Research Data Management

Yes, it is safe to store research data on your staff or student drive. Oxford Brookes has an enterprise version of Google Drive. It adheres to the University's data protection requirements. Some funder's guidance can expressly exclude Google and other public clouds. In those cases, you must check with the funder to see whether an enterprise version is acceptable. However, you need to be aware of the level of risk that your data presents There are specific datasets for which there are better solutions than Google Drive.

The research data manager DOES NOT write data management plans but provides guidance and support in developing them. If you need assistance, please contact the research data manager at nlewin@brookes.ac.uk with the plan for review. If the plan is part of a grant, please also include, at a minimum, the methods and risk section of the research protocol.

Yes, A data management plan is required of all research at Oxford Brookes, irrespective of funding status, to delineate and document rights and responsibilities regarding data. Compliance with data protection obligations and preventing potential disputes concerning data ownership are key considerations. It is important to remember, you are accountable for all the data you hold, including any data your students collect. The academic integrity policy put data management responsibilities on the researcher.

Yes and no, it is more complex than open or closed. The Oxford Brookes Research Data Management and Intellectual Property policies both recognize that data should be made as open as possible, as closed or secure as needed. The University asks researchers to adhere to ethical and reasonable sharing practices that are inclined towards openness. However, the University focuses on excellent academic practices to promote data reuse. Open research practice is strongly encouraged and all data should follow FAIR principles (Findable, accessible, interoperable, and reusable), irrespective of immediate sharing intentions. Even in cases where data sharing is not pursued, providing metadata and transparent reasons for data unavailability is obligatory. In this case, sharing would mean writing a data access statement detailing how access can be obtained in restricted circumstances. In general, either data or metadata should be deposited in a repository. However, you need to choose the correct level of access then and attach the appropriate license.

No, you need to decide how long to keep the data in data management plan. It is unlikely it will be less than ten years but different data retention rules might be mandated by funder conditions of grants, or terms outlined in a research contract. As a default position, data preservation for a minimum of ten years is mandated, with the specifics of data sharing contingent upon decisions outlined in the Data Management Plan (DMP). You should also consult the records retention schedule when deciding what retention period to apply. Remember, data needs to be reviewed at the end of a 10, 15 or 20 years. You need to think about what will happen at the end of the retention period and who will be responsible to make decisions.

It generally does apply.  All research that collects data requires research data management. Within humanities research, data encompasses all elements utilized in generating research outcomes. While archival research may be perceived as secondary research not traditionally classified as data, creating sub-datasets or collections from existing sources represents a novel organization of information that constitutes an intellectual product. Furthermore, various forms of expression, such as performance, art, and literature, also yield datasets. If information is being collected to support a research result, it is data. However, common data management planning guidance might assume that you are collecting data such as interviews or measurements. If you find that a template is not suitable for your kind of research so you should contact the research data manager for assistance. Data planning tools can be customised.

There is no one place; the University is not prescriptive. You should put the same amount of thought into choosing a repository as you do into choosing a journal. Targeted impactful dissemination is the key.   Packaging data alongside tailored training materials, or organising public participation workshops for specific user groups is deemed an effective strategy for data sharing. Another method is to use a repository that has a good record of generating downloads and citations e.g. Open Science Framework.  Oxford Brookes researchers are advised to leverage the free institutional repository RADAR for streamlined open data dissemination practices. Arkivum is used for sensitive data. Funded researchers should prioritize the funder's preferred repository.

Yes, it is necessary. In the first instance, data management ensures that you collect data effectively, handle messy data, and introduce data quality. In other words, it's a necessary research component. Data management allow this work to be recognised, recorded and credited.  Formal data management makes that element of research work visible to the researcher but all research involves data management. Based on international averages, you should expect to spend between 5 and 15 % of your research budget on research data management, mostly in staff time. However, all of these processes can be budgeted into a research grant. If you need to reduce the time or the money spent on data management, then ask for assistance from research data management or scholarly communications at the library. There are many different ways to manage data within resource constraints. 

You need to contact the data curator of your intended repository and deposit data. RADAR does provide DOI’s for open data. Unfortunately, the process of getting a DOI can be placed under immense time pressure because certain journals requires that the data has a DOI and is in a repository before a paper is published. So, it important to know that to get a DOI, you will need to do data curation. Data curation transcends a file upload; it necessitates a meticulous preparatory process. This includes crafting metadata for datasets and structuring them in alignment with FAIR principles (Findable, Accessible, Interoperable, Reusable). Researchers should anticipate tasks such as data cleaning, organization, annotation, and potential pseudo-anonymization before embarking on the sharing phase after the end of a project.  If you can, consider adding a budget line for data curation. 

You need to have a research data management discussion with your line manager to sort out how you will manage the data you are holding.  Cleaning up data when leaving the University can be a daunting experience but help is available. Data curation is essential to ensure that your data is maintained and supported appropriately. Before leaving, it is crucial to discuss your or any student's data that you are responsible for, with your research lead/ line manager. Don’t forget that to curate the data, you also need records such contracts, ethical approvals, protocols, and SOPs. You can always ask for assistance in creating or updating data management plans.

Mostly, staff members take copies of their data and records when they leave. However, the University is flexible, and discussing research data can result in many types of arrangements. A contract or a data management plan that clarifies rights and responsibilities might already exist. If that is the case simply record that nothing has changed. Sensitive data might need special arrangements.

It is vital to have a record of this discussion reflected in a research data management plan. Once the plan has been discussed, it should be executed, often by archiving the data. The plan must be retained as a record. If you have any concerns or questions about leaving the University and how it may affect your legal rights, please ask your research office for guidance.