- SLUB Dresden
- Publishing Research Data
Publishing Research Data
As a researcher, you are facing the question of how to archive your research data such that they are findable as well as reusable - whether for purely internal purposes, for review, or even for sharing with other researchers.
In collaboration with our colleagues at the TU Dresden the Service Center Research Data (see box on the right for contact details) we provide support with regards to all questions in this context. The following aspects are particularly relevant:
In most cases, research funding agencies expect the project application to include information on the planned data management. This data management plan should also include initial statements with regards to data archiving and respective potential publication of the data.
Whether or not to make the archived data publicly available is mostly your own decision. Data archiving systems (so-called repositories) usually offer the possibility to choose between pure archiving and archiving+publication.
We observe that data publication is increasingly expected by research funding agencies. It is therefore helpful to familiarize yourself with the respective guidelines of the funding agency, the call or even the research discipline early on.
In order not to leave you on your own with regards to all of these aspects, we provide the following services at the Service Center Research Data:
Our experience from dozens of consultation mandates shows that relevant decisions should be made as early as possible:
- Which data is worth archiving? (And which not?)
- Who might have an interest in the data later on? (And for what?)
- Should (some of the) data be made publicly available?
To address these questions, it helps to be aware of your values and goals (as well as relevant guidelines, see 1.):
- Do we - or others - potentially want to be able to reuse existing data in a subsequent project?
- What does it take for us to act according the principles of good scientific practice and make our research verifiable? (cf. Research Integrity and Good Research Practice - Code of the DFG).
- Which advantages do we gain from adequate archiving and potential publication of the data? (e.g. reputation)?
- Which disadvantages could arise and how can we avoid them? (e.g. embargo periods, choice of a suitable license)
Ideally, you should deal with these questions at the beginning of the project and review the decisions again and again throughout the project (iterative process). As the project progresses, the decisions made need to be substantiated and implemented:
Preparation of the data includes selecting, cleaning, and documenting the data. In order to do so, you can follow the guidelines of research funding agencies (cf. 1.) and best practices. Since this topic is complex and conceptual and technical questions may arise, we provide support in the form of an individual consultation:
The following options are available for archiving your data as well as for the respective option to publish it:
Archives and repositories
- interdisciplinary data repository of the TU Dresden: OpARA (usable purely as an archive, but also for publication)
- interdisciplinary, supra-regional data repositories: e.g. Zenodo or Dryad
- subject-specific data repositories: an individual search through e.g. Re3Data, the HTW Repository Recommender or the DFG's RIsources portal is worthwhile.
In addition to storing your data as a data package in dedicated archives, you may also want to present your data in an easily accessible way or make it immediately reusable and expandable:
- e.g. for the public
- e.g. for Citizen Scientists, Crowd Sourcing
- e.g. for programmers, bloggers
Web-based databases are suitable for this purpose, for example on the basis of Linked Open Data (Wikidata, Wikibase) or in the form of subject-specific portals.
Finally, there is the question of how other researchers can learn about your data. This includes, for example, the following possibilities:
- Citation and linking to related articles (most data repositories will provide the ability to uniquely identify and link to your datasets using a DOI).
- Publication in a data journal, e.g. Data in Brief
- Linking in research information systems such as the FIS of the TU Dresden or other subject-specific portals
- Public outreach (social media, etc.)
We are happy to support you in this.