What is Data Management?

In the course of a project, research data pass through various stages. With proper research data management, you process your data securely and efficiently at each stage and make it usable beyond your publication. Good data management starts in the planning phase. At the latest when you start collecting data, data documentation begins as well. After analyzing and publishing initial results, you also might want to share your data. To increase quality of data, it is recommended to not only share the data but also make it FAIR.

Data organization begins in the planning phase (e.g., determine folder structures), but becomes especially important when data is being collected.

When naming files, keep in mind:

• Choose short but meaningful file names.
• File names can also be used for further classification of files.
• Avoid spaces or special characters in file names
• Use version control (v.1.0 for the original, v.1.1., v.1.2, etc. for minor changes, v.2.x, v.3.x for major changes)
• Filenames with year-month-day start in the form YYYYMMDD or YYMMDD so that the files are listed chronologically

When organizing the folder structure, it helps if the data is divided into categories, e.g. by project/subproject, time, date, file type, location, etc. The folder structure should not be more than 3-4 levels deep.

A Data Management Plan is created at the beginning of a project and describes how data is created, processed, secured and finally archived and shared in a project. Basically, anyone and everyone can set up an individual DMP.

What goes into a data management plan? The Swiss National Science Foundation provides guiding questions to complete a DMP. To write a DMP, you can also consider the data life cycle and note down important aspects for each step.

A DMP helps you to structure, describe and store your research data in a meaningful way and to make the data usable for others. If you have written a DMP, you can manage your data and often the entire research project more efficiently, keep track of your own data output,  guarantee the continuity of data management if project staff leave or new researchers join, and are safe(er) in dealing with sensitive or personal data, as well as copyright issues.

More and more research funders require a DMP, including the SNSF and the EU.

More information can be found here: Requirements ORD

Science IT supports UZH researchers in technical matters for software solutions, data storage, data management and data visualization.