulfil the data model requirements. CARAconnect facilitates the secure data extraction process based on the variables and tables identified.
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
dmponline.dcc.ac.uk
|
Data description and collection or re-use of existing data
|
What data (for example the kind, formats, and volumes), will be collected or produced?
|
coded diagnosis medication prescribed date of consultations
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
dmponline.dcc.ac.uk
|
Storage and backup during the research process
|
How will data and metadata be stored and backed up during the research process?
|
Procedures, data models, code, information etc (no real data), is shared on the CARA GitHub channel. GP Data will be stored on ICGP servers.
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
dmponline.dcc.ac.uk
|
Storage and backup during the research process
|
How will data security and protection of sensitive data be taken care of during the research?
|
The CARA network registration process for GP practices follows a well-defined workflow to ensure secure and efficient onboarding. Initiating the registration, new practices provide necessary details, and the system validates that the email is associated with the closed and secure email service adopted in Irish general practice and hospitals as the primary mechanism for secure communication between health systems (hospitals, laboratories, general practices, pharmacies). Upon entering the registration details, aone-time password (OTP) is generated and sent via email to the provided secure email address. Users are required to enter the OTP within a specified time limit. In case of delay, an option to regenerate a new OTP is available. Following successful OTP validation, users proceed to fill out the registration form, where confirmation of terms and conditions (GP agreement) is a prerequisite before finalising the registration. The GP agreement includes a detailed list of the data that will be extracted, an explanation of the aggregated use of this data for practice comparisons and for research purposes. Afterwards, an email is sent to the secure email address, facilitating the download of the CARAconnect application. The users can subsequently login using their registered credentials, ensuring a seamless and secure experience throughout the CARA network registration and login process. At every subsequent data upload, the GP agreement has to be re-confirmed. GP can only register with their health mail account. Healthmail is a secure clinical email service that allows health care providers to send and receive clinical patient information in a secure manner. The service is provided by the Primary Care Directorate of the HSE and is managed by eHealth Ireland and supported by the ICGP and the Irish Pharmacy Union. Healthmail is a closed mailing system. CARA has a healthmail account and can send GPs mails from this account.
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2e26f2953eb2ae6c10b86c84a9fd65c3
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dmponline.dcc.ac.uk
|
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?
|
CARAconnect extracts de-identified data from the practice database and ensures data security through a practice specific login- based access with 2-factor-authentication. GPs can view their practice data but are only allowed to view aggregated practice data from all other participating practices to avoid possible identification of another practice. Uploads are for a static period to irrevocably de-identify the practice data. Any new data upload overwrites previously uploaded data. Data extraction does not include any patient identifiers or free text, nonetheless, specific technical identifiers needed to link together data in different tables are hashed and extracted. As combinations of specific variables with other external identifiable data sources may potentially lead to identification, two additional processes were applied to facilitate the use of specific technical identifiers to link data in different tables: ● Salted hashing is unidirectional encryption and decryption is almost impossible. Salting introduces an additional random part (a set of strings of fixed length) to a hash function to create a one-way function. The random part remains the same during extraction but is unique for every extraction. ● k-anonymisation is applied to the data from all other practices, with k set at 5. This guarantees that a minimum of 5 similar patients are included in any comparison (between practice) visualisation. A k-anonymised dataset implies that each record is de- identified from at least k - 1 other. To accommodate the patients’ right to object to the processing of personal data, which provide the option to exclude their data from data processing for research purposes in accordance with General Data Protection Regulation (GDPR) requirements, a data entry field was identified in the PMS to indicate the exclusion of a record.
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
dmponline.dcc.ac.uk
|
Legal and ethical requirements, codes of conduct
|
What ethical issues and codes of conduct are there, and how will they be taken into account?
|
Legal basis for processing: Article 89 of GDPR. Section 42s (1)(b); 42 (2) and 42 (3) of the DPA 2018. The processing of Article 9 type data (including health data) requires that a condition in Article 9 must be found; In this case the Art 9 ground will be ‘is necessary for reasons of substantial public interest’. As explicit individual level consent would be impossible to obtain this research will require a consent declaration from the Health Research Consent Declaration Committee (HRCDC).
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
dmponline.dcc.ac.uk
|
Data sharing and long-term preservation
|
How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?
|
Data requests from researchers will be considered by the CARA board (CARA team members, ICGP members and GP/patient representative) and a platform, application form and procedure will be designed. To be finalised (and updated) by the end of 2024.
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
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)?
|
See procedures outlined in application process (CARAnetwork.ie)
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2e26f2953eb2ae6c10b86c84a9fd65c3
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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)?
|
CARA team led by Prof Akke Vellinga, UCD
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2e26f2953eb2ae6c10b86c84a9fd65c3
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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)?
|
Ongoing investment
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2e26f2953eb2ae6c10b86c84a9fd65c3
|
dmponline.dcc.ac.uk
|
Data Collection
|
What data will you collect or create?
|
Productivity data, growth rate data, environmental data. Experimental measures data, tabular data and models. Models data to microalgae culture in natural environment are long term useful data. No data will be reused or purchased Data volume: Gb, raw and procesed data. No need to include additional costs Data format: text (.txt), open format
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
|
Data Collection
|
How will the data be collected or created?
|
Collected by direct measurement. Standar for software development quality data: ISO33000 Standar for data quality control, evaluation and improvement: ISO25012
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
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Documentation and Metadata
|
What documentation and metadata will accompany the data?
|
The data will be accompany with strains metadata. The metadata will be created manually.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
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How will you manage any ethical issues?
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We own the authorship of the data and give the consent for data sharing and data preservation. If protection is required, will be granted via anonumisation. There is no sensitive data.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
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Ethics and Legal Compliance
|
How will you manage copyright and Intellectual Property Rights (IPR) issues?
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We own the data and will be licensed for free use, reuse, sharing. No restriction will be placed.
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28f46524c27aa787b40d850edeadd6ee
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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?
|
At least 4 copys of the data will be stored on external storages at different facultys, 2 on Puerto Real campus ( science faculty, CASEM), 2 on researchers residence. Also the data will be saved on university IT teams.
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28f46524c27aa787b40d850edeadd6ee
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dmponline.dcc.ac.uk
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Storage and Backup
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How will you manage access and security?
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No data is confidencial, it is very low risk data.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
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Selection and Preservation
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Which data are of long-term value and should be retained, shared, and/or preserved?
|
The strains growth rate data and Models of microalgae culture in natural environment are long term useful data.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
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Selection and Preservation
|
What is the long-term preservation plan for the dataset?
|
The data will be held on CSIC repository. If neede will search other repositorys to compliment.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
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Data Sharing
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How will you share the data?
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First will share through CSIC repository, the data will be avalaible after quality control.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
|
Data Sharing
|
Are any restrictions on data sharing required?
|
There will be no restriction in data sharing.
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28f46524c27aa787b40d850edeadd6ee
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
Who will be responsible for data management?
|
Both principal investigators are responsible for all the data management (capture, metadata production, data quality, storage and data sharing)
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28f46524c27aa787b40d850edeadd6ee
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dmponline.dcc.ac.uk
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Responsibilities and Resources
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What resources will you require to deliver your plan?
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No extra resources are required to deliver the plan.
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28f46524c27aa787b40d850edeadd6ee
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dmponline.dcc.ac.uk
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0. General information
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Document version & date
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Version 3.0 Date: 09 / 01 / 2024
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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0. General information
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Your contact details
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Full name: Amalia Kontochristou Your role in the project (please refer to the CRediT contributor roles): Conceptualization (1), Data Curation (2), Formal Analysis (3), Investigation (5), Methodology (6), Software (9), Validation (11), Visualisation (12), Writing- Original Draft (13) Email: [email protected] ORCID ( LibGuide ): https://orcid.org/0009-0006-5988-0024 University: Vrije Universiteit Amsterdam Faculty/Institute: Faculty of Science Department/Research Group: Bioanalytical Chemistry
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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0. General information
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List other people involved, including those at partner organisations in the project (if applicable)Full name of person(s) involved:
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Prof. Dr. Anouk M. Rijs Their role(s) in the project (please refer to the CRediT contributor roles): Conceptualization (1), Funding Acquisition (4), Resources (8), Supervision (10), Writing- Review & Editing (14) Email: [email protected] ORCID ( LibGuide ): https://orcid.org/0000-0002-7446-9907 University: Vrije Universiteit Amsterdam Faculty/Institute: Faculty of Science Department/Research Group: Bioanalytical Chemistry Dr. Melissa J. Bärenfänger Their role(s) in the project (please refer to the CRediT contributor roles): Conceptualization (1), Funding Acquisition (4), Investigation (5), Methodology (6), Resources (8), Software (9), Supervision (10), Writing- Review+Editing (14) Email: [email protected] ORCID ( LibGuide ): https://orcid.org/0000-0002-2855-924X University: Vrije Universiteit Amsterdam Faculty/Institute: Faculty of Science Department/Research Group: Bioanalytical Chemistry
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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0. General information
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Funding organisation & grant number (if applicable)
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Funding organisation: National Government, Ministry of Education, Culture and Science (OCW)
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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0. General information
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Consulted data management expert(s)
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Name: Dr. Brett G. Olivier Email: [email protected] University: Vrije Universiteit Amsterdam,
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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0. General information
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Date of consultation:
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DD / MM / YYYY (has yet to be planned)
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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Will you collect or produce new data? If yes, please describe how.
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New data will be produced in this project. Due to the use of multiple analytical techniques, such as liquid chromatography and mass spectrometry, using different instrument-specific software, various data formats will be obtained. The techniques mentioned will be used to analyse glycosylated proteins contained in cerebrospinal fluid (CSF) and plasma samples (from humans). CSF and plasma samples will be provided to us by the Amsterdam UMC, VUmc. The samples will be stored at -20oC (locked freezer; only people involved in the project will have access to the samples), and they will be analysed using first separation techniques (such as affinity chromatography and reverse phase chromatography) and then detection techniques (such as mass spectrometry). Data asset: Liquid Chromatography (LC) Description: Chromatograms will be generated using either HPLC (Agilent) or nanoLC (Thermo Fischer) Formats: .CSV, .txt, .png, .jpeg Data asset: Mass Spectrometry (MS) Description: Mass spectra will be generated using different types of mass spectrometers. Formats: .d (Bruker DataAnalysis), .wiff (SCIEX), .CSV
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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Describe the population/participants/subjects that will be studied
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Cerebrospinal fluid and plasma samples will be collected from Alzheimer's patients and healthy individuals, female and male, from 40 to 90 years old. The sample will be collected by specialised hospital staff and provided to us from the Amsterdam UMC, VUmc. The samples, after collection, will be stored at -20oC. The number of samples that will be used has still to be determined.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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Do you process any of the following (personal) data?
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In this project, only limited personal data will be processed. Specifically, the patient's name will not be mentioned. The data collected and processed will be restricted to the age and gender of the patient and whether the patient has Alzheimer's disease.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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Does the data collection include any of the following types of personal data?
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The data collection for this project includes information related to the patient's health. The focus will be solely on the presence or absence of Alzheimer's disease; no other detailed health information will be collected.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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How much digital data storage will your project require?
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The exact amount of digital data storage needed depends on the amount of raw data files. The estimated amount needed is between 500GB and 2TB. Data is stored on the SURFsara and Yoda cloud drive provided by Vrije Universiteit Amsterdam.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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Will you collect physical data? If yes, please describe these.
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No physical data will be collected. The biological samples, the consent forms from patients and the patient information are not collected by us but by specialised hospital staff.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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1. Data description
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Will you take measures to ensure data quality? Please describe these, if applicable.
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1. Implement validation checks during data collection to identify and correct errors. 2. Develop cleaning protocols to address inconsistencies, outliers, and missing values. 3. Document data collection methods, including instruments, protocols, and any changes made using eLabFTW. 4. Conduct regular audits of the dataset to identify and rectify errors or inconsistencies. 5. Implement access controls to ensure that only authorized personnel can modify the dataset. 6. Regularly monitor and log data access to identify and address any unauthorized changes. 7. Regularly back up the dataset to prevent data loss.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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3. Storage and back-up during the research process
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What measures will you take to secure and protect data during the research process? Please describe, for eachseparate data asset you described for question 1.10, how you will ensure data security, where the data assets arestored & backed up, and who has authorization to access the asset.
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All data will be stored in SURFDrive and Yoda and archived in Yoda for long-term storage. All data (stored and backed up) will be available only to people involved in the project. In details: Raw data: Data asset: Produced liquid chromatography (LC) and mass spectrometry (MS) data and patient information Storage: SURFDrive Backup: Yoda Access: restricted access (only people involved in the project) Security measures: All personal data will be anonymised, and access to all digital data assets (protected by a password) will be restricted, according to General Data Protection Regulation (GDPR) regulations.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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3. Storage and back-up during the research process
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What other tools or software do you intend to use during your research?
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Name: Bruker Compass DataAnalysis version 5.0 ( https://www.bruker.com/en/products-and-solutions/mass-spectrometry/ms- software.html ) Role: Analysis of mass spectrometry data Country: The Netherlands Name: MacCoss Lab Software: Skyline version 23.1 ( https://skyline.ms/project/home/software/Skyline/begin.view ) Role: Analysis of mass spectrometry data Country: The Netherlands Name: MSfragger version 20.0 ( https://www.nesvilab.org/software.html ) Role: Analysis of processed mass spectrometry data Country: The Netherlands Name: MSConvertGUI (64-bit) version 3.0.23272-0f4c78d ( https://proteowizard.sourceforge.io/download.html ) Role: Convert mass spectrometry data to other types of data Country: The Netherlands Name: Matrix Science Mascot Deamon version 2.8.0 (64-bit) ( https://www.matrixscience.com/daemon.html ) Role: Process proteomics data Country: The Netherlands Name: Matrix Science Mascot Database search ( https://www.matrixscience.com/search_form_select.html) Role: Process proteomics data Country: The Netherlands
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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Which data assets will be archived and which will be published?
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After completion, all data assets generated in each subproject will be archived in Yoda Drive. Personal data will be archived in Yoda with restricted access, and a mandatory anonymization process will precede any data publication, ensuring adherence to GDPR regulations and protecting individuals' privacy. Assets related to publications will be designated for public access (apart from personal data) and published through Yoda Drive. All CSF and plasma samples will be used during the research, so no archive is required.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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What other archive(s) do you intend to use to archive data assets?
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Not applicable for now.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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For how long will the data be available in the archive?
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The data generated in the course of this project will be available in Yoda for a minimum period of 10 years after its completion.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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Where will you publish your data assets?
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The data assets from this project will be published through Yoda, ensuring the protection of personal data, appropriately documented and accompanied by metadata to enhance its visibility and utility for other researchers. The documents containing personal data will not be published.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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How will you ensure your data assets get a persistent identifier (e.g. a DOI-code)?
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The data assets will be assigned a persistent identifier, specifically a Digital Object Identifier (DOI), through Yoda. Yoda automatically generates a DOI upon publishing and storing the data, providing a unique and persistent link directly connected to the dataset. Metadata, including comprehensive information about the dataset, will be meticulously curated and associated with the DOI to enhance the visibility, accessibility, and proper attribution of the data assets within the scholarly community.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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Are there restrictions to data publishing? If yes, please specify the reasons and list the data assets you do notwish to share publicly.
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Yes, with the exception of data associated with personal data, all other data from this project can be published. Due to privacy and confidentiality concerns, information linking samples to specific patients will not be made publicly available. Access to this specific data will be restricted to authorised personnel to ensure compliance with ethical standards and privacy regulations.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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When will you share the data? If not immediately after completion of the project, please specify the reasons.
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The data from this project will be shared immediately after completion. However, due to privacy and confidentiality concerns, personal data linking samples to specific patients will only be accessible to individuals directly involved in the project.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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4. Data archiving and publishing
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Please indicate the license and/ or terms of use under which you share your data.
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Attribution-NonCommercial 4.0 International
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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5. Documentation
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What documentation and metadata will accompany the project?
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Dataset registrations in PURE and CERIF metadata standards will be followed. Metadata will be generated by Yoda after each publication and also at the end of my project. Additional documentation will include the lab journal (eLabFTW) linked to each experiment performed, describing methodologies, sample info and preliminary results. Moreover, a Readme file in .txt format will describe how the data is stored.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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5. Documentation
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What metadata and documentation will accompany the data assets?
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Property Obligation 6 Subject (with scheme sub-property) R 7 Contributor (with type, name identifier, and affiliation sub-properties) R 8 Date (with type sub-property) R 9 Language O 11 AlternateIdentifier (with type sub-property) O 12 RelatedIdentifier (with type and relation type sub-properties) R 13 Size O 14 Format O 15 Version O 16 Rights O 17 Description (with type sub-property) R 18 GeoLocation (with point, box and polygon sub-properties) R 19 FundingReference (with name, identifier, and award related sub- properties) O 20 RelatedItem (with identifier, creator, title, publication year, volume, issue, number, page, publisher, edition, and contributor sub-properties) O
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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6. Data management responsibilities and resources
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Who will be responsible for management of the data assets during the project? Please specify their name,position, role in the project, and faculty/ institution/ group.
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Full name: Amalia Kontochristou Your role in the project (please refer to the CRediT contributor roles): Investigator Email: [email protected] ORCID ( LibGuide ): https://orcid.org/0009-0006-5988-0024 University: Vrije Universiteit Amsterdam Faculty/Institute: Faculty of Science Department/Research Group: Bioanalytical chemistry
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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6. Data management responsibilities and resources
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Who will be responsible for management of the data assets after completion of the project (e.g. the project lead/dedicated data manager/ department head)? Please specify their name, position, role in the project, and faculty/institution/ group.
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The department head will be responsible for the management of the data assets after the completion of the project. Full name: Matthias F. Bickelhaupt Your role in the project (please refer to the CRediT contributor roles): Investigator Email: [email protected] ORCID ( LibGuide ): 0000-0003-4655-7747 University: Vrije Universiteit Amsterdam
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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6. Data management responsibilities and resources
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For data that are only available upon request, what methods will be used to handle requests for access and howwill data be made available to those requesting access?
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Access will be handled in compliance with the European Data Protection Regulation (GDPR) regulations for data that is only available upon request. The following methods will be employed: 1. All requests for access to restricted data should be submitted through a formalised process, which may involve a designated contact person or a secure online portal. 2. Requests will be subject to a thorough verification process to ensure the identity and legitimacy of the requester following GDPR requirements. 3. Each request will undergo a legal and ethical review to assess compliance with GDPR regulations and other relevant legal frameworks. 4. For approved requests, data access will be granted under a restricted access protocol, limiting access to the specific data requested while maintaining compliance with data protection regulations. 5. Data provided in response to requests will undergo anonymisation or pseudonymisation processes as necessary to protect the privacy of individuals, ensuring compliance with GDPR principles. 6. Data will be transferred securely to the requester using encryption and other secure methods to prevent unauthorised access during transmission. 7. All requests, approvals, and data transfers will be thoroughly documented to ensure a transparent and auditable process consistent with GDPR record-keeping requirements.
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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6. Data management responsibilities and resources
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What resources (for example financial and time) will be dedicated to research data management? Please estimatetheir cost.
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Active data management will be done every week to ensure proper data organisation and storage. The data will be stored in both SURFsara and Yoda cloud drives. The online storage drives used are provided by the VU (cost unknown).
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989d56ebb8b569763678d44160a7fd1e
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dmponline.dcc.ac.uk
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IV. Legal and ethical requirements, codes of conduct
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How will ownership of the data and intellectual property rights to the data be managed?
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For projects involving commercially-sensitive research or research involving third parties, seek advice of your Faculty Contract Manager when answering this question. If this is not the case, you can use the example below. The datasets underlying the published papers will be publicly released following the TU Delft Research Data Framework Policy. During the active phase of research, Mohammed will oversee the access rights to data (and other outputs), as well as any requests for access from external parties. They will be released publicly no later than at the time of publication of corresponding research papers.
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af7a08e54b6628cf9dc61e19b0e1da07
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dmponline.dcc.ac.uk
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IV. Legal and ethical requirements, codes of conduct
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Please list the categories of data subjects
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For the experiments, the participants will recruited in two ways: 1- General public through online platforms (e.g., Prolific, etc..) 2- Counsellors who have previous experience in their field (e.g., volunteer Counsellor)
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af7a08e54b6628cf9dc61e19b0e1da07
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dmponline.dcc.ac.uk
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IV. Legal and ethical requirements, codes of conduct
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Please describe the informed consent procedure you will follow:
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All study participants will be asked for their consent to participate in the studies and for data processing before the experiments start. As this data management plan is for the whole 4-years period of the PhD program, we will attach the relevant consent form to each experiment's DMP.
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af7a08e54b6628cf9dc61e19b0e1da07
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dmponline.dcc.ac.uk
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IV. Legal and ethical requirements, codes of conduct
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Does the processing of the personal data result in a high risk to the data subjects?
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If the processing of the personal data results in a high risk to the data subjects, it is required to perform a Data Protection Impact Assessment (DPIA). In order to determine if there is a high risk for the data subjects, please check if any of the options below that are applicable to the processing of the personal data during your research (check all
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af7a08e54b6628cf9dc61e19b0e1da07
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dmponline.dcc.ac.uk
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VI. Data management responsibilities and resources
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If you leave TU Delft (or are unavailable), who is going to be responsible for the data resulting from this project?
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Myrthe Tielman ([email protected]) Willem-Paul Brinkman ([email protected])
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af7a08e54b6628cf9dc61e19b0e1da07
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dmponline.dcc.ac.uk
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Data Type
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Summarize the types (for example, 256-channel EEG data and fMRI images) and amount (for example, from 50research participants) of scientific data to be generated and/or used in the research.
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This dataset is generated from 557 participants who were purposively interviewed in southwestern Uganda on their trypanocide usage practices. This dataset consists of quantitative data that was collected using MS Forms provided by the UOE and stored in MS Excel format.
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Data Type
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Describe which scientific data from the project will be preserved and shared. NIH does not anticipate that researcherswill preserve and share all scientific data generated in a study. Researchers should decide which scientific data topreserve and share based on ethical, legal, and technical factors. The plan should provide the reasoning for thesedecisions.
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Participant responses on survey questions will be preserved. All identifiers are removed form the dataset and pseudo names are used where applicable. There is no data sharing with collaborators outside the university. Data will be shared through DataShare UOE
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Data Type
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A brief listing of the metadata, other relevant data, and any associated documentation (e.g., study protocols and datacollection instruments) that will be made accessible to facilitate interpretation of the scientific data
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A questionnaire with observations on social demographics, knowledge, drug usage practices will be provided.
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Standards
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Describe what standards, if any, will be applied to the scientific data and associated metadata (i.e., data formats,data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).
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Survey data on household responses on trypanocide usage practices in southwestern Uganda.
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Data Preservation, Access, and Associated Timelines
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The name of the repository(ies) where scientific data and metadata arising from the project will be archived.
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University of Edinburgh Datashare
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Data Preservation, Access, and Associated Timelines
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When the scientific data will be made available to other users and for how long. Identify any differences in timelinesfor different subsets of scientific data to be shared.
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This will be available after 5 years.
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Access, Distribution, or Reuse Considerations
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Privacy and confidentiality protections consistent with applicable federal, Tribal, state, and local laws, regulations,and policies
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Data is anonymized and no patent rights are associated with the study.
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Access, Distribution, or Reuse Considerations
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Any other considerations that may limit the extent of data sharing. Any potential limitations on subsequent data useshould be communicated to the individuals or entities (for example, data repository managers) that will preserve andshare the scientific data. The NIH ICO will assess whether an applicant’s DMS plan appropriately considers anddescribes these factors. For more examples, see
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Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data. Not applicable
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Oversight of Data Management and Sharing
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Indicate how compliance with the DMS Plan will be monitored and managed, the frequency of oversight, and by whom(e.g., title, roles). This element refers to oversight by the funded institution, rather than by NIH. The DMS Policy doesnot create any expectations about who will be responsible for Plan oversight at the institution.
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This is article summarizes key findings from the survey.
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23dc414312620af9ac6378993bb69693
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dmponline.dcc.ac.uk
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Data description
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What data will you create?
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The data created in this study will include survey responses to questions related to household food security, habitual food intake (estimated from a food frequency questionnaire) and participant demographics. The survey will be conducted using “JISC online Surveys”. Response will be downloaded into excel/ SPSS and stored in a password protected folder on the University of Nottingham OneDrive.
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
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Data collection / generation
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What are your methodologies for data collection / generation? How will you ensure data quality? What data standardswill you use?
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We will be using established programs for Data collection which are “Jisc online surveys” All participants will be assigned a participant number which will be used throughout the study to ensure anonymity.
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
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Data storage and security
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Where and how will data will be stored, backed-up, transferred, and secured during the active phase (short to mediumterm) of research?
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We will use UoN-provided storage for our working data. UoN licenses Microsoft Teams, allowing for secure and controlled sharing of data among the research team. Microsoft Teams encrypts data both in transit and at rest and is approved against the University’s Handling Restricted Data Policy. The service provides several layers of automatic back up and, in a disaster scenario, files can be recovered. Access to data stored in MS Teams is via secure log-in with multi-factor authentication. We will store data for a period of no less than 7 years after the research project finishes. The researchers who gathered or processed the data may also store the data indefinitely and reuse it in future research. Password protected files on OneDrive will also be used for storage of data Data provided via an online questionnaire and food intake data from the food application (FFQ) will be transferred to the Excel and SPSS spreadsheets and anonymised for further analysis with the same unique study identification number which will be given to each participant. Participants' contact details, including e-mail address and postcode, will be kept in a different study folder. All research data including consent and personal data will be password-protected and stored securely in a locked archive.
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
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Data management, documentation, and curation
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What are your principles, systems, and major standards for data management and creation? What metadata anddocumentation will you keep?
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All data will be managed according to the University of Nottingham's data management policy (accessible to University staff through the library website - https://www.nottingham.ac.uk/library/research/research-data-management/index.aspx; https://uniofnottm.sharepoint.com/sites/DigitalResearch/SitePages/Research-Data-Management-Policy.aspx) with specific focus on policy statement 3.1 3.1 It is the policy of the University of Nottingham that all research data be managed in a manner that supports its authenticity, reliability, security, discoverability and, where appropriate, accessibility for re-use. Data will be generated using online survey managed by "Online Surveys" (Online surveys Jisc, 4 Portwall Lane, Bristol, BS1 6NB, UK). All survey data through the JISC service is stored "...within Amazon Web Services (AWS), within the Republic of Ireland..." and the security of this data is guaranteed to ISO/IEC 27001 standard.
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
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Ethics & Privacy
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Are there any ethical or privacy related issues associated with your data?
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We will have email addresses and post codes for a number of respondents. We will have some contact details (e-mail address and postcode) for participants. However, these contact details will not be used for data analysis or published in further studies. These identifiable details will be removed from the study data and transferred to another folder and protected securely. All research data (questionnaire and food intake data) will be anonymized.
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
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Data preservation
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How will you ensure the long term storage and preservation of data?
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The research team will be responsible for the protection of original research data and they will be responsible for protecting the participants' rights and privacy. The study team will adhere to General Data protection Regulation, 2018. Study data will be held securely and password protected at the University of Nottingham. The University of Nottingham uses Microsoft OneDrive for storage of data. Study datasets will be stored within the lead researcher's OneDrive. The specific folder will be accessible only to other members of the research team.
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
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Data sharing and access
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How will the data generated be shared and published?
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Data will only be shared amongst the study group for the purposes of analysis. All data will be anonymised, so all of the summary findings will be derived according to groups of people rather than for individuals. If external researchers request access to the data, we will take careful guidance from the University Information Compliance Office in order to ensure adherence to correct procedure and permissions. All data processing and sharing will adhere to the University of Nottingham Data Protection Policy (https://www.nottingham.ac.uk/governance/records-and-information-management/data-protection/data-protection-policy.aspx). Outcomes identified from analysis of the data will be published in the scientific literature as appropriate. We expect publication of study data to take place between 4 - 6 months after the second data collection. If, however, the early outcomes of the study identifies particularly vulnerable groups who might be aided by local or targeted national policy/intervention, we will communicate with the information compliance team in order to appropriately disseminate the details to the relevant local authorities. Participants will not be identifiable in the further publications, as their personal data is transferred from study data to another file and given to them unique study number instead
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30aef004acc4d0427699a6a748444f2d
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dmponline.dcc.ac.uk
|
Roles & responsibilities
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Who will be responsible for managing data, data security, data quality, and data security both during the award andpost-award?
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The responsibility for the data will fall to the main study leaders. The overall responsibility for data security is held by the University of Nottingham Chief information security officer. The datasets generated in this study will not be deposited in any public repository so we do not anticipate needing to generate metadata to allow its identification for wider groups.
|
30aef004acc4d0427699a6a748444f2d
|
dmponline.dcc.ac.uk
|
Relevant policies
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What are the relevant institutional, departmental or study policies on data sharing and data security?
|
The University of Nottingham abides by The General Data Protection Regulation (GDPR) and the university is the Data Controller under UK Data Protection laws (legally responsible for the data security). For further information: https://www.nottingham.ac.uk/utilities/privacy/privacy.aspx Specifically relevant policies include: University of Nottingham Research Data Management Policy Records Management Policy Records Retention Policy Data Protection Policy Data Handling Standards Policy Information Security Policy
|
30aef004acc4d0427699a6a748444f2d
|
dmponline.dcc.ac.uk
|
IPR
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Who will own the copyright and IPR of any data that you will collect or create? Will you create a licence(s) for its useand reuse? If you are planning to use existing data as part of your research, do any copyright or other restrictionsdetermine its use?
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Copyright & IPR for all project research data is owned by University of Nottingham.
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30aef004acc4d0427699a6a748444f2d
|
dmponline.dcc.ac.uk
|
Budgeting
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What are the costs or funding required for capturing, processing, storing, and archiving your data?
|
Unkown
|
30aef004acc4d0427699a6a748444f2d
|
dmponline.dcc.ac.uk
|
Data Collection
|
Give details on the proposed methodologies that will be used to create the data. Advise how the project teamselected will be suitable for the data/digital aspects of the work, including details of how the institution’s datasupport teams may need to support the project
|
1. Data collection: First, we need to determine the type of data to be collected. This may include quantitative data (e.g., age, gender, income, etc.) and qualitative data (e.g., satisfaction, preferences, etc.). Data can be collected in a variety of ways, such as online surveys, face-to-face interviews, telephone interviews, or extracted from existing databases. 2. Data cleansing: After collecting data, we need to perform data cleansing to ensure the quality of the data. This may include removing duplicates, dealing with missing values, correcting incorrect inputs, etc. 3. Data Analysis: We can then analyze the data using various statistical methods and tools. This may include descriptive statistical analysis, inferential statistical analysis, predictive modeling, etc. 4. Data Visualization: Finally, we can use visualization tools such as charts and graphs to present the data. This can help us understand the data better and communicate our findings to others. Here are some suggestions on how project teams can adapt to the data/numerical aspects of their work: 1. Training: Project teams may need to be trained in data management and analytics. This can help them understand how to handle and analyze data using various tools and techniques. 2. Resources: The project team needs to have adequate resources to collect, clean and analyze data. This may include software, hardware, manpower, etc. 3. Collaboration: The project team needs to work closely with other team members (e.g., the data support team) to ensure the quality and accuracy of the data. For more information on how the organization's data support team may need to support the project, here are some suggestions: 1
|
17e480756035d6484b0b2af7e92f9230
|
dmponline.dcc.ac.uk
|
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