NTNU Open Data - Kunnskapsbasen
NTNU Open Data
On this page you can find information about how you can archive your data set in NTNU's institutional repository in DataverseNO.
Topic page about research data | Pages labeled with Open Data
Norsk versjon - NTNU Open Data
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About DataverseNO - NTNU
The NTNU collection in DataverseNO is a manually curated institutional repository for open data from all fields and disciplines. DataverseNO is operated by UiT The Arctic University. NTNU adheres to the guidelines and policy of DataverseNO, including review of data sets by a curator prior to publishing. DataverseNO is a Core Trust Certified repository and assigns DOIs (Digital Object Identifiers) to data sets. The standard license is CC0 (Creative Commons Zero), but other open licenses can be considered if needed.
How to archive in DataverseNO
Log in to the NTNU collection with FEIDE (your NTNU user). We recommend that you use the DataverseNO deposit guidelines for archiving. The guidelines are comprehensive, and not all part are relevant for all types of data. Therefore we will list the most important aspects, including some which are often overlooked. Feel free to have a look at published data sets in DataverseNO to get good examples of how to describe and organize your data according to DataverseNO's guidelines.
Note that there are limited options for changing file structure and data once the dataset is uploaded. You should therefore finalize your dataset according to the guidelines before uploading.
A single dataset cannot contain more than 300 files. If you need to deposit more files, you may opt for one of these alternatives:
- Pack the files into one or more (max. 300) container files.
- Distribute your data files across multiple (sub-)datasets.
If your files are organized in folders (and sub-folders) and you want to keep the folder structure in your dataset, click the Upload a Folder button. After that, click on Select a Directory and select the folder which contains the folders and files you want to upload. Note that the top level in the selected folder will not be uploaded/reflected in the dataset, only the content in the folder.
Files:
- All data sets should be accompanied by a ReadMe file. This file should be in plain text format (.txt) and include the prefix 00 to ensure that it appears on the top of the file overview. See deposit guidelines for more information about the ReadMe.
- Some file formats are better suited for long term archiving. If your files not are in any of the preferred formats, we recommend to converting to one of these. The original file format can be uploaded in addition.
- The size of individual files should not exceed 100 GB. Larger files can create problems for others when it comes to downloading and reusing data.
- A file upload should not exceed 200 GB in total size.
Metadata:
- Note that all names should be in the format Family name, Given name.
- Be generous with keywords, and add them separately using the +-button.
- The description should provide a general overview over the content and context of the data set.
- Some metadata fields are mandatory, other are optional. The deposit guidelines has in-depth information about the metadata fields.
- After saving the draft, you can add additional metadata with the "Add + Edit Metadata" button. Se the deposit guidelines for recommended metadata.
Data about persons
Data sets that contain directly or indirectly identifying personal data cannot be published in DataverseNO, cf. DataverseNO Deposit Agreement. However, anonymized data sets can in many cases be published. To ensure that this is done in a legal and ethical manner, everyone uploading data sets based on information about or from individuals must complete a brief online form. Here you must assess whether the data set is anonymous, describe whether the data was anonymized as well as what information the participants were given. More detailed information on pre-publication assessment is available in the example template for ethical and legal review. The wiki on processing personal data in research may also be useful.
In addition, you are encouraged to include relevant documentation as part of the data set. This may include the information letter and consent form, questionnaires and interview guides (if applicable), as well as the ethical/legal assessment based on the answers in the online form referred to above.
Review and curation of datasets
When you are satisfied with your data set, send it for review. A curator at the University Library will look through it and either publish or return it for adjustments. If you need to give others access before publication (for example journal editors, reviewers or collaborators), contact Research Data @NTNU.
See also
Contact
- Research Data @NTNU - if you have questions about open data, or if you have suggestions for changes to the web page.