Archiving Solutions: Arkivum

Arkivum

Digital archiving involves various activities to ensure that digital content remains accessible and understandable over time. Arkivum provides Oxford Brookes University's digital research archiving solution. Arkivum is a suitable option for:

  • Personal or sensitive data
  • Data that needs to be retained for ethical, legal, or regulatory reasons
  • Data that supports projects and needs to be retained
  • Data that is required to be securely archived in a grant, collaboration, or data agreement.

Contact us

Research Data Manager

Nina Lewin

nlewin@brookes.ac.uk

Non-standard Software

When non-standard software is used, assistance may be needed to choose an alternative format for preservation and convert the data to the required format.

Depositing to Arkivum

Arkivum offers a complete cloud-based solution. To access this secure service, please follow the steps below.

Routes for you to consider

Access to Arkivum is via two routes depending on the amount of data to be deposited. 


Route A: Small volume of data to archive - total volume less than 500GB

Data pools representing different research areas have been created to accommodate small data volumes and simplify the process for research students. The Research Data Manager will manage these data pools and deposit data for the researcher(s).

This archiving option is perfect for researchers or research students who have interview transcripts, surveys, focus group data, or small experiment data totaling less than 500GB. It is also helpful for researchers who need to deposit a subset of data to fulfil a data availability requirement for a journal when submitting articles. Follow the steps below:

Route B: Large volumes of data to archive - Above 500GB

For large volumes of data, a data pool will be created specifically for your data, and access will be provided to allow you to ingest the data directly once it is ready. You will manage the data pool assigned to you.


This route is ideally suited to researchers and research students whose data underpins a significant number of outputs/projects.

It is also helpful for researchers dealing with big data. Follow the steps below: