Note: These guidelines form an initial framework that is intended to aid the ScholarsArchive@OSU team in judging whether data may be accepted for deposit into the ScholarsArchive@OSU Data Service. We envision that this rubric will eventually be much broader in scope in the years to come, with a more robust definition of what defines "data".

• Data accepted for deposit is generally defined as the facts and statistics produced for reference or analysis in the course of scientific research undertaken by OSU faculty, researchers or graduate students. (E.g. "numeric data sets", research results, surveys, instrument outputs, databases, and measurements.) Licensed data (such as that originating from the ICPSR, Bureau of Labor Statistics, etc.) is not accepted.
• The data must be produced, submitted, or sponsored by OSU faculty, researchers or graduate students.
• The data should be complete and ready for distribution.
• Classified or confidential data requiring formal, contractual, or legal restrictions to access, such as HIPAA-designated Protected Health Information, will not be included in ScholarsArchive@OSU, but may be archived on IS/CN servers.
• We accept all file formats, although depending on the format of the file there may be limitations on OSU Libraries' ability to preserve it and for the ability of others to use it. We encourage standards and formats that are open (e.g., .txt), commonly used (e.g., .xlsx), or community-recognized (e.g., .mat) be used for all files deposited.
• The dataset may contain multiple files. Individual data files (including zipped/tarred files) uploaded to ScholarsArchive@OSU may not exceed 2 GB. If your data exceeds 2 GB, you should contact us for other options. 
  
• The author/owner must be willing and able to grant OSU the right to preserve and distribute the data (SA@OSU Deposit License), in accordance with user-defined embargo restrictions.
• Each dataset submitted to the ScholarsArchive@OSU repository should contain a 'readme' file listing:
• The contents of the submitted dataset (i.e., file names, formats and sizes of each file). See this dataset, for example.
  
• A list of software used to produce, render and compress the data (where applicable).
• Where in the research process the data falls (e.g. raw/unanalyzed data, processed/analyzed data, rendered/visualized data).
• Submitters are responsible for supplying adequate metadata (descriptive fields) of the contributed dataset for the purposes of discovery and other informational purposes. You may contact us for metadata assistance.
• It is recommended that datasets be described sufficiently, using the ScholarsArchive@OSU platform, so that other knowledgeable researchers can find, understand and use the data.

Many funders now require researchers to have data management plans and share their data as well as the final articles resulting from their research.  Many researchers also see the benefits of open data and code.  Sharing data allows others to reproduce results, which is a cornerstone of science.  It also allows researchers to do new things with existing data.  ScholarsArchive@OSU is an appropriate platform for sharing and preserving data.  This page provides some suggestions of additional tools you can use to share and manage your data throughout your research process.

Much research now involves creating software to manipulate data, or at least creating short scripts.  I encourage you to share any code you create, as it could be helpful to future researchers.

SEND US AN EMAIL