5S Data Model for Research Data Management
In this project we want to present you the five steps in 5S Data for research data management. The steps are designed to help researchers build an organizational structure for research data and maintain this system over time. Below, you find a link to each step visualized with a comic:
TKFDM's first online Coffee Lecture on Jan. 27th, titled "5S Data: Organization is not a 4-letter word!" presents all the steps of the model in a compact format. If you are interested in learning more about the origin and popularisation of the 5S methodology, the following section is for you.
Origin of 5S
The 5S methodology originates from the philosophical concept of "Kaizen" from Japan, which means "the action of making bad things better". These have been effectively implemented in Toyota's production system since the 1950s, which is why its definition, according to the New Oxford American Dictionary, is: "a Japanese business philosophy of continuous improvement in work practices, personal efficiency, etc.". Following this philosophy, Toyota has designed five steps to improve the production process through various methods. All of them start with the letter "S" to make them easier to remember.
|Set in Order
|Anordnung zur Regel machen
|Alle Punkte einhalten und verbessern
Since the Japanese terms are difficult to read and understand outside of Asia, an equivalent model was developed in English which also consists of 5 steps beginning with "S". A German translation following the same scheme proved to be difficult, so the steps were rewritten starting with the letter "A". Therefore, in addition to the international 5S method, one also sometimes speaks of the 5A method.
Other well-known production companies such as Boeing or Hewlett-Packard have also aligned their companies with the 5S methodology in recent decades. However, the method is not only used for production, but also for administrative organizations or safety guidelines. It quickly became apparent that the application of the 5S method is not only suitable for optimizing manufacturing processes, but can also improve the process of gaining knowledge and project work. For example, in 2019, the University of Helsinki made the connection to research data and presented the method in the form of a poster on its website in their role as a member of the Research Data Alliance (RDA) 2020.