The data are to be archived and stored in such a way that they can be easily retrieved or used locally using standard communication protocols both by machine and by hand (Source).

https or ftp seem to be the methods of choice. There are problems with confidential or otherwise sensitive data.


A datatype is a schematic description of a data structure. It is organized hierarchically in an arbitrary granularity and can be used for the identification as well as for the structural description of resources. In order to ensure machine readability, datatypes are stored in a Datatype Registry.


According to FAIR principles, data should be "Findable, Accessible, Interoperable, and Re-usable".


Data should be easy to find both by humans and by computer systems. (Source).

Requirements are meaningful metadata, IDs and open access (not necessarily part of the definition).


The data should be able to be exchanged, interpreted and at least semi-automatically combined with other data sets (Source).

The prerequisite for this is a common format or a kind of crosscompiler between different formats (this is not part of the definition, but it seems to be important).


Metadata or metainformation is structured data that contains information about characteristics of other data.


Conceptual system consisting of the concepts of a knowledge domain and their relations among each other (after LIU, LING and M. TAMER ÖZSU (editor): Ontology, Encyclopedia of Database Systems. Springer publishing house, 2009)

PID Information Profile

A PID Information Profile is a special datatype describing the structure of a PID Record. It defines mandatory and optional elements, which have to be part of a PID Record in order to correspond to a certain profile. This allows automated validation of PID Records and their indexing for depth search based on PIDs.

PID Record

PID Records are the sum of all key-value-pairs associated with a PID. In the context of FAIR Digital Objects PID Records are used for fast decision making as they contain basic metadata about the referenced content. Elements of a PID Record are defined by a PID Information Profile and allow the validation of a given PID Record.

Persistent Identifier

Persistent Identifiers (PID) are globally unique strings for identifying resources. They are managed and resolved by a distributed infrastructure. Depending on the PID system, single PIDs can be associated with additional key-value metadata which is accessible via the PID record.


Provenance generally refers to the origin of a person or object. In the research context, the term is used to denote the origin and history of data. The recording of provenance makes it possible to trace where data comes from and who changed it, when and how. The Prov-Standard is used for recording.

The term has its origins as a designation of the origin of works of art and cultural assets, and provenance research is dedicated to their research. This is also transferred to data. At DLR, the PROV@DLR group is working on this topic. The department Intelligent and Distributed Systems (IVS) of the Institute for Software Technology (SC) is also engaged in the provenance recording of software as well as software development processes.

Provenance is applied in many areas of DLR; especially in the areas of Digital Gemini and Simulation-based Certification, provenance plays a role.

Research data

Research data are all data generated in the course of a scientific project, e.g. through source research, experiments, measurements, surveys or questionnaires (Source / download).


The data is reusable for future research and comparable with other data sources. Citability and terms of use also fall under this keyword (Source).

This implies, among other things, intensive use and provision of metadata such as test environment, version documentation, etc.

Web Ontology Language

The Web Ontology Language (OWL) is an ontology language for the Semantic Web with formally defined interpretation. It is a specification of the World Wide Web Consortium (W3C). (after OWL 2 primer )

data management plan (DMP)

A data management plan (DMP) is an important tool to structure the handling of your own research data. DMPs can be used as checklists as well as for ongoing documentation: from the collection of data to long-term storage or publication. More and more research funding agencies, e.g. the EU or the BMBF, are demanding the creation of a DMP.