To make your data, software and code deposits more discoverable you can enter metadata about them into Symplectic. This then feeds through into Spiral, the Imperial College institutional repository. Spiral is indexed by various search engines, including Google Scholar, and will improve the visibility of your work which will in turn make it more citable.

To do this access your Symplectic account and add information about your data, software or code.

Principle Investigators are required to inform the College of the location of published datasets and software via Symplectic in order to meet funder requirements, ensure that valuable assets are not lost, and to help make research outputs more visible.

Videos on how to deposit information about your dataset, software or code in Symplectic are available below:

How to deposit information about your dataset in Symplectic:

How to deposit information about your software/code in Symplectic:

How to cite data

Citing and measuring the impact of datasets is increasingly important for the scientific research community. If you use, adapt or reference someone else’s dataset it is important that you acknowledge this, and you may wish to cite your own deposited datasets in research papers and publications.

Information on how to correctly cite a dataset can be found on the DataCite website, following the principles outlined by Force11 in 2014.

The recommended format for data citation usually comprises the following components:

Creator (PublicationYear). Title. Publisher. Identifier

If applicable, information about two other properties, Version and ResourceType, should also be included

Creator (PublicationYear). Title. Version. Publisher. ResourceType. Identifier

Example:

Cridford, T., Peters, W. (2018). Test Data Collection. Version 1. Imperial College London Data Repository. Dataset. 10.4469/hpc/4817. 

 

Further reading:

Australian National Data Service: Data Citation

UK Data Service: Cite the data