Data Archive Geo (DAG)

During Depositing

After the preparations you are ready to deposit your data in a few simple steps: 

 You can start a new deposit using DAG. A deposit will be saved until it is finished or deleted. You can start a new deposit while another deposit is pending. Pending deposits can be resumed. 

 For setting up a data package, separate data files or data files containing folders can be uploaded in a deposit session using the browser, via the file explorer  or command line

 Metadata is descriptive information about data and contains descriptors that facilitate cataloguing data and data discovery. Metadata help to explain the purpose, origin, time, location, creator(s) and access conditions of research data, which enables a broad scientific community to find, share and understand the content and context of a dataset.

Once all the data is uploaded, and the metadata are specified, you can verify your deposit and submit it. The data and metadata will be packaged and stored in the archive and you will get a notification containing a persistent reference to the data. Depending on the amount of data, this may take some time.


Your data, once it is submitted and stored in the archive, can be found by all members of the faculty, after logging in to DAG. The metadata is not shared with other systems, so it cannot be found outside DAG. If you do need your data to be findable, you should consider publishing it in a public repository such as Yoda or Pangea, you can find public repositories on the UU Repository Finder tool, or you can contact your data steward for help.

Related Links:
UU Repository Decision Tool

Contact Information:
UU Geosciences Data Team (Data Stewards, Data Manager, Privacy Officer)

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In principle there is no maximum size to the files or dataset that you need to archive. However, there are some things that you need to consider: 

  • Is it worth archiving the specific (large amount of data)? 
  • How are you going to transfer the data efficiently?  
  • Does DAG have enough capacity to store the data? 

You should have no trouble archiving data up to a few GB with file explorer, or up to 100s of GBs if you use iCommands. If you plan to upload over 1 TB of data, you need to contact the DAG management so that we can reserve sufficient storage capacity and for the team to help with optimizing the data package. 

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Within DAG the following roles will be distinguished:  


  • Data Owner – The principal researcher of the project or research group leader. The owner is recorded in the metadata, and responsible for establishing access controls to the data.  
  • Data Depositor – The person who uploads and documents the data in DAG. Ideally this is the person that knows the context and processes for creating and using the data (the data creator), on behalf of the data owner. The depositor is recorded in the metadata, and will also be used as the primary contact for questions about the data.  
  • Data Manager – The person(s) that curate the data, monitor access controls and support in fulfilling data access requests and possesses deeper technical knowledge about the backend of DAG.  
  • Data Consumer – this is a faculty staff member who is interested in reusing research data from DAG. The data consumer can search the data and (request) access. The data consumer should respect any conditions specified by the data owner. 

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The general parameters of the project should be documented in discrete files. For instance, the following information / files is required to interpret and understand a study by a researcher who is not part of the research team:    

  • Proposal   
  • The data collection / generation methods to contextualize the space and time of the study   
  • Final Data Collection Tools     
  • Analytical and procedural information (such as fieldnotes, observations, codebook development)    
  • Codebook explaining variable definitions, units of measurement, names and schemas  
  • Permissions or licenses from copyright holders from partner organizations (if any)   
  • Any assumptions made during analysis  

When the data collection methods and objectives etc. are included in the project proposal or accompanied publications, there is no need to add them in the data documentation.   

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Open: Data is to be accessible to all faculty members, free to use/download and modify. Data has been de-identified and has an appropriate license.    

  • Open for analysis   
  • Open for reuse   
  • Open for redistribution   
  • Open to adapt   
  • Open for redistribution of adapted version   
  • Open with obligation to cite   
  • Open except for commercial purposes   

Restricted: Data is not directly accessible to all faculty members. Stored data should only be accessible to approved researchers only. Access can be given upon request by the data owner/ custodian. Metadata is  findable by all faculty members.    

  • Available upon request   
  • Conditionally available   

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