Cooperative research projects with several partners are increasingly characterised by a transnational as well as interdisciplinary character. This brings about additional challenges in the management of research data, which can be addressed through coordinated data management planning and collaborative working practices. The implementation of data management should therefore be planned jointly. Moreover, agreed procedures and responsibilities should be recorded in a project policy and a data management plan.

Challenges in managing research data in collaborative work include, for example, the joint organisation and processing of data and documents under what may be different methodological or disciplinary requirements. Setting standards for folder structures, file naming, metadata, file formats and even entire workflows is also essential. The provision of shared storage as well as access to and transfer of research data between different research institutions, taking data security and data protection into account, are further challenges.

There is a broad field of special tools for joint, location-independent academic work with data, which enable sustainable and reproducible research in the sense of the rules of good research practice, especially through the documentation of research processes and data processing.

For collaborative work with research data, centrally coordinated planning of research data management and all workflows is even more important than for individual research due to the large number of participants and institutions involved. From the very beginning, the basic responsibilities and the handling of the data generated in the research project should be defined in a project policy - independent of any existing institutional or disciplinary policies.

The specific measures should be defined in a data management plan (DMP), which is ideally oriented towards the data life cycle. In addition to statements on the handling of research data throughout the project duration, this plan contains information on the specific requirements of the funding organisation, statements on copyright and intellectual property rights of the research data, confidentiality agreements as well as guidelines on how to handle the data at the end of the project, such as data publication or destruction. The data management plan is important for making data interpretable and reusable for third parties and is therefore now expected by many third-party funding organisations (DFG, EU Horizon 2020, Volkswagen Foundation) for the allocation of funds from certain funding lines as part of a funding application.

Collaborative work requires the joint editing of and access to files. This can save a lot of time and all participants have access to the latest file versions available. When working collaboratively on data the following requirements exist:

• Storage and sharing of documents and data files,
• The ability to organize documents and files into folders,
• An access control system that easily manages authentication and authorization,
• Version control of documents and data files,
• The ability to annotate metadata or define metadata templates, if applicable.
• Prevent file locking so that users can work on the same file simultaneously
• Safeguarding of data protection laws

For collaborative work, the joint editing of documents and files is an indispensable necessity. There are numerous tools and utilities for this purpose, such as:

• Google-Docs
• Onlyoffice
• Microsoft SharePoint
• Overleaf
• ShareLaTeX
• HedgeDoc
• KMcloud 

Are you missing an important tool? Feel free to contact us and contribute your experience and knowledge in handling research data.