Research Data
Where can I publish research data under the open access model?
Videos, tables and ZIP files up to a maximum of 60 MB in size can be published using the open access model in OPEN FAU. The corresponding publication must also be made available in OPEN FAU. For research data which must meet more strict requirements in terms of memory, documentation or compliance with research funding organisations’ requirements, we recommend ZENODO (http://zenodo.org/about).
What are the professional options for publishing research software?
- Using a software repository (see http://software.ac.uk/resources/guides/choosing-repository-your-software-project). GitHub is often used for this purpose. You can also connect DOIs to versions of your software on Github and Zenodo. This makes identification and citation easier.
- Publish in a software journal (see http://software.ac.uk/resources/guides/which-journals-should-i-publish-my-software)
- Small programs consisting of only a few lines of code can be added to your research data as a text file.
When should I refrain from publishing my research data?
There are legitimate reasons not to publish your data and grant the general public access to it:
- If you want to apply for a patent.
- In case your data contains confidential or personal information (for example, from questionnaires or interviews) that could not be anonymized, and/or you do not have written consent from your participants to publish this sensitive information.
- If your research is funded by a commercial sponsor who did not agree to publication.
Under which licence conditions can I publish my data?
Depending on where your data is stored (for example, in a repository or data journal) and your goals, different licensing models are available.
The most widely used models right now are Creative Commons and Open Data Commons.
For specific recommendations, please contact Petra Heermann, the library’s contact person for legal issues.
Does research data management mean that anyone can access my data without restrictions? If so, how can I ensure that my data is not analyzed before I want it to be?
You decide who has access to your data, and you can control this through licenses. Generally, you can publish your data with a delay, known as an embargo, or publish only the metadata.
Please keep in mind the specific conditions and policies of your funders and publishers.
How should research data or software be cited?
Citation styles vary by subject and publisher.
Ask your colleagues or publisher in advance or consult a guidebook on scientific research that deals with the conventions of your field.
The following is an example of how to cite data in a bibliography according to a recommendation by FORCE11:
Author(s) (Year of Publication): Title of Research Data. Data Repository or Archive. Version. Globally persistent Identificator (preferably a URL)
Software can be cited as follows:
Author(s) (Year of Publication): Title of Software (Version). [Form, e.g. Computer Software] Source as a URL and/or DOI (Date of last retrieval)
More information on this topic can be found here:
- The literature management program EndNote (version X5 and later) provides citation templates for research data and software.
- If you know the DOI of the data you want to cite, you can use CrossCite to convert it into a full reference with different quotation styles (http://software.ac.uk/so-exactly-what-software-did-you-use).
- https://ltl.lincoln.ac.nz/research/citing-data/
Why should I archive research data?
Proper archiving of research data guarantees that future research can benefit from it and ensures that your research can be reproduced by the scientific community.
Collecting research data is time-consuming and expensive in terms of money and labor. Therefore, archiving your data is often cheaper than collecting new data, especially since sometimes your previously collected data cannot be reproduced (for example, weather data).
Third-party research funders and scientific publishers recommend archiving your data to ensure good scientific standards. Sometimes archiving is even compulsory. There are also benefits for you.
Which data formats are best for archiving?
The best formats are open and non-proprietary. The RADAR project provides a comprehensive overview of the available options.
In the context of research data, what is the definition of “re-use”?
Re-using published research data means it can be cited and/or used for other scientific research, as long as it is within the bounds of the data’s chosen license.
What are metadata and metadata standards? What are their uses?
Metadata are structured data that provide additional information about a specific resource. This information may include a description of the resource’s contents, a technical description, the context of its creation, or its relations to other sources and works.
Due to the different requirements of various disciplines, different metadata standards have emerged (e.g., the “Ecological Metadata Language” and the “Gene Ontology” for biology). Metadata provide a standardized, machine-readable description that makes it possible to find, reference, and use research data later on.
What are persistent identifiers?
Persistent identifiers are names given to any type of publication (research results, data, software). These names are linked to the publication’s location within a table. If the publication location changes, only the reference in the table needs to be updated, while the identifier remains the same. This usually happens automatically, unbeknownst to the authors and users.
This makes literature research, quoting, and linking publications and their accompanying data possible in the long term. Examples of persistent identifiers include the Digital Object Identifier (DOI), the Uniform Resource Name (URN), ePIC, and Handle.
Further information can be found in Chapter 13.2 of the Nestor guidebook, “Eine kleine Enzyklopädie der digitalen Langzeitarchivierung.”