Data Archive Geo (DAG)

DAG Essentials

Data which is directly or indirectly related to a research project or program. DAG is intended for research data that is no longer active. 

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The archived data is read-only and suitable for data that you no longer (need to) change because you project is finished, or because the data has reached a final stage (e.g. raw, cleaned or processed). 

If the data is still active, and you expect to make changes to it, then you can use Yoda for Geosciences, the faculty network drive or another approved storage location.

Related Links:
UU Geosciences Yoda
UU ICT Storage Finder Tool

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DAG is an internal archive for the faculty of Geosciences. It is intended to safeguard research data that cannot or may not be published as FAIR data in public repositories such as Pangaea or Yoda.

Related Links:
UU ICT Data Storage Finder Tool
UU Geosciences Repository Listing

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Although DAG and Yoda use the same infrastructure and make use of the same IRods technology, there are some fundamental differences. DAG is an internal data archive, which is only accessible by member of the faculty of Geosciences, while Yoda is an institutional repository, which is accessible by users from Utrecht University and beyond. DAG is focused on preserving data on the long-term which can be considered as static. Besides preserving data on the long-term in the vault, in Yoda data can also been stored in the workspace for sharing and collaboration purposes. In addition data in the vault of Yoda can be made publicly available, so a DOI can be assigned and data is online retrievable by means of the registered metadata. Also the data in DAG is retrievable, but only within DAG itself. By the way: it is possible to make data from DAG publicly available by using a publication workflow.

Related Links:
What is Yoda?

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The data in DAG are only findable and accessible for researchers of the faculty and this makes the data less FAIR than data that is in most public repositories.

However, there is a lot of data in the faculty that remains on external disks or isolated network folders, in many cases because the data is not suitable or allowed to be published, even with restricted access.

DAG provides a solution for these data, to ensure that these data remain available. By providing metadata, access controls and guidance we maximize the findability, accessibility, interoperability and reusability of the data.

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These guidelines are created in cooperation with researchers and supporters from different divisions of the faculty 

  • Data Manager and Stewards: Vincent Brunst, Garrett Speed, Ilja Kocken 
  • Pilot Group sensitive data
  • Pilot Group lab data
  • Pilot Group big data
  • Yoda Team: Maarten Hoogerwerf, Erik Hakvoort, Monic Hodes

We welcome any feedback, suggestions, etc. Users can give feedback on questions and pages using the feedback link on each page. 

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Yes, you may archive data with which is sensitive. However, you should restrict access to your data via the metadata. 

If your data contains personal data, then you must indicate that in the metadata, so that we can manage it in compliance with GDPR. 

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Personal data means data that can be related to an identified or identifiable natural person. This data needs to comply with the regulations of the GDPR / AVG. Otherwise sensitive data is data that has been labelled as sensitive for ethical, commercial, or valorization reasons and should be treated as such. Please consult your data steward or the faculty privacy officer if you are unsure if your data may be considered personal data. 

Related Links:
UU RDM Handling Personal Data

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The DAG is built upon the Yoda platform, which complies with Utrecht University’s Information Security policy for data classified as public, internal use or sensitive.  

As a depositor you can control restrict data access to either the whole faculty, or to yourself (and data managers).  

Access restrictions are set in the metadata through the personal data field and the data sensitivity field. Note that metadata can be searched by the whole faculty.  

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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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Primary responsibility for complying with these guidelines lies with the researcher who is also responsible for the generation of the research data. This also applies for PhD candidates and postdoctoral researchers. For research master’s students, their promotor or daily supervisor is responsible. 

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Data creators and data owners have the primary responsibility to deposit data., because they have insight knowledge about the content of the data and how it is originated,. They should write the data documentation, decide in what structure the data should be recorded and create the metadata.    

Data managers, data stewards, data custodians and/or administrative/support staff are not responsible for depositing data, but they are available to help. They do not have a full understanding of the structure and content of the data, so they should focus on supporting the data depositor, so he / she can deliver high-quality data, metadata and data documentation to DAG.   

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Selecting data means making choices about what to keep for the long term, and what data to archive securely. This means that you have to decide whether your dataset contains data that needs to be deleted or separated. Reasons to exclude data from publishing include (but are not limited to):   

  • The data is redundant   
  • Data concern temporary byproducts, which are irrelevant for future use   
  • Data is sensitive for privacy reasons in regard to the GDPR/AVG: like consent forms, voice recordings, transcripts, DNA data, or any other data the contains information on specific people.  
  • Data containing state secrets  
  • Data sensitive to competition in a commercial sense, preserving data for the long term is in breach of contractual arrangements with your consortium partners or other parties involved 

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Not all research data can be included in DAG. This has to do with the fact that the faculty (owner of DAG) takes over the responsibility for making the data available from the data owner. The data owner still has the rights and the responsibility to determine what happens to the data stored in DAG. Data of which the UU (faculty or data owner) does not have the ownership or intellectual property rights cannot be included in DAG. This could also apply to data to which third parties, such as funder, publisher, data supplier or consortium partner have (shared) claims or rights. In that case it must be agreed with the relevant party whether the data can be included in DAG. In addition, commercial considerations or valorisation purposes could be reasons not to include data in DAG. If these reasons apply, find out first before data are deposited. 

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There are costs for archiving your data the most important being the cost of the data storage. 

The storage costs are currently covered by the faculty and will not be charged to the individual researcher or research group.   

The storage usage will be monitored, and when inefficent usage is detected, we will contact the data depositor and data owners to discuss how the usage of DAG can be optimized. 

Related Links:
UU Guide – Cost of Data Management

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