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4. Data Storage and Backup
|
Describe where you will store your data and documentation during the research.
|
UMC Utrecht is initiator of this multicenter study. All data and documentation collected by the UMC Utrecht will be stored in the secured Research Folder Structure of the UMC Utrecht. Importantly, personal data is stored separately from other research data and adequate access and control rights are in place. In other participating sites, data and documentation will be stored accordingly.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
4. Data Storage and Backup
|
Describe your backup strategy or the automated backup strategy of your storage locations.
|
During data collection, automatic backups will be made in the Electronic Data Capture Tool Castor. Upon completion of data collection, all data are exported and saved in the Research Folder Structure where they are automatically backed up by the UMC Utrecht backup system. All (research) data is stored on UMC Utrecht networked drives from which backups are made automatically twice a day by the division IT (dIT).
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
5. Metadata and Documentation
|
Describe your version control and file naming standards.
|
We will distinguish versions by indicating the version in the filename of the master copy by adding a code after each edit, for example V1.1 (first number for major versions, last for minor versions). The most recent copy at the master location is always used as the source, and before any editing, this file is saved with the new version code in the filename. The file with the highest code number is the most recent version and older versions are moved to a folder OLD. The major versions will be listed in a version document (projxVersDoc.txt), stating the distinguishing elements per listed version.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
7. Data Preservation and Archiving
|
Describe which data and documents are needed to reproduce your findings.
|
The data package will contain: the raw data, the study protocol describing the methods and materials, the script to process the data, the scripts leading to tables and figures in the publication, a codebook with explanations on the variable names, and a ‘read_me.txt’ file with an overview of files included and their content and use. I use an Electronic Lab Notebook and I create work instructions for every step that is needed to reproduce my results from ddPCR analysis on blood samples. Information on sample and DNA quality and quantity will be documented. Any practical difficulties will also be documented. After finishing the project, this documentation will be stored at the UMC Utrecht and is under the responsibility of the Principal Investigator of the research group.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
7. Data Preservation and Archiving
|
Describe for how long the data and documents needed for reproducibility will be available.
|
Data and documentation will be stored for at least 15 years.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
7. Data Preservation and Archiving
|
Describe which archive or repository (include the link!) you will use for long-term archiving of your data andwhether the repository is certified.
|
1. We will use Archivematica to archive our research data, we will follow the UMC Utrecht guidelines for archiving data. 2. After finishing the project, the data package will be stored at the UMC Utrecht Research Folder Structure and is under the responsibility of the Principal Investigator of the research group. When the UMC Utrecht repository is available, the data package will be published here.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
7. Data Preservation and Archiving
|
Give the Persistent Identifier (PID) that you will use as a permanent link to your published dataset.
|
The PID as a permanent link to the data is not yet determined. This answer will be updated later.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
8. Data Sharing Statement
|
Describe what reuse of your research data you intend or foresee, and what audience will be interested in yourdata.
|
1. My peers will be reusing all research data in the final dataset to generate new research questions. 2. The raw data can be of interest for other researchers or for spin off projects. 3. Our processed data can be of interest for other Europeans researchers in the field or for comparison to similar projects in other European countries.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
8. Data Sharing Statement
|
Describe which metadata will be available with the data and what methods or software tools are needed to reusethe data.
|
1. All data and documents in the data package mentioned in 7.1 will be shared under restrictions. 2. The publication will be open assessable. The study protocol and this Data Management Plan will also be available. 3. Along with the publication, the codebook of the data and scripts of analysis in SPSS/Matlab/R/Python will be available.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
8. Data Sharing Statement
|
Describe where you will make your data findable and available to others.
|
We will use DataverseNL as a repository for our research data, we will follow the UMC Utrecht guidelines for publishing research data.
|
24adb1188d97f228d76f9625fd6e2647
|
dmponline.dcc.ac.uk
|
Data Collection
|
What data will you collect or create?
|
Develop a chemical kinetic mechanism of ammonia co-firing with high reactivity fuels such as hydrogen and n-heptane (a surrogate of diesel). The design of ammonia/hydrogen co-combustion in marine engines requires knowledge of chemical kinetics to understand the ignition, flame propagation, as well as pollutant emission formation. Chemical kinetic mechanisms describes the combustion of ammonia/hydrogen mixture with ignition improver (such as n-heptane). One important issue of ammonia/hydrogen engines is the emission of N2O, which is a greenhouse gas (GHG) of high impact. It is hypothesised that by co-combustion of ammonia with hydrogen, N2O emission can be reduced.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Data Collection
|
How will the data be collected or created?
|
Data will be collected through simulations using CFD tools
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Documentation and Metadata
|
What documentation and metadata will accompany the data?
|
Documentation of the mechanisms will be published in open-access journal papers. Metadata will also be documented in the publications in terms of the definition of validity ranges.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
|
How will you manage any ethical issues?
|
There are no ethical issues related to this work.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
|
How will you manage copyright and Intellectual Property Rights (IPR) issues?
|
Data will be openly published and shared in publications. The mechanism will be made available for download on group website.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Storage and Backup
|
How will the data be stored and backed up during the research?
|
The mechanism and generated data are stored on NTNU storage facilities such as NTNU Box.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Storage and Backup
|
How will you manage access and security?
|
As data and results are published in open access papers, only the source code for the actual mechanism should be stored for security reasons. Even if lost, the actual mechanism will be available for recreation from published papers.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Selection and Preservation
|
Which data are of long-term value and should be retained, shared, and/or preserved?
|
No long-term value data will be preserved. Once the mechanisms are available, new data will and should be generated depending on new conditions and technical development.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Data Sharing
|
How will you share the data?
|
Potential users of the chemical scheme will access this from the website. We will share this with project partners who are open to use this in their own simulations. Further publications from this work should site the original source.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
Who will be responsible for data management?
|
The PI is overall responsible for the data/chemical mechanism.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
What resources will you require to deliver your plan?
|
Access to NTNU Box. Group website hosted by institution NTNU.
|
52dadeb0bfdb5faa187edaae27b52c13
|
dmponline.dcc.ac.uk
|
Project Details
|
Dissertation/ project title:
|
EmpowerHER
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Data Collection
|
Will you be using any secondary data for this project? Please outline what kind of secondary data you will be usingbelow:
|
Published research papers, existing published online research and secondary research conducted by Spring ACT from information publicly available online.
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Data Collection
|
Please can you describe how you plan on conducting data collection using these methods:
|
An online survey will be conducted via Qualtrics targeting Gen Z (aged 18 to 26) females who are currently living in the UK or Europe through a snow ball method.
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Research Ethics
|
Please explain how you will collect informed consent:
|
The consent and participation form will be shown to the participants before they start answering any questions. They will have a ‘tick box’ to check which indicates their consent to participating in the survey.
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Research Ethics
|
Once you have collected proof of consent, you will need to store it safely. Please can you explain below how you planto do this:
|
All the survey consent information will be recorded along with the questionnaire answers through Qualtrics and the data will be store in our LSE Onedrive.
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Research Ethics
|
If you are collecting primary data from research participants, you are required to anonymise the dataset so thatindividuals are not identifiable. How do you plan to do this?
|
The participants will not be asked about their names. Participants' age range and country of residence will be asked, this data will be stored in H: Space.
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Data Storage & Security
|
Could you outline how you plan to share data between members in your research team:
|
We plan to share data through OneDrive
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Data Storage & Security
|
Please can you supply details/ links to any additional research tools you’ll be using below:
|
Qualtrics, Microsoft Excel, H:Space
|
5c7918fe3d309cb86db4e29f81a5bb32
|
dmponline.dcc.ac.uk
|
Manchester Data Management Outline
|
Will this project use innovative technologies to collect or process data?
|
Remote sensing and machine learning
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Manchester Data Management Outline
|
Who will act as the data custodian for this study, and so be responsible for the information involved?
|
Muhammad Uthman
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Project details
|
What is the purpose of your research project?
|
PhD Research
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Project details
|
What policies and guidelines on data management, data sharing, and data security are relevant to your researchproject?
|
UK Research Council's Policies University of Manchester Research Data Management Policies
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
Who will be responsible for data management?
|
Muhammad Uthman
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Responsibilities and Resources
|
What resources will you require to deliver your plan?
|
Data Storage Solution (Microsoft One Drive)
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Data Collection
|
What data will you collect or create?
|
Mainly secondary data and a small fraction of primary data. The secondary data will be in the form of a raster or statistical dataset, while the primary will be electronically. This will nor require much storage, perhaps an estimate of 20GB.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Data Collection
|
How will the data be collected or created?
|
Secondary data will be obtained from existing datasets, reports, or online repositories. Primary data will be collected through interview. The data will be organized into a hierarchical data structure based on themes. And folder will be named with a traditional naming system that will easily recognize.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Documentation and Metadata
|
What documentation and metadata will accompany the data?
|
To make the data well documented and easy for reuse, the underlisted infomation will be included: Basic detail about the data, to inclue the title ofh the dtataset, creators, date of publication and licesing.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
|
How will you manage any ethical issues?
|
This study will not include the collection of personal information; however, the ethical approval will be requested to ensure compliance with appropriate ethical regulation through the institutional ethical committee. After which all ethical concern highlighted during the ethical review procedure will be appropriately dealt with and capture into the research methodology. Any data collected from participant will capture the consent section to highlight the purpose of the data collection and the the issues related to the data been collected for public use and the possibility of sharing such data in a processed manner.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Ethics and Legal Compliance
|
How will you manage copyright and Intellectual Property Rights (IPR) issues?
|
I will soley own the copyright and intellectual property rights (CIPR) of the research outcome, but in the case where a collaboration was made for a journal or conference paper the CIPR will be for the contibutors. Collaborator will also be adequately acknowledge. Data generated from the research will licensed appropriately to facilitate reuse such as the Creative Common Lincens. No restriction will be on the reuse of third party data except where indicated.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Storage and backup
|
How will the data be stored and backed up?
|
The Microsoft One Drive will be adequate for backing up all necessary data.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Storage and backup
|
How will you manage access and security?
|
All data for the research will be based in my computer device and One drive which are all managed by the university and properly secured. And access to such data can be only through me. Password protected device will be used for interview and protecting the data collected. The safe transfer of data from the field will be done using a secured network to transmit the data.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Selection and Preservation
|
Which data should be retained, shared, and/or preserved?
|
collected primary data should be fully retained, while dataset for other relevant secondary dataset will be documented. The duration for retaintion should be a suffiecient period that meets the research need. However, the data will be save in cloud storage such as OneDrive/Google Drive or figshare that will allow easy access.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Selection and Preservation
|
What is the long-term preservation plan for the dataset?
|
The research dataset will not require a formal long-term preservation plan. However, all necessary data or sources will be curated in a cloud storage and figshare
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Data Sharing
|
How will you share the data?
|
Data sharing will be done using Figshare repository.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
Data Sharing
|
Are any restrictions on data sharing required?
|
No, as all participant will be anonymised.
|
0f8b6dcb1eb8c98f475de9662dd68798
|
dmponline.dcc.ac.uk
|
1. General features
|
Please fill in the table below. When not applicable (yet), please fill in N/A.
|
DMP template version 30 (don't change) ABR number (only for human-related research) - METC number (only for human-related research) 22-008 DEC number (only for animal-related research) - Acronym/short study title HNPGL Name Research Folder 22-008_HNPGL Name Division Surgical Specialties Name Department Vascular Surgery Partner Organization Amsterdam Universitair Medisch Centrum (Amsterdam UMC) Erasmus MC (EMC) Leiden Universitair Medisch Centrum (LUMC) Radboud Universitair Medisch Centrum (Radboud UMC) Start date study 01-10-2021 Planned end date study T.b.d. Name of datamanager consulted* D. Steins, P Ojha, N. Koning Check date by datamanager 07-10-2021, 21-12-2021, 7-7-2023 (amendement)
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
2. Data Collection
|
Give a short description of the research data.
|
Primary Objective : to create a registry that can be used for future research on optimising diagnostic protocols, treatment strategies, improving symptom-free survival and optimising patient follow-up among HNPG patients. Data flow : After broad consent has been obtained, clinical information from the UMC Utrecht's electronic health records (EHR; HiX) will be (partially) extracted by the division datamanager and partially added to the eCRF by hand. This dataset will be pseudonymized with a key-linking table and stored in secure research folder on the UMCU's network drive. This dataset, including data not available in the RDP, will be collected in Castor EDC (eCRF) by members of the research team. Castor EDC is a browser-based, metadata- driven EDC software solution and workflow methodology for building and managing online clinical research databases. The eCRF contains data items as specified in this research protocol. Radiological scans will be shared with the UMCU via RIA. All participating centers will collect all data as described in the research protocol. The key files will stay at the local research center in a secured file at their network drive. Furthermore they will get access to Castor. Subjects Volume Data Source Data Capture Tool File Type Format Storage space Human 100 PACS/MRI/CT scanner Research Imaging Architecture Imaging .dcm 101-1000 GB Human Ongoing eCRF Castor EDC Quantitative .csv .xslx .sav 0-10GB
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
2. Data Collection
|
Describe who will have access to which data during your study.
|
After given consent, data will be entered in the registry Castor Database by authorized personnel per individual center to make sure it is possible to extract data for use in Registry 'Uitgiftes' at a later stage. A committee of all centers needs to approve each of those, beside the normal procedure for a Registry 'Uitgifte' Protocol. The key table linking study specific IDs to patient IDs is available to the datamanager and specified members of the research team for each individual center and not shared between centers. Type of data Who has access Direct identifying personal data Research team of local investigation center, Datamanager. Key table linking study specifics IDs to patients IDs PI, Datamanager, registry coordinator of each participating center. Key files will not be shared. Pseudonymized data Research team, datamanager of the local center and of the UMCU.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
2. Data Collection
|
Specify data management costs and how you plan to cover these costs.
|
Type of costs Division ("overhead") Funder Other (specify) 1. Time of datamanager X 2. Design of eCRF X 3. Data capture tool license fee X 4. Storage X 5. Archiving X 6. Questionnaire license fee X
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
2. Data Collection
|
State how ownership of the data and intellectual property rights (IPR) to the data will be managed, and whichagreements will be or are made.
|
In this multicenter registry, all participating centers are owner of the data. As paragangliomas are a relatively rare disease we want to encourage centers to enter their data in the registry and to be involved in the research. All participating centers only have access to their own data, but can get access to pseudonomised data upon request. All this is stated in contracts for research collaboration and a data transfer agreement.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
3. Personal data (Data Protection Impact Assessment (DPIA) light)
|
What legal right do you have to process personal data?
|
Broad consent gathered within this registry by all involved centers for the purpose of future research.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
3. Personal data (Data Protection Impact Assessment (DPIA) light)
|
Describe how you manage your data to comply to the rights of study participants.
|
Right of Access Research data are coded, but can be linked back to personal data, so we can generate a personal record at the moment the person requires that. This needs to be done by an authorized person. Right of Rectification The authorized person will give the code for which data have to be rectified. Right of Objection We use informed consents. Right to be Forgotten In the informed consent we state that the study participant can stop taking part in the research. Removal of collected data from the research database cannot be granted because this would result in a research bias.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
3. Personal data (Data Protection Impact Assessment (DPIA) light)
|
Describe the tools and procedures that you use to ensure that only authorized persons have access to personaldata.
|
1. We use the secured Research Folder Structure that ensures that only authorized personnel has access to personal data, including the key table that links personal data to the pseudoID. 2. We make use of a certified Electronic Data Capture (EDC) tool (Castor). To send surveys, email address will be used in the EDC, but this is encrypted for the users in such a way that users can send emails to subjects without seeing the actual email address. No personal data other than email address will be used in the EDC. 3. Participating centers will also use secured Research Folder Structures that ensures only authorized personnel has access to personal data, including the key table that links personal data to the pseudo ID. 4. Patient digital imaging data for study purposes will be stored at the Research Imaging Archive (RIA) facility of the imaging division of UMC Utrecht. For safe processing of images, RIA will be used (uses pseudonymization in order to guarantee safe processing). Only authorized personnel can access the (pseudonymized) imaging in the RIA container via personal login. The linkage table for the pseudonymized images will also be stored at the RIA. The container can only be accessed by users with the proper rights. Hospitals may transfer digital data into the RIA through secure connections. The RIA shields patient identifiable information through pseudonymized identifiers (i.e., study number) and only allows access to authorized researchers.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
3. Personal data (Data Protection Impact Assessment (DPIA) light)
|
Describe how you ensure secure transport of personal data and what contracts are in place for doing that.
|
1. We will not transport any personal data outside the UMCU network drives. 2. In case we need to transport personal data with colleagues, we use Surffilesender with encryption. 3. We have a Research Agreement and/or Data Transfer Agreement with Erasmus MC, LUMC, Radboud UMC and Amsterdam UMC. The agreement is stored at location (secured Research Folder Structure of the UMC Utrecht): L:\Onderzoek\Vaatchirurgie\22- 008_HNPGL\B_Documentation\6_Contracts
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
4. Data Storage and Backup
|
Describe where you will store your data and documentation during the research.
|
UMC Utrecht is initiator of this multicenter study. All data and documentation collected by the UMC Utrecht will be stored in the secured Research Folder Structure of the UMC Utrecht. Importantly, personal data is stored separately from other research data and adequate access and control rights are in place. In other participating sites, data and documentation will be stored accordingly.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
4. Data Storage and Backup
|
Describe your backup strategy or the automated backup strategy of your storage locations.
|
1. All (research) data is stored on UMC Utrecht networked drives from which backups are made automatically twice a day by the division IT (dIT). 2. During data collection, automatic backups will be made in the Electronic Data Capture Tool Castor. Upon completion of data collection, all data are exported and saved in the Research Folder Structure where they are automatically backed up by the UMC Utrecht backup system. 3. Because of the multicenter registry, all local (research) data is stored on the local network drdives from which backups are made automatically every day by the information and technology divisions of participating centers. 4. All data from other centers will be registred in Castor, so Castor will also make automatic backups of the data of participating centers. 5. Data in Research Imaging Archive (RIA) is stored in two data centers in the UMC Utrecht that are synchronized hourly. These centers are present at different locations within the UMC Utrecht. Next to this, two snapshots are daily created from the data.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
5. Metadata and Documentation
|
Describe the metadata that you will collect and which standards you use.
|
For the data collected in Castor, a codebook of my research database is available in Castor. The metadata will be handled in an Excel-file with a codebook. This will be placed in the secured online research folder by the data manager of the department.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
5. Metadata and Documentation
|
Describe your version control and file naming standards.
|
We will distinguish versions by indicating the version in the filename of the master copy by adding a code after each edit, for example V1.1 (first number for major versions, last for minor versions). The most recent copy at the master location is always used as the source, and before any editing, this file is saved with the new version code in the filename. The file with the highest code number is the most recent version and older versions are moved to a folder OLD. The major versions will be listed in a version document (projxVersDoc.txt), stating the distinguishing elements per listed version.
|
47d5e31e1a429b3ddb90d246c85862a0
|
dmponline.dcc.ac.uk
|
7. Data Preservation and Archiving
|
Describe which data and documents are needed to reproduce your findings.
|
1. The data package will contain: the raw data, the study protocol describing the methods and materials, a codebook with explanations on the variable names, and a ‘read_me.txt’ file with an overview of files included and their content and use.
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47d5e31e1a429b3ddb90d246c85862a0
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dmponline.dcc.ac.uk
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7. Data Preservation and Archiving
|
Describe for how long the data and documents needed for reproducibility will be available.
|
Data and documentation needed to reproduce findings from this non-WMO study will be stored for at least 10 years.
|
47d5e31e1a429b3ddb90d246c85862a0
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dmponline.dcc.ac.uk
|
7. Data Preservation and Archiving
|
Describe which archive or repository (include the link!) you will use for long-term archiving of your data andwhether the repository is certified.
|
After finishing the project, the data package will be stored at the UMC Utrecht Research Folder Structure and is under the responsibility of the Principal Investigator of the research group. DataverseNL will be used as repository to make the research open and available.
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47d5e31e1a429b3ddb90d246c85862a0
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dmponline.dcc.ac.uk
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8. Data Sharing Statement
|
Describe what reuse of your research data you intend or foresee, and what audience will be interested in yourdata.
|
1. My peers will be reusing all research data in the final dataset to generate new research questions. 2. The raw data can be of interest for other researchers or for spin off projects. 3. Our processed genetic data can be of interest for other Europeans researchers in the field. 4. Due to the multicenter registry, participating centers have rights to reuse data. Their will be a board with members of all participating centers, and here researchers can submit the research question. The board will decide if the data for the research question will be granted.
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47d5e31e1a429b3ddb90d246c85862a0
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dmponline.dcc.ac.uk
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Manchester Data Management Outline
|
Who will act as the data custodian for this study, and so be responsible for the information involved?
|
Professor Neil Humphrey and Professor Pamela Qualter
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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Project details
|
What is the purpose of your research project?
|
Research has shown that the teaching of social and emotional skills (social and emotional learning; SEL) improves mental health (Taylor et al., 2017) and reduces loneliness (Eccles & Qualter, 2021; Hennessey, Qualter, & Humphrey, 2021). However, most of that work is based on interventions implemented in the initial years of primary school, and there is a need to determine effects for older school aged children. 'Passport' is an SEL intervention for schools and we will determine, via a randomised controlled trial (RCT), whether its use with 9 to 11 year olds in England improves mental health and reduces loneliness. This work will advance our understanding of how SEL can be used to support children’s mental health and relationships in school settings. Furthermore, we can use the data generated through the project for secondary analysis, addressing important knowledge gaps in our understanding of child and adolescent mental health, including, for example, longitudinal relations between bullying, loneliness, and wellbeing. References Eccles, A. M., & Qualter, P. (2021). Review: Alleviating loneliness in young people - a meta-analysis of interventions. Child and adolescent mental health, 26, 17–33. https://doi.org/10.1111/camh.12389 Hennessey, A., Qualter, P., & Humphrey, N. (2021). The impact of Promoting Alternative Thinking Strategies (PATHS) on loneliness in school-children: Results from a randomised controlled trial in the UK. Frontiers in Education, 6. Taylor, R.D., Oberle, E., Durlak, J.A., et al. (2017). Promoting positive youth development through school-based social and emotional learning interventions: a meta-analysis of follow-up effects. Child Development 88, 1156–71.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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Responsibilities and Resources
|
Who will be responsible for data management?
|
Joao Santos will act as Data Manager and Trial manager.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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Responsibilities and Resources
|
What resources will you require to deliver your plan?
|
For working remotely and at the office, team members will need a fast, stable internet connection, VPN access to the shared network, and a connection to the office phone. A University managed desktop/laptop will suffice.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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Data Collection
|
How will the data be collected or created?
|
With regard to data collection : Existing data from participating schools will be provided via Zendto, a service used by UoM for the transfer of information. All information transferred via Zendto will be encrypted prior to sending, and will only take place after the relevant data sharing/data transfer agreements are in place. Data from the National Pupil Database (NPD) will be accessed through a secure online environment, as facilitated by the Office for National Statistics (ONS). The research team will aim for remote access to NPD data with the ONS approved secure room located in the Ellen Wilkinson as a backup for accessing said data. The necessary steps for requesting access to said data will be followed and the relevant data sharing/data transfer agreements will be set up. The research team will lean on the expertise of the Information Governance team at the UoM. With regard to data creation : All quantitative data will be created by means of online surveys, built using Qualtrics, a GDPR compliant platform. Qualitative data will be obtained either face to face, via semi-structured interviews and focus groups, using audio recorders, or using Zoom. Steps will be undertaken to ensure accurate data versions and versions of all ethics documentation.
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ded90e4d40e9703472c5c61942957cd0
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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?
|
Some measures used in our surveys may be subject to copyright and licensing arrangements, and so the research team will ensure compliance with these. Given the intention to make the project data publicly available, we will explore the prospect of licensing it, following relevant guidance as we do so (e.g., https://www.dcc.ac.uk/guidance/how-guides/license-research- data). Copyright and IPR for the 'new' data generated by this project (e.g. participant and staff survey data) will rest with UoM. Copyright and IPR for the 'existing' data note rests with the Local Authority providing it.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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Storage and backup
|
How will the data be stored and backed up?
|
Data are to be kept in an encrypted Veracrypt container/folder (AES-256 algorithm), in a protected folder on the university's Research Data Storage system, known as Ipsilon. Accessing the data requires 2FA to log into the university's network. The folder with the Veracrypt file can only be accessed by named users, and the container is itself protected with a long password (30+ characters, changed annually). The exception to the aforementioned storage process concerns the fully anonymised teacher interview and pupil focus groups' transcripts. Although these will be stored in the encrypted container described above, during the qualitative analysis process the research team members responsible for analysis of the transcripts will store them in the Passport to Success TEAMS channel (which is restricted to the project team members and is equivalent to a sharepoint channel). Once the qualitative analyses are complete, the transcripts will be deleted from the TEAMS channel and kept only in the encrypted drive. The separate storage process for the teacher interview and focus groups' transcripts is due to the fact that only one person can access the shared drive at one point in time, which would then preclude simultaneous analysis of said transcripts by the different post graduate researchers. Furthermore, access to an encrypted drive may require that some team members contact IT due to technical aspects. This separate storage process allows the research team to still uphold the anonymity of the data, while preventing data analysis delay. The encrypted container noted above is stored on an access restricted data share on the University’s network storage infrastructure which is the recommended location for storing sensitive or critical University data. The storage infrastructure is hosted across two data centres (approx. 4KM apart) for resilience and disaster recovery purposes. Physical access to the data centres is strictly limited to data centre staff and a limited number of authorised IT Services staff. The data centres are protected by physical and electronic access security systems, swipe card access in and out of the data centres and CCTV coverage. The data centres are locked down out of hours and access is discouraged, but can be arranged by prior agreement with the data centre manager. The University’s IT Services utilises Legato Networker Backup domains. Supporting infrastructure comprises disk libraries and both physical and virtual tape libraries. Cross data centre backup is performed, so services hosted within data centre 1 (Joule House) are backed up to data centre 2 (Reynold House) and vice versa. Backup/recovery plans are documented as part of the service install process during the commissioning of a specific service. Each Service is responsible for its business continuity and disaster recovery plans, to which IT Services feed in its technical recovery plans. ITSD operates change and release management processes. All proposed changes to infrastructure hosted, maintained and administered by IT Services are recorded via the Request for Change (RFC) process with changes being reviewed and authorised by a Change Advisory Board (CAB). Research data storage is not backed up to tape in the traditional fashion. However, resilience is obtained through replication and use of snapshots means that files deleted by accident or corrupted can be recovered. Hourly backups can be accessed within 24 hours and daily backups can be accessed within 35 days.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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Storage and backup
|
How will you manage access and security?
|
Only named project staff will be able to access the project data. Accessing the data requires 2FA to log into the university's network. The folder with the Veracrypt file can only be accessed by named users, and the container is itself protected with a long password (30+ characters). Survey data are collected via GDPR compliant Qualtrics, with results being exported directly into the above mentioned encrypted drive. Qualitative data, in the form of audio recordings, will be collected following UoM standard operating procedures, with subsequent storage also taking place in the above mentioned encrypted drive.
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ded90e4d40e9703472c5c61942957cd0
|
dmponline.dcc.ac.uk
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Selection and Preservation
|
Which data should be retained, shared, and/or preserved?
|
The research team will retain a full version of the project dataset until such time as identifying personal information is no longer required (e.g. all data linkage opportunities which require such information to facilitate matching have been exhausted and there will be no additional analyses related to the possibility of a longitudinal follow-up of this cohort). Once personal identifiable data is no longer required the research team will dispose of said information securely, with the support of UoM IT Services. In the longer term, for a period of 20 years, an anonymised version of the dataset will be retained to maximise the potential for further insights resulting from the research. With regard to data accessed via the Office for National Statistics, the research team will abide by the access requirements of the data providers.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
|
Selection and Preservation
|
What is the long-term preservation plan for the dataset?
|
The intention of the research team is that the publicly available versions of the qualitative and qualitative datasets will be housed in the Open Science Framework, which has funding for 50+ years of data access hosting at the time of writing.
|
ded90e4d40e9703472c5c61942957cd0
|
dmponline.dcc.ac.uk
|
Data Sharing
|
How will you share the data?
|
As noted above, an anonymised, publicly available version of the dataset will be housed in the Open Science Framework.
|
ded90e4d40e9703472c5c61942957cd0
|
dmponline.dcc.ac.uk
|
Data Sharing
|
Are any restrictions on data sharing required?
|
The anonymised personal data set - the 'public' version of the project dataset, will be a completely anonymised version which will not allow re-identification of participants. This data set will only contain data created by the project, not existing data collected from the aforementioned parties (e.g., schools, National Pupil Database). Aggregated data will be made available in the form of feedback reports containing summary statistics in tabular and data visualisation formats. These feedback reports will be provided to participating schools, but this too will be completely anonymised and will not allow re-identification of participations. A failsafe is built into the school feedback system such that any scores for any output representing fewer than 10 participants are not calculated.
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ded90e4d40e9703472c5c61942957cd0
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dmponline.dcc.ac.uk
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General Information
|
Name applicant and project number
|
Name applicant = Saskia Stoker Project number = not yet available
|
6a5ace20f81b1bd052d30fdf35fa2f21
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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.
|
Dr. Khadjavi Pour ( [email protected] )
|
6a5ace20f81b1bd052d30fdf35fa2f21
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dmponline.dcc.ac.uk
|
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?
|
The entire study cohort consists of 45 in-depth interviews from a re-used dataset from the WeRin-project. Specifically, after matching the criteria the study included 36 interviews with participants from various Dutch HEIs that offer different educational programmes ranging from Business and Economics to Health Care, Technology, and Creative Industries. The participants were selected using snowball sampling, and the first and second authors’ networks were employed as starting points. Following the interviews, the authors selected several respondents to include in the analysis based on the quality of the interviews and the representativeness of the respondents. The final data set included 25 EE students and 11 entrepreneurship educators. The interviews were conducted during spring 2021 and were recorded, with verbal and written consent, in a face-to-face online setting. An interview protocol with semi-structured questions based on social role theory topics facilitated cross-interview comparisons. All interviews were transcribed verbatim. In the new data set, is collected within one of the higher educational institutions in The Netherlands. Specifically, ten events were observed during the Fall semester between September 2022 and January 2023 (t = 15 hours). The observations focused on how gender is ‘done’ in the context of this learning environment—that is, how student entrepreneurs, their peers, and the educators talked and socialised with each other in the learning environment. Notes were made during the sessions, and more extensive observation reports were produced in critical reflexive journals (field notes and reflexive memos) following the observation sessions (Cunliffe, 2016). Raw data / Processed data Data asset: Data spreadsheet Description: Word (docx & pdf) & MaxQda files including only those interviews that may be relevant for the current project Format: Docx & MX Analyzed data: Data asset: Data spreadsheet Description: Cleaned and processed MaxQda files Format: .MX Other: Research documentation: Tables Analysis software: Word (Docx, pdf) Research documentation: Tables Analysis software: Excel (xlsx, pdf) Research documentation: Logbooks Analysis software: Word (Docx) Research documentation: Manuscripts Analysis software: Word (Docx)
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6a5ace20f81b1bd052d30fdf35fa2f21
|
dmponline.dcc.ac.uk
|
3. How will data and metadata be stored and backed up during the research?
|
How will data security and protection of sensitive data be taken care of during the research?
|
Although the data is pseudonymized, it is still personal / sensitive data.
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6a5ace20f81b1bd052d30fdf35fa2f21
|
dmponline.dcc.ac.uk
|
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?
|
Owner of the data WeRin dataset that is re-used: Amsterdam University of Applied Sciences (AUAS). All WeRin-partners have access to data in Research Drive since it is a multi-partner project. Though the data is in Dutch and not accessible for the other consortium partners. Owner of the new data used: Free University (VU). The PhD-candidate has access to the data in Research Drive. Since it is a single- partner project element. Intellectual property rights: NO
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6a5ace20f81b1bd052d30fdf35fa2f21
|
dmponline.dcc.ac.uk
|
5. How and when will data be shared and preserved for the long term?
|
How will data be selected for long-term preservation?
|
The datasets that are used for the purpose of the current study will be archived for 10 years after the last publication, but this does not apply to the original datasets within the WeRin project (those may be even archived indefinitely).
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6a5ace20f81b1bd052d30fdf35fa2f21
|
dmponline.dcc.ac.uk
|
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?
|
Once the manuscripts have been published the data assets will be registered in PURE Research Portal, on the VU Research Portal.
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6a5ace20f81b1bd052d30fdf35fa2f21
|
dmponline.dcc.ac.uk
|
5. How and when will data be shared and preserved for the long term?
|
Describe your strategy for publishing the analysis software that will be generated in this project.
|
The specific steps taken during the data processing and analyzing, as well as the thought processes behind those, are described in memo's and logbooks in MAXQDA that are saved as Docx-files. All the codebooks and coded datasets are saved in .mxda files.
|
6a5ace20f81b1bd052d30fdf35fa2f21
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dmponline.dcc.ac.uk
|
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)?
|
Storage costs: We do not expect any storage costs. Costs for research data management support: We do not expect any data management costs. Time invested in RDM: 16 hours (writing the DMP), 16x4 hours (publishing datasets related to each sub-study), 16x4 hours (archiving each sub-study), and on average 1 hour/week (other RDM tasks). Costs for Open Access publication: depending on the journal, publishing an open access article may cost up to €3000. However, since this process is part of a PhD-trajectory the work will be published in a special issue of the Journal of Entrepreneurial Behavior and Research which means the costs are covered as part of a agreement with Emerald and the VU for PhD-students.
|
6a5ace20f81b1bd052d30fdf35fa2f21
|
dmponline.dcc.ac.uk
|
0. Administrative questions
|
Name of data management support staff consulted during the preparation of this plan.
|
Nicolas Dintzner
|
ca1e5b178d99c63da806b5c01186d1c3
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dmponline.dcc.ac.uk
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IV. Legal and ethical requirements, codes of conduct
|
How will ownership of the data and intellectual property rights to the data be managed?
|
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. Ownership of the data and intellectual property rights will be managed in accordance with the collaborative nature of the research. TU DELFT, will retain ownership of the raw data, findings, and intellectual property, there is a collaborative component involving a group project called PDPC (Pandemic Disaster Preparedness Center), as part of the Convergence initiative involving Erasmus MC and Erasmus University that I am part of in the project called "Frontrunner 3 Pandemic lessons for flood disaster preparedness", certain findings, rather than raw data, will be shared with this group for collaborative analysis but no personal or raw data. There is no common approach among the project for data related sharing and ownership, therefore, TU Delft owns the data and this research is considered an internal TU DELFT project. The data shared will adhere to ethical and legal considerations, ensuring privacy and confidentiality. Additionally, the outcomes of the studies will be publicly released following the TU Delft Research Data Framework Policy, aligning with transparency and open science principles. Managing data ownership and intellectual property rights will prioritize responsible collaboration and adherence to institutional policies and guidelines.
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ca1e5b178d99c63da806b5c01186d1c3
|
dmponline.dcc.ac.uk
|
IV. Legal and ethical requirements, codes of conduct
|
Where will you store the signed consent forms?
|
Project Drive (:U)
|
ca1e5b178d99c63da806b5c01186d1c3
|
dmponline.dcc.ac.uk
|
VI. Data management responsibilities and resources
|
Is TU Delft the lead institution for this project?
|
Yes, TU Delft is the lead institution for this project, spearheading the collaboration known as the Pandemic Disaster Preparedness Center (PDPC). The partnership involves multiple partners, including Erasmus MC and Erasmus University, and is part of the broader "Convergence" initiative. As the recipient of PDPC funding, TU Delft is central in coordinating and driving the research activities. The collaboration encompasses a multidisciplinary effort, pooling expertise from different institutions to address critical issues related to patient flow logistics during disasters.
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ca1e5b178d99c63da806b5c01186d1c3
|
dmponline.dcc.ac.uk
|
VI. Data management responsibilities and resources
|
If you leave TU Delft (or are unavailable), who is going to be responsible for the data resulting from this project?
|
1st Promotor of my PhD : Tina Comes ([email protected]) TU Delft, Faculty TPM
|
ca1e5b178d99c63da806b5c01186d1c3
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dmponline.dcc.ac.uk
|
VI. Data management responsibilities and resources
|
What resources (for example financial and time) will be dedicated to data management and ensuring that data willbe FAIR (Findable, Accessible, Interoperable, Re-usable)?
|
The resources dedicated to data management and ensuring FAIR principles will be carefully allocated to facilitate effective archiving and accessibility of the research data. Utilizing the 4TU.ResearchData repository, which offers free archiving services, helps optimize financial resources. The commitment to making data FAIR (Findable, Accessible, Interoperable, Re-usable) will be embedded in the PhD trajectory, ensuring that efforts to enhance data discoverability, accessibility, and usability are an integral part of the research process. This approach reflects a proactive strategy to uphold the highest standards of data management and aligns with the commitment to transparency, collaboration, and the broader principles of open science. The investment in these resources underscores the importance of fostering a research environment that promotes knowledge exchange and the long-term impact of the research outcomes.
|
ca1e5b178d99c63da806b5c01186d1c3
|
dmponline.dcc.ac.uk
|
Manchester Data Management Outline
|
If you will be using Research Data Storage, how much storage will you require?
|
Data used for this research should not comprise more than 1 TB.
|
e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Manchester Data Management Outline
|
Who will act as the data custodian for this study, and so be responsible for the information involved?
|
David Buil-Gil / Tomas Diviak / Nicholas Trajtenberg Pareja
|
e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Assessment of existing data
|
Provide an explanation of the existing data sources that will be used by the research project, with references
|
This research may utilise MPS data holdings such as arrest data and police intelligence reports, pending a successful developed vetting application. Simulated data is also intended. Initially, the MPS data will likely be qualitative, consisting of arrest data and/or police intelligence reports. These will be analysed for relevant data, such as information indicating a network tie, or relevant offense information. MPS data will be processed and stored as a spreadsheet in a network analysis relevant format. An example of this is having a column indicate offender identity and subsequent columns indicate the identities of offenders they are connected to. It is possible that time will be relevant to network data at various stages. If this is the case, network data can be stored in separate files representing apparent structure at each time point. Other data (such as records of criminal activity) can be stored as part of the network data (such as having an attribute for each individual) or separately in a dedicated file. This data is not expected to comprise a significant amount of storage space, as such backup and storage will not be problematic (the University of Manchester OneDrive will be sufficient). Access for this research will be dependent on a successful vetting application (approved in April). Future access and re-use, for example in the case of future research, will depend on consent from the Metropolitan Police, as well as anonymisation of any identifying information contained in the initial data.
|
e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Assessment of existing data
|
Provide an analysis of the gaps identified between the currently available and required data for the research
|
The primary gap is the lack of currently available open source data on criminal networks. Understandably, many organisations with the capabilities to gather such data (i.e. law enforcement or intelligence groups) are often reluctant to release it. This has led to many studies on criminal networks relying on the few public access criminal network data sets that are available (such as the Caviar network ), or relying on generated data such as through agent-based models. As such, findings from novel data sets are critically important to ensure that conclusions in research are not simply artefacts of a limited sample size, as research suggests criminal networks operate substantially differently from non-covert networks. Furthermore, simulation studies within network analysis provide a useful tool to allow confidence intervals and network parameters to be estimated using maximum likelihood estimation and permutation significance. This research aims to contribute substantively to the field by addressing methodological issues such as missing data in network analysis.
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e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Information on new data
|
Provide information on the data that will be produced or accessed by the research project
|
Data accessed Arrest records (.docx), police intelligence reports (.docx), other (project partner has mentioned possibility of access to other sources such as archived network data, likely stored in .xslx or .csv format). The data is expected to comprise at least one criminal network. The initial volume of this data (in pure word count) may be quite high, however not to the extent that storage will pose an issue. The data will be parsed for network and activity relevant information with the rest being discarded. Data produced Network Data in graph format (.csv or .xslx), potentially with relevant actor level attributes (such as any offenses committed for a given time frame). This is the standard format for social network analysis research and allows convenient use of a range of dedicated software packages in R. It is also very efficient in terms of storage and easy to re-use, simply requiring the data to be loaded into a statistical environment with the relevant packages. The environment and packages used for this research are all open source meaning that, if permission is given by the project partner to share the data, anyone with the relevant skills would be able to easily use the data. Data produced by simulation will be in .xslx or .csv format. Total scale Less than 1 TB
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e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Quality assurance of data
|
Describe the procedures for quality assurance that will be carried out on the data collected at the time of datacollection, data entry, digitisation and data checking.
|
The data is expected to be of high quality, comprising records supplied by the Metropolitan Police. Guidelines for data extraction will mainly revolve around definition of a tie within the network when using arrest data and intelligence reports. Currently, it is planned to have two levels of tie; weak and strong. Weak ties will refer to network ties with only one data source confirming their existence, strong ties will refer to ties which have more than one data source as support. Single instance co- arrest data will also be treated as a weak tie in the absence of corroborating evidence. If access is given, archived network data will be extracted as is, as these networks were constructed by police intelligence as part of larger scale operations (not simply built with co-arrest data) and verification of this information would be beyond the scope of the research team. These networks will not be assumed to be entirely accurate, the theoretical relevance of them will instead be in the difference in structure compared to more simplistic networks, such as co-arrest networks. Simulated networks will have no quality concerns.
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e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Backup and security of data
|
Describe the data security and backup procedures you will adopt to ensure the data and metadata are securely storedduring the lifetime of the project.
|
Following anonymisation processes at the Met, the initial data will be stored on the P drive or data safe haven as necessary, in a password protected folder with restricted permissions (named individuals only). The password will be given only to individuals comprising the research or supervisory teams. Access to the data will be secured using the universities VPN. Once the data has been processed (and anonymised if necessary), it will be stored securely on the P drive. When accessed, it will be accessed from a password protected computer. It will not be stored on portable storage devices such as USB sticks, nor on any device which is not password protected. Devices themselves will be stored in secure locations, such as staff or PGR offices. The data is only expected to be stored and processed on one computer, which will be encrypted. No paper or other hard copies of the data are expected to be required, however if this expectation proves false, they will be stored in a locked cabinet in a securable room (the Criminology Post-Graduate office of the Williamson building). Access to the data is expected to take place in person, involving an in-person visit to New Scotland Yard where data will be transferred to an encrypted device.
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e9c5477c15ccd5478ccb53981ba05b3d
|
dmponline.dcc.ac.uk
|
Management and curation of data
|
Outline your plans for preparing, organising and documenting data.
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Arrest records will be parsed from oldest to newest. They will be grouped into categories (such as from the same month) and searched for co-occurring names (or unique identifiers post-anonymisation), such as individuals being arrested together. Any co- occurrences will be interpreted as a network link and logged as such in anonymised graph format. Intelligence reports will be analysed in a similar fashion, with evidence of individuals interacting with each other being interpreted as a network link and stored accordingly. Once initial data has been anonymised, the networks generated from it will be stored in separate files. The initial data will be stored in the P drive or data safe haven. Networks data will be stored with file and folder names indicating crime type of network and time point (in the case of longitudinal data), such as "Drug_Trafficking_Jun22_Jun23" being stored in the folder "Drug_Trafficking_1". In the case of multiple networks of this type they will be numbered in the order they were discovered. The final network data will be documented, describing relevant details about each node (person) as well as explaining the structure of the file (graph format excel file). The initial data will likely not be sharable due to the high chance of containing identifying information, however this is not expected to leave the Met before anonymisation. Final documentation will also include information regarding the research question/objectives, a description of how the data was collected and analysed and an explanation of the validation measures in place. Data architecture and other relevant metadata and content will be documented in a ReadMe where the data is stored, as well as in any repository the project partner grants permission for sections of the data to be shared publicly to.
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e9c5477c15ccd5478ccb53981ba05b3d
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dmponline.dcc.ac.uk
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Difficulties in data sharing and measures to overcome these
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Identify any potential obstacles to sharing your data, explain which and the possible measures you can apply toovercome these.
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Sharing the final data should not be problematic, depending on the consent of the project partner. The initial data will not be sharable as described above, however the processed data will be anonymised with all identifying information removed. Precedent for sharing anonymised criminal network information exists in the literature, such as the 'Caviar' and 'Siren' networks.
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e9c5477c15ccd5478ccb53981ba05b3d
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dmponline.dcc.ac.uk
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Consent, anonymisation and strategies to enable further re-use of data
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Make explicit mention of the planned procedures to handle consent for data sharing for data obtained from humanparticipants, and/or how to anonymise data, to make sure that data can be made available and accessible for futurescientific research.
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Consent for sharing will be dependent on the Metropolitan Police. If not pre-anonymised, all data will be anonymised in house before sharing such as by giving individuals a numerical identifier. The final data set will be anonymised to the extent of removing any directly identifying variables, as well as collation or collapsing of key variables which may otherwise be combined with public data to achieve identification, and express permission will be sought from the project partner before exporting any data to a university device. No data will be directly gathered from human participants. Data which could be used to identify an individua directly will not be included in the shared data.
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e9c5477c15ccd5478ccb53981ba05b3d
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dmponline.dcc.ac.uk
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