The research data lifecycle


Planning data management is the first step in a research project and is done before data collection. From the very beginning, researchers should consider the entire life cycle of research data, ranging from data collection to archiving, publication and reuse. Comprehensive and early planning has many advantages. The anticipatory design and organisation of RDM measures helps to better cope with challenges (e.g. through planning of resources for data processing or storage, or the correct implementation of legal provisions, or the ethical framework for data collection and data publication). Data management plans (DMP) are a useful tool in this regard. They are also a mandatory requirement of many funding bodies. The University of Vienna supports its researchers in the planning phase through training courses for preparing DMPs. Moreover, it offers individual advice on how to prepare these plans.

Data collection

Research data are generated using different methods, depending on the research question and discipline, e.g. from sources, experiments, measurements, descriptions or surveys. Depending on the type of data collection and data type, there are different challenges, such as guaranteeing the legitimacy of data collection or the compliance of data collection with ethical principles. If necessary (ethics vote is required by publication organ or research funding body), an application can be made to the Ethics Committee.

The collection of personal data is subject to data protection provisions which also influence the opportunities for further data processing, including data storage, sharing, archiving or publication and licensing for reuse. If you have any questions regarding data protection, you may contact the data protection officer of the University of Vienna.

Already during data collection, technical questions should be addressed. For example, the selection of a data format suitable for long-term accessibility.


RDM measures in the phase of preparation and analysis aim at, among others, temporary data storage and sharing data among a defined group (e.g. the project group). For storing and sharing data among a project group during a research project, researchers can use services offered by the Vienna University Computer Center (ZID), such as online storage space, a university-wide Wiki, an ACOnet file sender, shares, a cloud storage or a temp space to share large amounts of data for a short period of time.


Archiving of research data allows to save them and to prevent data loss. Archiving usually takes place by delivering research data and accompanying documentation to a repository for the purpose of temporary or long-term storage of research data. This includes preparatory activities prior to archiving, such as data preparation to improve reuse, measures to make data (provision) FAIR, complementing data with metadata and research documentation as well as access permissions and terms of use. With the institutional repository PHAIDRA and the Austrian Social Science Data Archive AUSSDA, the University of Vienna provides an infrastructure for this purpose. It also gives comprehensive advice about data archiving to researchers.


Publication aims at making research data visible and accessible. It has many advantages: The research process becomes more transparent and the results reproducible. Other researchers can reuse these data in their own research. This may lead to more efficient and faster results and new findings. Additionally, data publication can increase the visibility or impact of the research and the researchers themselves. Data should be published in a suitable repository. This repository should meet the most important publication criteria (e.g. the licensing or access requirement for data as well as better findability of data). In the institutional repository PHAIDRA, different licenses and access requirements can be selected individually, as needed. Persistent identifiers are generated automatically. In the discipline-specific repository AUSSDA for the social sciences, the license and the access requirements are defined jointly with the employees depending on the data type. In any case, the allocation of a persistent identifier (e.g. DOI) is important during research data publication. To obtain a DOI, the University of Vienna offers different opportunities.


The reuse of data can be addressed in the beginning or at the end of the research data cycle. RDM measures, such as the assignment of a rather open licence or the comprehensive description of data, aim at making data FAIR and allow for reuse in different areas. To enable this, the potential reuse of data should be considered in all stages of research data management. International initiatives, such as the European Open Science Cloud (EOSC), enhance the further development and linkage of research infrastructures to allow for the reuse of research data. The University of Vienna therefore fully participates in European and national projects addressing the EOSC and the FAIR principles.