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Data Deposit Policy

Click here for a copy of the Data Deposit Policy

Last Updated: 2018-08-24

Terms of Use

You are solely responsible for the contents of your deposit and agree that Florida State University is not responsible for the contents of your deposit. You represent and warrant that:

  • The deposit is your original work, and/or that you have the authority to authorize the uses contained in the license you have selected for your deposit; if your deposit contains material that is not your original work, either you have the right to deposit the materials in this context or you have obtained the necessary permission to do so.
  • Any third-party material is clearly and appropriately identified and acknowledged in the content of the deposit.
  • Your deposit does not infringe upon anyone's rights (e.g., copyright, privacy, defamation, etc.), breach a contract, violate the law, or contain unlawful material.

You are responsible for ensuring that Research data involving the use of human subjects is in accordance with the Florida State University's Institutional Review Board (IRB). You understand and agree that DigiNole Research Repository services are provided "as is" without warranty of any kind, either express or implied, including without limitation, the implied warranties of merchantability or fitness for a particular purpose. You understand and agree that if the Library determines that the terms of service have been violated, it may limit or remove access to the deposited material in question, leaving descriptive metadata and a notice to explain the reason for the removal. The descriptive metadata and the notice will be visible to those who have its persistent URL.

Submission

Depositors may submit their work through the Research Repository main page https://fsu.digital.flvc.org/repository. Fill out the required submission fields, and include your data files and data document as attachments. Users are strongly encouraged to assign a CC0 license to their work, only if they have the right to do so. This can be done through the submission form.
Self-deposit: Maximum size of total files uploaded through a single submission form via the online interface is 100 MB.
Mediated deposit: Data deposits over 100 MB but under 10 GB need to be uploaded to a separate storage site (e.g. Dropbox or Google drive).
Individual files or collections of files that meet these parameters should be shared by contacting The Office of Digital Research & Scholarship at lib-support@fsu.edu, and providing a link to the stored data file or collection. If you have questions regarding preparing your data for submission or require consultation, please contact lib-support@fsu.edu or the Repository Specialist rsmart@fsu.edu.

Data Document

Included with your submission should be a Data Document (also known as a Data Dictionary) in the form of a README.txt file. The purpose of this file is to provide any important information necessary to fully understand and interpret the data. This descriptive information makes your data usable to you, your colleagues, and future researchers. Example, https://deepblue.lib.umich.edu/data/downloads/6969z0927?locale=en

  • README.txt includes:
  • file manifest
  • variable descriptions
  • file structure and relationships
  • file naming conventions
  • software necessary to view data
  • software used to analyze data
  • attribute providers of data/datasets used in research

In your data, do not include:

  • source code that is not made available in the publication as part of the research (e.g. software source code)
  • Personally identifying information
  • Administrative data unrelated to the research process

File Formatting

As the intent of the DigiNole data repository is to make data as openly available as possible for discovery, understanding, and reuse, we strongly encourage the submission of data in formats that are open and non-proprietary. Non-proprietary(Open) File Formats:

  • csv, xml, tar, gzip, zip, gif, png, svg, mp3, txt, ePub, pdf

If data cannot be converted to nonproprietary formats, we then encourage data submission in formats that are widely used. DigiNole will accept data in proprietary formats provided that these formats are appropriate for the research communities who are likely to have an interest in the data. However, it may not be possible to provide as high a level of preservation service for proprietary formats

  • Audio and video files should be no larger than 10 Gbs.
  • Audio/Visual files: mkv, avi, wmv, mp4, flv (animate video file), m4a, mpg, mpeg, flv, m4a, mp3, wav, wma.
  • Include any co-dependent files that must be packaged together, in zip files.

Removing Work from DigiNole

Depositors can request their work removed from the repository with the assistance of the Repository Specialist if it is determined by both parties that the work is not appropriate for the service. The Library will take information accuracy and level of use of the work into account when a removal is requested. The Library may remove any material that is retracted, contains sensitive information, viruses or other malware, or infringes copyright.

Accessibility & Sustainability

The Library is committed to providing the required financial and technical resources for the long-term curation of content in DigiNole. Should the funding or organizational imperatives of the Florida State University Library change, the Library will strive to provide at least one year notice, and devote resources to support the transition to another host institution and/or returning the data to the data producers.

Data Licensing

There are various standard licensing frameworks. For the purposes of licensing data, we recommend specifically the Creative Commons 0 and Open Data Commons licenses:

  • Creative Commons licenses apply to all layers of IP so are sub-optimal for licensing datasets that may include various owners. However, CC0 licenses give owners the option of “opting out” of copyright and are recommended by CC for data. More information can be found at CC0 license.
  • Open Data Commons licenses do distinguish between databases and their “contents”, and so these licenses may provide a more attractive option for licensing datasets. More information can be found at https://opendatacommons.org/.

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