RDM Compas Knowledge Base

Generic Research Data Management

The Generic RDM includes all topics that are relevant for comprehensive, sustainable and forward-looking research data management in data curation field, regardless of the subject-specific characteristics of individual disciplines.

The articles are divided into two parts: direct information for data curation and guidance for consulting researchers.

Basics of Research Data Management

What is FAIR data? What is metadata? What is DMP?

Here you will find all the basic information on the research data management.

Create and receive

Data creation and data acquisition from data centers or repositories. The assignment of the approapriate metadata.

Appraise and select

Evaluation of the obtained data and its selection for long-term archiving and preservation.

Ingest (or dispose)

Data transfer to a data center, an archive, or a repository. Secure data disposal, in case the data have not been selected for long-term retention.

Preservation action

Data cleaning and validation for archiving, and metadata assignment for its reuse. Assurance of adequate data formats and data evaluation for the reusability purposes.

Store and secure

Ensuring secure data storage, in compliance with applicable policies and legal standards.

Access, use and reuse

Ensuring data access for users and subsequent users, as well as developing and using access checks and authentication procedures.


Creating new data (structures) from original data, converting data to another format, or creating a partial dataset in order to produce new results.

Data Type Specific Research Data Management

Taking into account all content that is relevant in the context of generic research data management, specific characteristics may still apply to different types of data generated in social, educational, behavioral and economic sciences. Here you will find relevant information and materials related to specific characteristics of comprehensive research data management (RDM) according to different data types.

In addition, we have compiled data type specific tools, services, networks and relevant NFDI consortia.

Qualitative Data

Survey Data

Corporate Data

Physiological Data

Health Data