Datamanagement
Data management refers to creating, saving, updating, making available, archiving and long-term storage of research data. The final goal of this process is often defined in terms of the FAIR principles: 'Findable, Accessible, Interoperable and Re-usable'.
This involves thinking carefully, before you start collecting or creating data, to make sure that your data is findable, accessible, interoperable and re-usable. Not only for others, but also for your own future use.
For more information on data management, see the University Library website.
Responsible management of research data is part of good research. The Netherlands Code of Conduct for Research Integrity (2018) recognises the “growing importance of the way data is used and managed and the developments in the area of open science.” Research funders such as NWO require the writing of data management paragraphs and plans. They follow the guiding principle “as open as possible, as closed as necessary” when it comes to making datasets available for reuse.
The Research Data Management Regulations of Leiden University provide a framework for research data management policy. The Department of Economics and the Institute for Criminal Law and Criminology have their own data management protocols.
Data Management Plan (DMP)
The Research Data Management Regulations of Leiden University require all researchers to draw up a data management plan (DMP) before starting a data collection.
A data management plan is an excellent tool to structure your thoughts about the dataset(s) that you will collect or create. It outlines your practices for collecting/creating, organising, protecting, storing, documenting and, where possible, sharing the data. This will improve the management of your project. At an early stage, you will address practical questions, privacy issues, costs or potential risks such as loss of data or unauthorized access. Others, such as a supervisor or a collaboration partner, have information to understand decisions about how you deal with your research data in one place. In many cases, planning and thinking ahead increases the quality of the dataset and its documentation. Thus, it will enable the reuse of your data, for follow-on research and, where possible, for the long term.
See also the Tips and tricks for writing a Data Management Plan
- Should your research involve the collection of personal data, for example when conducting interviews, you will have to take one additional step. You would have to submit a Research Data Processing Inventory form to the privacy officer. It helps to think about risks in your research and provides information on corrective measures and available tools. In addition, a review by the Ethics and Data Committee might be necessary. Writing a DMP and creating the Research Data Processing Inventory are part of the preparation of the review.
DMP in PhD trajectory
PhD candidates, PhD fellows and contract PhDs of Leiden Law School are required to follow a research data management course as part of their training. (Non-funded) external PhD candidates are welcome to join the course or a DMP workshop offered by the library. Data management in complex research scenarios could best be discussed early on with the supervisors and where needed with research support staff.
All PhD candidates are required to draft a DMP at the beginning of the trajectory to be checked and approved of by their supervisor. Afterwards it should be reviewed and updated when major changes occur. The final version of the DMP will be submitted together with the dissertation.
In the PhD trajectories where an evaluation meeting is being held at the end of the first year, the plan should be submitted together with the other documents for the meeting.
When should I write and update my DMP?
New PhD-candidates will write their first draft of the DMP as part of the Data Management Training of Leiden Law School. Usually, this happens within the first 6 months of the PhD trajectory, before any data will be collected. During the course PhD-candidates discuss the DMP with their supervisor(s) and will receive feedback by one of the instructors.
Though not obligatory for (non-funded) external PhDs, they are also very welcome to join this course or a DMP-workshop offered by the library.
Should the research project include the processing of personal data and/or require ethical review, the data management plan will have to be submitted to the privacy officer and/or Committee Ethics and Data. The consult and/or review needs to take place before the start of the data collection.
In order to prevent any delays in the procedures, it is strongly recommended to contact the Data Steward well in advance for a DMP-check before submitting the documents.
Towards the end of the first year, PhD candidates (employees and contract PhDs) submit the DMP together with the other documents needed for the evaluation meeting.
When preparing (a new version of) the DMP they can approach the Data Steward for advice and feedback.
Starting and ending a new research phase such as data collection, data processing or data analysis are also a good moments to review and possibly update your DMP. You might plan the new phase in more detail (software usage, size of dataset etc.) or know if something of the finalized phase did not happen as anticipated earlier.
DMP Submission together with the manuscript. As part of the finalization of the PhD-trajectory, the DMP will be updated to the final version and submitted together with the manuscript. The supervisor will formally declare that the DMP “which applies both to digital and non-digital data, has been observed conform the Research Data Management Regulations of Leiden University.”
Please note that also the documents submitted to the privacy officer might need a final update.
If you did not do so during the research, you will have to submit the dataset to a (certified) repository. In the case that data are not suitable for sharing, you should register the metadata of your dataset, in order to comply with the data management regulation. You can contact the data steward with questions regarding the final DMP draft as well as archiving and metadata registration.
Research without data collection/creation
Some researchers at Leiden Law School do not collect or create any data for their research, some might not be sure if this is the case. Please contact the data steward in case of doubt.
Regarding the DMP-requirement, some research projects at Leiden Law School, need to fill out only parts of the DMP.
- A data management plan is needed when the researcher creates or collects new research data or analyses existing datasets with qualitative and quantitative methods and by this generates processed and analysed data.
- In "classic" legal research (doctrinal research), when the data used consists of publicly accessible documents only, such as statutes, rulings, annotations, scientific articles and books, the completion of the DMP-form is a formality, performed to declare formally that the project does not generate data and to specify the location of the public data.
- Filling in the DMP can help to improve the process of doing research and reduce the risks such of the risk of losing files. It is strongly recommended to answer the questions about organisation and documentation of the files as well as storage location and back-ups.
Support at Leiden Law School
In general, research support staff at Leiden Law School is your first point of contact:
- the data steward for data management questions during all phases of the research;
- the information manager for questions about university infrastructure, tools and software;
- the privacy officer for questions about privacy and data protection;
- the ICT contact person to apply for ICT facilities for research
- the Ethics and Data Committee for ethics and data/privacy review of research proposals and
- the Graduate School of Legal Studies for questions with regard to procedures in PhD trajectories.
Information and training
The Centre for Digital Scholarship (CDS) at the University Library is offering several trainings on data management. The CDS website offers plenty of information such as a data management checklist, best practices, a catalogue of research data services and information on copyright and intellectual property.