Store and organise

Storage of research data

It is important that data is stored securely throughout the entire research process. As a researcher, you must prevent unauthorised access to your data, and you must ensure that data is backed up and does not disappear. Different types of data may require specific measures, for example if you are working with personal data, sensitive data or very large volumes of data.

Data that does not contain personal data or other sensitive information  

Use the servers that are maintained and backed up by the Division of IT at Lund University or the solutions offered by your own faculty’s IT department. Consult your data steward if you are unsure which solution you are to use.  

The Division of IT offers the “research project folder” service free of charge to researchers who need to store data. Such a folder can be shared with other people (provided they have a LUCAT ID) within a research project/equivalent, and they can be assigned different read and/or write access.  

The service "research project folder" (in Swedish) 

Data containing personal data or other sensitive information  

Personal data and other sensitive data must not be stored in cloud services. Instead, use LUSEC, a platform for storing, managing and analysing personal and other sensitive data in a highly secure way. This is done, among other things, through encryption, two-factor authentication, secure user environment and controlled access (at Lund University or remotely). Access to LUSEC can be purchased from the Faculty of Medicine.  

About LUSEC at the Faculty of Medicine internal website 

You can also store sensitive data on encrypted hard drives in a locked safe if necessary. In these cases, it is important to handle these hard drives and USB sticks in a secure manner in accordance with procedures established and agreed within your department.

Large volumes of data  

Are you working with large amounts of data and need storage and calculation services for large data sets? In that case you can use LUNARC, which is a research infrastructure at Lund University. LUNARC provides large-scale computing and storage resources for calculation and storage.  

LUNARC

Document registration during the project  

Lots of documents will be created during the project. Right from start, during the storage process, it is important to think about how these documents will be handled and when they will be registered. Data files and related documentation will also be managed and intermediately stored during the project. If there is a reason to dispose of parts of the data, you need to make specific disposal decisions which are to be signed by the head of department.    

Preservation and disposal of document

Organisation of research data  

Working with data in a structured way can make it easier both during the project itself and before it is archived and potentially made available to others. It helps you and your project colleagues keep track of data throughout the process. It does not need to be very sophisticated, but thinking about how to organise the material can save a lot of time and effort. This may involve things like thinking through file names and formats or describing data in a structured way using metadata.

Structure of folders and files

Collected data should be organised in a well thought-out folder and file structure. Name your files and folders systematically and according to a structure that is intuitive or well described. Names should preferably include time, place and other information relevant to the material. It is also advisable to find an easy way to keep track of different versions of your files, for example by naming the files with edit dates or by using version management.  Large datasets managed in databases should be organised and described according to current standards, which are often regulated by the repository or database type.

Folder structure, file names and versioning (SND.se)

File formats

If possible, be sure to store your files in persistent formats that are open, commonly used and not tied to a particular supplier. It helps if you plan for and use the right format when you create the information, as it can be difficult to convert to durable formats later on when sharing and archiving your data. For example,  if you want to save and archive spreadsheets that you have created in Excel, it can be useful to save both as XLSX files with all the content, such as graphs and formulas, and as CSV files along with a description, attached as a PDF, of how you produced the graphs or formulas. This is to ensure that the format is both specific and durable.  

Choosing a file format that fulfils the above criteria may not always be possible. For example, there may be standards and conventions in certain subjects that determine the choice of format. If specific instruments, analytical tools or proprietary software are used, this may also determine the file format. To facilitate reuse, it may be a good idea to include information in the metadata about how your data can be read (e.g. what software is required) and to make any proprietary software available together with your data.

Choosing a file format (SND.se)

Electronic archiving       

Use metadata to describe your files  

Metadata is structured descriptions of your data, which you can use to make your data searchable and understandable to someone else. Metadata is not only something to consider once research is complete and you are describing what you have done, but also a way to provide meaning and structure from the beginning. One example of how to do this is to use a clear and descriptive method of naming your image files right from the start, when you transfer the images from your camera to your computer.  

Different types of metadata

There are different types of metadata that you can use in various ways. Descriptive metadata makes data searchable and includes, for example, title, abstract, author, geographical area and DOI (digital object identifier).  Structural metadata allows others to use your data, and can include, for example, information on the number of variables, number of research subjects, file structure and structure within the files.  Administrative metadata provides information on how data can and may be used, such as whether there is a licence or embargo, technical information (what programs are required to open the files), what file formats exist and the files’ version history.  

Describe your datasets in a README file

An easy way to create metadata is to describe your datasets in a README file and store it alongside the datasets, for example in a research data folder if you use LU's local storage solution. Sharing your data via a repository usually requires you to fill in a form with details about your data (e.g. what the dataset includes, how it was created and how it was analysed). This will generate metadata based on what you have entered and also make your data more easily searchable for others who want to use it.  

There are different standards for how to describe your data using metadata. If you are using a form in a repository, standards may be built into the forms. If you are going to describe your data yourself in a README file use the University template.

Document your research data in a README file