Table of contents
This is a guide on how to publicly share data through the Data Repository for the University of Minnesota (DRUM), including how to prepare data before submission. DRUM is a publicly available collection of digital research data generated by University of Minnesota researchers, students, and staff. Anyone can search and download the data housed in the repository, instantly or by request.
How to deposit datasets to DRUM
How to deposit datasets to DRUM
DRUM is a publicly available collection of digital research data generated by University of Minnesota researchers, students, and staff. DRUM can help you comply with federal requirements for data sharing, as it meets the US Office of Science and Technology Policy's Desirable Characteristics of Data Repositories for Federally Funded Research. Anyone can search and download the data housed in the repository, instantly or by request.
Please review the sections on this page to be sure your deposit meets DRUM's policies and requirements. Once you are ready to deposit your data, here are some resources to help you deposit your data in DRUM:
- Step by step deposit instructions page
- Step by step video tutorial [coming soon]
Before you deposit
- Ensure your data falls within DRUM's policies and the Digital Conservancy’s policies and that you understand the terms of use.
- If your data was collected from or about human participants, ensure your data meets the Human Participant Data Policy.
- Prepare your data by cleaning or processing in such a way that it is easily reusable by others. Transform files to non-proprietary formats if possible (e.g., transform .xlsx to .csv).
- Gather necessary documentation and related files, such as a Readme File.
- Determine the appropriate license for sharing your data or software. See Creative Commons license options below.
Checklist to prepare data deposit in DRUM
- Select files to be shared. Determine what files are needed to understand, use, or re-produce your results. Consider sharing analysis or data cleaning code, related procedural files, as well as any relevant documentation files.
- Clean the data. Follow any disciplinary standards (e.g., how to note missing data), ensure proper labeling (e.g., all variables have units of measurement and or definitions), remove extraneous information (e.g., internal notes to the research team).
- Transform files to non-proprietary formats. For preservation and interoperability, data files should be non proprietary if possible (e.g., transform .xlsx to .csv; transform .docx to .pdf or .txt).
- Prepare documentation to accompany your dataset. A Readme File, which offers project- and file-level metadata, or similar is required for all DRUM datasets. If you are submitting a codebook or data dictionary, that information does not need to be repeated in the Readme File. Other metadata to think about are the keywords that will help to make your data discoverable by others. You will include those in the digital system upon upload.
- Decide on data author order. Note that the authors of the dataset may differ from the authors of a manuscript.
- Choose a thumbnail image. The digital record requires a thumbnail image to represent your data. This should be an image that you own or one that is labeled for reuse. Upload a .png or .jpg format of that image with your other materials. If you don’t have one, your assigned curator will assist you in locating an appropriate image.
Sensitive data checklist
If your data has sensitive material related to the types below we have additional requirements for acceptance:
- Human data. If you are submitting data that was collected from or about human participants, 1) carefully review the data for de-identification and 2) upload a blank copy of the informed consent form, information sheet, or other participant agreement used. A curator will review it to make sure it meets our Human Participant Data Policy.
- Tribal data. If you are submitting data that was collected from, with, or about a Tribal agency, please provide documentation about who owns the data and evidence of permission to share in DRUM from the data owner. DRUM seeks to apply the CARE Principles of Collective Benefit, Authority to Control, Responsibility, and Ethics.
- Animal data. If you are submitting data that was collected from animals, include your IACUC approval statement in the Readme File.
- Protected plant or environmental data. If you are submitting data that was collected about protected plant species or is otherwise environmentally protected, include how you are masking their location in the Readme File.
Choose a Creative Commons or similar license
When you deposit your data, you will be asked to choose a Creative Commons license or similar (usually for software) that captures legal protections around how your shared files may be reused. To maximize openness and reusability, we recommend data are shared with the CC0 license.
- Learn about Creative Commons license options.
- Learn about software license options from UMN Technology Commercialization
Frequently asked questions
- Is there a cost associated with sharing data in DRUM? Sharing data in DRUM is free to UMN affiliates.
- Who can upload data to DRUM? Anyone affiliated with UMN who has an active UMN email address can deposit data to DRUM.
- What if my UMN email address is no longer active? For alumni submitting data collected at the UMN, a co-author with an active UMN email can deposit on your behalf. Please let us know upon deposit if you would like the contact email updated to a different address.
- What size can my files be? Currently, DRUM is able to accept datasets up to 50GB. DRUM recommends individual files be no more than 5 GB each.
- What is the difference between a persistent URL and a DOI? A persistent URL (handle) is the permanent link to the data. A DOI is minted and registered with DataCite, and the DOI resolves to the persistent URL in DRUM. The DOI increases the discoverability of the persistent URL, but either can be used in citations of a dataset.
- When do I get a DOI? A DOI is minted when curation is complete.
- What is curation? Curation is the organization and presentation of data and related materials. Data curators perform file checks, file format transformations, metadata augmentation, and final assessment of the data package.
- How long does curation take? The length of curation varies and often depends on the communication frequency between the curator and the submitter.
- Do I have to have an image? Yes, as it acts as the thumbnail for the dataset’s record. If you don’t have one that you can use, DRUM staff will help you find one.
- Can I restrict access to my dataset? No, DRUM is an open-access data repository. However, you can temporarily embargo individual files for up to two years. After that, the DRUM system automatically releases the embargo and the files are fully public. However, metadata in the digital record will be viewable even when files are embargoed.
- Can I add files to my existing dataset? When you deposit data to DRUM, it should be in its final state. If you are depositing data that may change (e.g., due to feedback from peer review), please let us know upon deposit. Files can be adjusted and changed during the curation process. Once curation has been completed, files should not be modified. Updates to files after curation will require versioning of the data deposit, which will reset data use statistics and create an additional record.
- What if I discovered my data is wrong and needs to be changed? In this case, DRUM would version your dataset, add the correct files, and update the DOI to point to the updated version.
- Can DRUM accommodate peer review of data? No, but DRUM is an institutional member of Dryad which can accommodate researchers whose data must undergo blind peer review.
Data Curators
Shannon Farrell
Research Data Services Lead & Director of DRUM, University Libraries. Shannon specializes in and curates data related to the biological sciences, including genomic data, ecological data, and others.
Kent Gerber
University Data Archivist, University Libraries, University Archives. Kent specializes in digital archives/digital humanities and appraises all DRUM submissions and assigns them to the appropriate data curator.
Alicia Hofelich Mohr, Ph.D
Research Support Coordinator, Liberal Arts Technology and Innovation Services (LATIS). Alicia specializes in and curates data related to human participants, social sciences, and statistical code.
Shanda Hunt
Research data education and outreach librarian, University Libraries. Shanda specializes in and curates data related to human participants, communities, Tribal agencies, animals, and health sciences.
Melinda Kernik
Spatial Data Analyst and Curator, University Libraries. Melinda specializes in and curates geospatial data for disciplines ranging from the sciences to the humanities.
Wanda Marsolek
Data Curation Librarian, University Libraries. Wanda specializes in and curates data related to engineering and physical sciences.
DRUM is also a founder and institutional member of the Data Curation Network.