Any scientist can upload data to be archived by us. This can be raw data, edited data or specific data that are underlying a publication. An overview of the criteria and practices for collection development can be found in our Data Collection Policy. For data that is still being worked on, 4TU.ResearchData recommends setting up a data lab.
Before uploading in 4TU.ResearchData, please read the deposit guidelines for more details and practical information on our upload procedure.
We strongly recommend you to submit a README file along with your dataset. A README file should describe what data is included in your dataset and ensure that future users of your
data will be able to easily understand your data files. If you are not sure where to start, read the Guidelines for creating a README file.
Check the Data Collection Policy if you are unsure whether your dataset will be accepted for inclusion in the archive.
Researchers may upload the data (up to approx. 10 GB) themselves, using the upload form. Registration and login can be accomplished through an institutional account or through an OpenID (e.g. a Google account).
Once you have logged in, a personal page will be created for you. You will be asked to consent to the Licence Agreement.
When you upload a data set, it is checked before inclusion. This is to ensure that no errors have been made. Within three days, your dataset will appear in the 4TU.ResearchData archive.
Datasets that are larger or consist of different parts that need to be linked are uploaded together with a 4TU.ResearchData employee. For the transfer of large datasets, you can use our FTP server, SURFdrive (only for Dutch higher education institutions) or an external hard drive.
You may contact us if you need help.
Every researcher can upload up to 10 GB of data per year to the 4TU.ResearchData-archive free of charge. By default, this data will be available via Open Access and be stored for a minimum of 15 years. Your data will be stored in three different locations to ensure its safety.
- Are you a researcher at Eindhoven University of Technology, the University of Twente or TU Delft and do you have research data from ongoing or completed research?
The costs for depositing up to 1 TB of your research data will be reimbursed by your university. For depositing larger data collections, a discount of 20% on the total storage price will be applied.
- Are you a researcher at another research institution and do you have research data from ongoing or completed research?
You can deposit up to 10 GB of data free of charge. For depositing larger data collections, we recommend to consult the research data management service desk of your own institution.
Descriptive metadata are indispensable for the preservation, retrieval and re-use of datasets. They provide answers to questions concerning the person creating the data, the subject of the data, the type of file, geographic information and other aspects. In other words, metadata are ‘data about data’.
Metadata make use of international standards for data exchange. This ensures that the information and the associated dataset can be found by search engines.
Substantive metadata are important primarily for the user of the data. For example, consider a codebook that tells how the data should be read or interpreted. In many cases, such information is added in the form of readme files or similar descriptions.
When uploading, you will be asked to enter the following descriptive metadata:
Main researchers involved in producing the data.
Name or title by which the dataset is known.
Institution where the data was created or collected. A person or organization responsible for making contributions to the dataset.
A holder of the data (including archives appropriate) or institution which submitted the work. Any others may be listed as contributors.
The year when the data was or will be made publicly available.
Date the resource itself was put together; this could be a date range or a single date.
Concise description of the contents of the dataset. Describe the research objective, type of research, method of data collection and type of data.
Subject, keyword, or key phrase describing the resource.
Indicate the dates to which the data refer. Enter the year, or beginning and ending
Describe the geographic area to which the data refer (e.g. municipality, town/city, region, country). The geographic coordinates of the area may be included, if desired.
4TU.ResearchData automatically assigns a DOI to a dataset once the entire deposit
The primary language of the resource. When no language is added, 4TU.ResearchData will automatically assign ‘English’.
Link to publication
Include the web addresses or DOIs for any publication, important internal reports or other datasets that are related to your dataset.
Terms and conditions on how the dataset may be used. Our recommended licence is CC0 as it makes your data maximally reusable. When no licence is selected, 4TU.ResearchData will automatically apply CC0 to your dataset.
|Funder||Name of the organization that provides financial support for your research.|
* is een verplicht veld
Auxiliary information necessary to interpret the data, such as explanations of codes, abbreviations, or algorithms used, should be included as accompanying documentation.
Read more in the Deposit guidelines and Guidelines for creating a README file.
Previous studies have indicated that publications containing links to the underlying data are cited more frequently than are publications without such links. By storing your research data in 4TU.Centre for Research Data archive, you can encourage the reuse of your data for new research or verification.
Digital Object Identifiers (DOIs) are used to create a permanent, stable link to the dataset. Even if the location of the dataset changes, the cited dataset can always be retrieved.
Every dataset in the archive of 4TU.ResearchData is provided with a DOI (through DataCite Netherlands). 4TU.ResearchData archives the data in a permanent and sustainable manner, fully according to the guidelines of the international Data Seal of Approval.
More than one DOI
DOIs can be assigned at every level of detail or size within a publication. For example, a DOI can be assigned to an entire data collection, as well as to each component within the data collection. In the choice of which levels should be registered with a DOI, researchers should proceed from the expectations of future data users. Is it likely that the objects within the data collection will be cited?
Link between publication and dataset
To promote the visibility and the sharing of your datasets, we recommend referring to the DOIs of your datasets in your articles or PhD thesis. You can even reserve a DOI in advance.
The choice of file format is of essential importance in order to ensure that the research data will remain usable and ‘legible’ in the future. 4TU.ResearchData therefore strongly encourages the use of standard, exchangeable or open file formats. For the preferred formats, 4TU.ResearchData guarantees that the research data will remain accessible and that they will be migrated or converted if necessary.
4TU.ResearchData provides two levels of support for file formats:Full preservation:
- All reasonable measures will be taken to ensure that the file formats remain legible and usable. These measures include migration, normalisation and conversion.
- Bit-level preservation: Access to the data object will be offered in the file format that was originally provided.
NetCDF and OPeNDAP
Most of the datasets in the 4TU.ResearchData archive are coded in netCDF (Network Common Data Form), which is both a data model and a data format which is very efficient for multi-dimensional array-oriented data. This data can be temperature, humidity, pressure, wind speed and direction in both vector and raster format. Although generic, netCDF is mostly and widely used in atmospheric sciences and oceanography.
The format is self-describing, i.e. it includes general metadata as well as detailed metadata about variables, dimensions and units used, in a fully machine-readable way (as opposed to, say, a spreadsheet with column headings which is not really machine-readable).
Access to netCDF data (and HDF5) is further enhanced by serving the data via the OPeNDAP protocol. OPeNDAP stands for Open-source Project for a Network Data Access Protocol. A major advantage using OPeNDAP is the ability to retrieve subsets of files without the need to download the whole dataset, and also the ability to aggregate series of data files, e.g. a time series, into one ‘virtual’ dataset. OPeNDAP makes it possible for datasets to be directly approachable through programming languages.
If NetCDF data are pasted together with OPeNDAP, it is easier to perform a ‘query’ that will return an accurately defined selection out of the data. It allows users to view a section of the data, thus saving a considerable amount of download time.
Our data experts will be happy to tell you more.
Additional information about netCDF is here available and about OPeNDAP at https:www.opendap.org. 4TU.ResearchData has published a report on its use of NetCDF. Our OPeNDAP server can be reached at https://opendap.tudelft.nl/.
As a data producer, you will be asked to consent to a deposit license. By doing so, you grant 4TU.ResearchData a non-exclusive licence to store the data and make them available to third parties.
When depositing your data you are required to select a licence for your data as part of the deposit process. A licence will define what others may or may not do with your data.
Read our guidance for more information on the licence types we offer.