Publishing
Research Data Management

Data Lifecycle - data cycle vs. project cycle

From planning to subsequent use, research data pass through different phases in the research process, with each station in turn being associated with a variety of tasks.

In the following, the handling of research data is examined from two different perspectives. On the one hand, the individual stages of the lifecycle of research data are illustrated and, on the other hand, the RDM requirements in different project phases of a research project are explained.

Research data in data cycle

Planning Project

planning data management (create DMP)
search for existing data

Collecting Data

perform experiments, surveys, simulations, etc.
request permission to use data

Processing Data

acquire, digitize, transcribe, translate data
check, validate, purge, anonymize data
document data and add metadata
administer and secure data
prepare data for long-term archiving (file formats)
interpret data and derive conclusions

Publishing Data

clarify legal and ethical aspects
set licenses
select publication location (repository, journal)

Archiving Data

select final data versions
select location for long-term archiving (data medium or open repository)

Reuse Data

verify data resp. conclusions
use data for teaching or research projects

Research data in project cycle

What should be considered before starting project?

Every research project generates new data or uses known data as a basis. Therefore, you should define rules for the future handling of these data already before the start of the project. Some third-party funders even explicitly require the creation of a data management plan (DMP) as well as the generation of FAIR data or open data. In addition to establishing initial rules, legal and ethical aspects related to the data should also be clarified in advance.

How can the data be managed during project?

Successful data management is based on a well-planned and consistently executed infrastructure. During the project period, you should therefore organize the data in a structured and clear manner and document it sufficiently. In addition to data management, however, data backup and security also play a major role. By selecting suitable storage media and locations, making regular backups and using suitable passwords, you can not only protect the data from loss but also prevent unauthorized access.

How can data be made available after the end of project?

After the end of the project, you should make the data publicly available for long-term subsequent use, insofar as this is permitted in the project. Some third-party funders even explicitly require this as a funding condition. Publication or long-term archiving can take place in a data repository for example. For this purpose, suitable file formats for archiving should already be used during the project and persistent identifiers should be assigned to the data sets. After clarifying all legal and ethical aspects related to the data (data protection, copyright, etc.), a suitable license should still be assigned. As far as possible, this should be an open license that turns the data into open data that can then be freely used, reused and further disseminated by anyone.

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Publishing Research Data Management