In general, data organisation refers to the arrangement of data for retrieval. By improving data organisation, you improve the findability of your data, for yourself and for other data users. Additionally, clear structures and clear folder systems make it easier for you to manage your data, which plays an important role with regard to simple and reliable access control for sensitive data, for example.
Clear data storage structures ensure that data is easy to retrieve. This is especially key when multiple people work on and with the data. The easiest way to improve retrievability is to establish and adhere to binding rules and structures from the very beginning of your project.
The goal of data management is to maintain an overview of the existing data, as well as all backup copies and editions, at all times. In this way, data loss is minimized, as is the risk of working with outdated files.
A clear data structure is also essential for the preservation and reuse of the data. By following a few rules for data organisation right from the start, you can avoid the tedious task of sorting your data after project completion.
Most likely, your Research Unit will already have a well-established storage structure in place, which can simply be adopted.
The following recommendations generally apply to data storage systems:
- Store all data in folders and subfolders, sorted by structure and content.
- Work with a maximum of three subfolder levels.
- Name the folders so that the content is clearly recognizable.
- Use the same folder structures in all projects, if possible.
It is advisable to work with predefined standard systems within working groups or projects. In addition to a clear description of the content, these should also take into account the development and modification of documents and data sets during the project.
It is advisable to keep the following guidelines in mind when naming files:
- Number each data set on an ongoing basis.
- Choose short, meaningful names. The names should consist only of letters, numbers, underscores and hyphens. Avoid spaces, slashes, umlauts and special characters. Only use abbreviations that are listed in your data naming rules.
If uniqueness requires the file name to contain multiple elements, the name should begin with the most common element and then become more specific. In any case, make sure that the file name does not get too long. It is recommended to separate the individual elements with an underscore.
If you do not use automatic version control, you should manually assign a version number and the date in YYYYMMDD format to altered data and documents.
Mark final versions of edited files with the word "final". Handle this marking with care to avoid constructs such as "...final_final_final...".
In the event of multiple editors, specify the editor by using initials or name abbreviations.
Example: 01_Labordaten 2017_V2_20181121_AW
You can use tags to actively assign keywords to files. The tags help you to find and organize files, for example by searching for tag names across folders. A file can have an unlimited number of tags.
It is advisable to keep the following guidelines in mind when naming tags:
- Keep the names short, use one or two words only.
- It is important to be consistent with names, also with regard to upper/lower case, singular/plural, symbols, etc..
- You may display different hierarchy levels in the tags, for example raw data (superior) + X-ray images (inferior).
Depending on the software, there are different ways to assign tags. For Windows files, for example, you can add tags in the "Tags" field of the “Save As” dialog box or in the detail area of the Windows Explorer. After previous selection, tags can also be assigned to a group of files at the same time.