Making your research data available via the Research Data Repository can:
- Enable greater scrutiny of research outcomes
- Facilitate new research and collaborative partnerships
- Enhance the impact and visibility of your research
- Reduce the cost of replicating data collection
- Offer a safe and secure storage space for your work
- Provide a permanent and stable DOI for your dataset(s) if not previously published elsewhere
- Increase your citation and download count
- Promote and enhance your academic reputation
- Aid compliance with Research England requirements for the next REF and funding body and publisher mandates
Research data falls into several categories and includes:
- Observational: data captured in real-time, usually irreplaceable. For example, sensor data, survey data, sample data, neuroimages.
- Experimental: Data from lab equipment, often reproducible, but can be instrument specific. For example, gene sequences, chromatograms, toroid magnetic field data.
- Simulation: data generated from test models where model and metadata are more important than output data. For example, climate models, economic models.
- Derived or compiled: data is reproducible but expensive. For example, text and data mining, compiled database, 3D models.
- Reference or canonical: a (static or organic) conglomeration or collection of smaller (peer-reviewed) datasets, most probably published and curated. For example, gene sequence databanks, chemical structures, or spatial data portals.
Research data can take many forms, for example:
- Documents (text, Word), spreadsheets, databases
- Questionnaires, transcripts, consent forms
- A/V files, photographs and film
- Digital objects acquired and generated during the process
- Models, algorithms, scripts
- Contents of an application (input, output, logfiles for analysis software, simulation software, schemas)
- Methodologies, workflows and standard operating procedures
- Correspondence (electronic mail and paper-based correspondence)
- Grant and ethics applications
- Technical and research reports
Data deposited to LJMU Research Data Repository should be in an open file format wherever possible. UK Data Service provide full information on recommended file formats for data sharing, reuse and preservation.
Deposit your data via Symplectic Elements, please follow the guidance for depositing research data provided or email the Researcher Engagement team. We will discuss with you what you want to deposit, and guide you through the process.
Data in the repository should adhere to the FAIR principles:
- Findable, Assessable, Interoperable and Usable.
To ensure data meets these principles, metadata should be as comprehensive as possible and all datasets should be accompanied by a readme file which gives details on when and how the data was created/collected and how it can be used (if there are any particular instructions for opening files, etc.)
Any abbreviations used in the data should be expanded in the readme file and any column or row names used in a spreadsheet should be self-explanatory or detailed in the readme file.
Research data and records should be: accurate, complete, authentic and reliable. As well as this, the FAIR data principles should be followed; data should be:
- Findable - data and supplementary materials must have sufficiently rich metadata and a unique and persistent identifier
- Accessible - metadata and data are always available and obtainable; even if the data is restricted, the metadata is open
- Interoperable - data exchange and reuse between researchers, institutions, organisations or countries is possible
- Reusable - data and collections have a clear usage licenses and provide accurate information on provenance
A readme file gives details on when and how the data was created or collected and processed. How it can be used and if there are any particular instructions for opening files, etc.
Any abbreviations used in the data should be expanded in the readme file and any column or row names used in a spreadsheet should be self-explanatory or detailed in the readme file.
Write your readme file as plain text and avoid using proprietary formats such as MS Word where possible.
A readme file should include the following information:
- Title of dataset
- Contact details
- File name structure
- File formats
- Column headings for tabular data
- Data and file overview, short description of what the file contains, when and how it was created
- Licences or restrictions placed on the data
Use our LJMU template readme file to ensure that you have provided all the information needed when making a deposit to the LJMU Research Data Repository.
There is a wealth of expertise within LJMU on related matters such as:
For information on commercially exploitable data, contact the Knowledge Exchange and Commercialisation team.
For Intellectual Property (IP) issues, contact the Head of Knowledge Exchange for IP: Jane Townend.
