Storing data during Research

Planning & Design
• Documents from ethical reviews and compliance e.g. DPIAs
• Licenses
• Data management Plans & Checklists
• Informed consent form templates
• Data Transfer Agreements

Data Collection & capturing
• Raw data from lab results
• Interview recordings
• Notes from observations
• Excerpts from existing data
• Encrypted data collection tables with sensitive data

Managing & Collaboration
• Results of data analysis e.g. statistical tables, audio transcripts, lab notes
• Protocols and Standard operating procedures
• Pseudonymized results

Sharing & Publishing Data
• Curated data e.g. selected data for publishing

Network drives are suitable if you work or to collaborate within the university (and can be approached through a VPN). The (U- and O-drives) for UU make automatic regular backed-ups you can also store personal data here. These drives may not be designed to save your research data.

1. Portable devices (e.g., USB sticks, external hard drive or personal laptop) are suitable for holding short term copies of your data file for transport, but they are vulnerable for loss and there is no automatic back-up of your data. If you use portable devices, make sure you:

• choose high quality products from reputable manufacturers.
• regularly check the media to make sure that they are not failing.
• make regular back-ups.
• protect (e.g., encrypt) the device in case of personal data.
• periodically 'refresh' the data (that is, copy to a new CD, disk, or USB flash drive)
• Note that external drives are not an archive for permanently storing your data. The hard drive will eventually break down. Migrate data to newer media every 3-5 years.

Cloud services are suitable for working remotely and collaborating with external partners. Be sure to check if your selected cloud service makes regular back-ups, if it falls under European jurisdiction and if it is a trustworthy partner. If not, this particular cloud service could be a bad idea. Most cloud storage solutions are owned by private companies, so it's important to remember to be aware that (1) your data may not be private as the company probably has the right to look at it and might have the right to do what it pleases with that data and (2) that company may go out of business or otherwise become obsolete.

• For Utrecht University researchers, OneDrive is the recommended cloud service to use. It allows storing personal data and collaboration, is linked to your Solis account, is backed up regularly and can be accessed via your local file explorer.
• An alternative to OneDrive is SURFdrive, which allows 500GB of storage space per university user and allows easy collaboration with researchers from many Dutch research institutions.
• Most Educational Institutions will have the right to access Your Data in accordance with the Institutional Policies" - meaning the university can look at what you store in One Drive for example.
• Please do not make use of third-party cloud solutions like Google Drive and Dropbox, especially when you work with personal data.

Storage space for researchers to deposit data sets associated with their research. They are specifically designed for sharing and preserving research data. They may be categorized into:

• Institutional Repositories (IRs); are affiliated with a researcher’s institution e.g., YODA, Dataverse nl, SURF Drive;
• Domain-specific or Disciplinary Repositories (DRs); are discipline-specific and often operated by a professional organization, a consortium of researchers, or a similar group e.g., NASA Space Science Data Coordinated Archive (NSSDCA);
• General-purpose or Open Repositories (ORs) allow researchers to deposit and make their data available regardless of disciplinary or institutional affiliation. e.g., Zenodo, Figshare, Dryad.

See Recommended Solutions for storing research data in the UU Data Storage Finder

Your raw data is the basis of all analyses that you plan and allows retracing of all steps you make afterwards. Therefore, it is important that raw data is not accidentally overwritten or changed. Store it in a separate, protected location, for instance a separate folder that is set to ‘read only’. Make a working copy of your raw data to do your actual analyses on. To check if the raw data is still the same, consider checking whether the data that you currently store is the same as the original. You can check data integrity with a checksum-checker (for MAC or UNIX users this is provided by the operating system).

Your working files are frequently changing. Imagine you have several copies at different locations. How do you keep track of what copy contains the updates you most recently made? If you choose the wrong file, it takes time to merge both documents afterwards. To avoid confusion, you select ONE place where the master copies of your work are located. All other copies are temporary and should be placed back or synchronized with the master copy location, at regular intervals, fixed times, or after each edit.

Backing up data means making and storing copies of your data in more than one place.

If there is a calamity or accident at your master copy location, all your work could be lost. It is important to have back-ups of your master data files, including one at a separate location. There are several back-up schemes to choose from. What you choose depends on:

• The dynamics of your data: how often are new versions created?
• The time a back-up takes
• The space you have
• The costs of making a back-up
• The risk of losing important information between back-ups

If you use a university-supported storage medium, you are almost certain that regular back-ups of your data are made automatically. In that case, inform yourself on the scheme used and how you can restore a back-up, if necessary.

Versioning ensures tracking the development of a data file and identifying earlier versions, when needed. A few simple ways to do this are:

• Adding an extension to the file name such as 'v1.00', 'v1.01', 'v2.06' with ordinal numbers indicating major and decimals minor changes.
• Using dates in the filename (preferably in the format YYYY-MM-DD).
• Adding a version control table (or file history or log file) to document what has changed between versions.

As long as the original 'raw' and definitive copy are retained and processing is well documented, the intermediate working files can be discarded. Keep only the major versions for longer term retention.

A well-arranged folder structure in which folders and sub-folders are hierarchical and follow each other logically, is invaluable in quickly navigating your data and finding what you require.

• Preferably think about a logical folder structure before your study (e.g., in your DMP). What kind of files will you likely produce, what would be best clustered together in folders?
• Make sure the folder structure is not too flat and not too deep; about three steps down is often workable.
• Make the folder structure stable and scalable, so you can expand without having to rearrange the structure completely. 
• Don't use folders with possibly overlapping contents on the same level.

• Build filenames from (shortened) elements, e.g., project name, project number, name of research team/department, measurement type, subject, date of creation, version number, etc.
• Explain your coded elements somewhere (e.g., in your DMP), so others and your future self will be able to crack the codes.
• Always go from generic to specific. This will help you find sets of files with a simple sorting of filenames in your folder.
• Keep filenames short, preferably max. 25 characters.
• Only use characters from the sets A-Z, a-z, 0-9, hyphen and underscore. Don't use special characters such as &%$#), as different operating systems can assign different meanings to those characters.
• Ensure file names are independent of location; this will avoid problems when moving files.
• Some good examples:
  • ‘NTC_wp5_MA_exp1.csv’ (project, work package, type of measurement, experiment ID of the measurement)
  • MicroArray_NTC023_20141031.xls (content description, project number, date: international standard)

The information in data files can be protected by:

• encrypting restricted materials. By doing so, your files will become unreadable to anyone who does not have the correct encryption key. You may code an individual file, but also (part of) a hard disk or USB stick. Be sure to keep the encryption key in a safe place, as you will lose access to the data if you lose the key;
• procedural arrangements like arranging access conditions in a consortium agreement and, if necessary, through non-disclosure agreements with participants and data handlers (See the guide on 'Legal instruments and agreements');
• not sending (confidential) data via email or through File Transfer Protocol (FTP). Instead, use services like SURF file sender and permitted cloud solutions;
• destroying data in a consistent and reliable manner when needed. Note that deleting files from hard disks only removes the reference to it, not the file itself. Overwrite the files to scramble their contents or use secure erasing software. For USB and CD/DVD, physical destruction works best to erase data.

The computer you use to consult, process and store your data, can be secured in the following ways: 

• Use a firewall to protect your data from viruses;
• Install anti-virus software;
• Install updates and upgrades for your operating system and software;
• Only use secured wireless networks;
• Use passwords of password sentences and do not share them with anyone, unless absolutely necessary. Do not only use passwords on your university computer, but also on your laptop or home computer. If necessary, secure individual files with a password. Be sure to keep your passwords safe, for example using a password manager like LastPass or Keepass;
• Do not provide others with your login credentials;
• Make sure you can wipe your device in case of loss or theft.

In the event that you have not stored your data in a shared/collaborative environment (see storage options above), it is important to ensure that you share files or data in a manner that ensures safety, confidentiality (for personal data) and data integrity. SURFfilesender (part of SURF), is recommended as the safest way to share (large) files within the UU and with external collaborators. Find more information on using Surf file sender  on the UU website sharing files securely.

For example, collect as little personal data as possible and pseudonymize the data as early as possible. In the guide 'Handling personal data' we will go into more detail.

There is a data breach in case when an incident involves the university’s employees or students or IT resources. If you suspect a data breach, please report it as soon as possible via databreach@uu.nl. See more information here.