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TAM DataHub Repository (DSpace)

For data and code publication with persistent identifiers (DOI), we have established the TAM DataHub Repository, based on the modern and widely used DSpace software. This research data repository further simplifies early sharing of data and code and is tailored to the needs of researchers in the field of psychology and neuroscience.

Our TAM DataHub Repository will fill the gap between our institutional repositories like data_UMR, JLUdata and TUdatalib, general research repositories like OSF or Zenodo, and discipline-specific repositories such as OpenNeuro or ZPID.

DSpace's Features

This article outlines the purpose, features and status of the TAM-DataHub Repository. Instructions for usage are part of the workflow section of this manual.

The TAM DataHub Repository has following core features implemented:

  • Access the repository publicly via: tam-datahub.online.uni-marburg.de
  • Search the repository for relevant information via full-text search.
  • Authenticate with your Uni Marburg account via Shibboleth to deposit publications.

  • Upload one or multiple files or archives via web-browser and control access with submission- and file-based options (open access, restricted access, embargo, ...).

  • Operation in the secured HPC infrastructure of MaSC and MaRC enables storing data with normal and elevated sensitivity requirements (not during pilot (test) phase, see below).

  • Submissions up to several hundred gigabytes (and above upon request) can be accepted.

  • Daily backups of all data and of the whole platform ensure availability of your archived and published research.

  • Use field-specific metadata schemata to describe your text- and dataset-publications. The schemata largely base on established schemata like Dublin Core for long-term interoperability. Specific item types (e.g. Text Publications, Datasets, Persons, Projects, etc.) are available, each with corresponding metadata. The modular submission process has some basic, mandatory metadata and extensive, optional metadata to provide the level of detail that fits your needs (see figure).

  • Define relations to connect related publications, data and code, archived documents and responsible persons, projects and organizations.
  • Use pre-selected values and controlled vocabularies to enable consistent and meaningful annotation.
  • Get feedback from the DataHub Data Stewards who act as curators and can help you to optimize annotation of your publication.
  • Obtain persistent identifiers (DOI) for your publications which also makes them findable via DataCite Metadata.

Figure: Submitting a Dataset in the TAM DataHub Repository Figure: Submitting a Dataset in the TAM DataHub Repository.

Further features will be added continuously, some of which are listed below:

  • Training resources
  • User interface customization
  • GitLab to DSpace publication pipeline
  • Integration with external data sources

Currently, users need to be authorized manually to publish at TAM DataHub. This should usually not take longer than two days. If you have logged in first time and are still not able to create submission within this time, please contact us.

TAM Acknowledgement and Publications List

We kindly ask all researchers affiliated with TAM and all collaborating researchers who use our DataHub services to add the following acknowledgement to their publications:

This work was supported by the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG) under Germany’s Excellence Strategy (EXC 3066/1 “The Adaptive Mind”, Project No. 533717223).

Please also remember to add your publication to the internal publication list or contact the TAM Research Coordinator Li-Ching Chuang to ask for your publication to be added.