Research Data Management

FAIR principles:

The FAIR principles serve as a framework for enhancing the findability, accessibility, interoperability, and reusability of digital resources. In light of the exponential growth in the volume, complexity, and velocity of data generation, the objective here is to ensure that the data can be located and retrieved by machines.

Metadata:

Metadata is data that contains structured information about the research data or resources and their characteristics. In order to enhance the efficacy of metadata, domain-specific standards have been developed over time that facilitate the linking and processing of metadata from disparate sources.

Provenance:

Provenance generally refers to any information that describes the?production process of an end product, which can be anything from a piece of data to a physical object.?While data provenance allows to track the?processing of individual data items?at the level of individual data items (and the operations they undergo), workflow provenance facilitates an understanding of the data flow and dependencies between different process steps.

Research Data:

The DFG defines research data as an essential foundation for scientific work. [...] Research data might include?measurement data,?laboratory values,?audiovisual information,?texts,?survey data,?objects from collections, or?samples?that were created, developed or evaluated during scientific work.

Research Data Management:

Research data management is the process of transforming, selecting, and storing research data with the goal of keeping it accessible, reusable, and verifiable in the long term, independent of the data producer.?

eLabFTW:

eLabFTW?a free and open source electronic lab notebook hosted by the University of Regensburg.

NFDI:

A protagonist in the field of research data management is the National Research Data Infrastructure (NFDI), which has set itself the task of indexing, networking and making research data in German-speaking countries permanently available. The goal is to make data available centrally and in the long term according to the FAIR principles (Findable, Accessible, Interoperable and Reusable). Various standards and initiatives already exist in this area - national NFDI consortia (consortia of various institutions within a research field) and international initiatives such as the European Open Science Cloud (EOSC) - which are to be compiled and classified in the written work.?

In her bachelor thesis, Natalie Franz conducted an interview study with representatives of various NFDI consortia. The aim was to analyze the existing identification and classification of different research data management projects and to filter out standards, procedures and methods in research data management in the different disciplines. The results of her work are summarized on the following website.

UR DATA HUB:

The UR Data Hub is a central facility of the University of Regensburg and supports you in all matters of research data management. Our services include consulting during the planning, implementation and completion phases of your project as well as the provision of digital services.