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Preserving and Sharing Data with ScholarsArchive@OSU: FAQ

Oregon State University provides digital preservation and sharing for OSU-affiliated researchers via our institutional repository, ScholarsArchive@OSU. This guide tells you everything you need to know about using SA@OSU for datasets.

Frequently Asked Questions

Why use ScholarsArchive@OSU (and why not)?
ScholarsArchive@OSU (SA@OSU) is a free service for all faculty, staff and graduate students at OSU, and provides a means to permanently archive and share your research results. We provide a local platform for research discoverablility and access, and expert, in-person curation support for all of your needs. That said, there are cases when SA@OSU is not the best choice for archiving or sharing your data. If a public discipline-specific or domain repository exists for your data (e.g. GenBank, INSDC, Protein Data Bank, BioSharing database,, NIH Data Sharing Repositories, ICPSR, NCDC, NGDC, etc.), you should contact them about the possibility of data deposit first. See a list of recommended repositories here. If your dataset is very large or has a geospatital component, your interests may be best served by a platform specifically designed for your data type or format. You may contact us for help in identifying an appropriate repository for your data.

When should I deposit my dataset?
Your dataset may be sumbitted any time after it reaches it's final, static state. If you would like to preserve the dataset but have concerns about making it public, we can embargo the dataset for a time period of your choosing.

How should I prepare my data for deposit?
See this page for guidance on how to prepare your dataset.

If my dataset is associated with a manuscript in review, can I embargo the dataset and still enable reviewers to access the data?
Yes, reviewers just need to do two simple things to gain access to your embargoed item. 1. Register as a new user by clicking "Login" on the upper-right corner of the ScholarsArchive@OSU home page. 2. Send an email to to notify us which item they need access to.

Can I modify files after I have submitted them?
Yes. While we encourage the deposit of "final" datasets only, we understand that datasets are often living records. If you need to update the version of your dataset, contact

How do I cite my dataset?
Data citation standards are still evolving, but in most cases you can cite your dataset in the same way you would cite one of your papers, i.e. in the references. Some journals insert a special note about the location of the dataset at the end of the manuscript, so if your dataset is associated with a specific manuscript, check with your editor. When your dataset is ingested into the repository, a suggested citation will be provided in the item description. If you need to use a specific citation style (e.g. APA, Chicago, etc.), enter your DOI (e.g. '10.1234/1234567') at this site to format the citation for your dataset. For more information about how to cite datasets, see this page.

Will my dataset have a DOI?
Yes, all datasets in ScholarsArchive@OSU are assigned a DOI (permanent, unique identifier).

Can I see how often the dataset is being downloaded?
Yes. Each item in ScholarsArchive@OSU has it's own download statistics. Click "View Usage Statistics" in the menu on the right side of your item page for information on how many times your files have been downloaded on a monthly basis.

Where can I learn more about ScholarsArchive@OSU?
See the SA@OSU FAQ page for more information about the repository.

Why do you encourage the use of a CC0 license for datasets?
For all the same reasons that Dryad does:

All data submitted to Dryad is released to the public domain under Creative Commons Zero (CC0), which reduces legal and technical impediments to the reuse of data by waiving copyright and related rights to the extent permitted by law. In most cases, CC0 does not actually affect the legal status of your data, since facts in and of themselves are not eligible for copyright in most countries (e.g. see this commentary from Bitlaw regarding U.S. copyright law).

CC0 does not exempt those who reuse the data from following community norms for scholarly communication, in particular from citation of the original data authors. On the contrary, by removing unenforceable legal barriers, CC0 facilitates the discovery, reuse, and citation of that data. Any publication that makes substantive reuse of the data is expected to cite both the data package and the original publication from which it was derived.

"Community norms can be a much more effective way of encouraging positive behaviour, such as citation, than applying licenses. A well functioning community supports its members in their application of norms, whereas licenses can only be enforced through court action and thus invite people to ignore them when they are confident that this is unlikely." (Panton Principles FAQ)

"…when you federate a query from 50,000 databases (not now, perhaps, but definitely within the 70-year duration of copyright!) will you be liable to a lawsuit if you don’t formally attribute all 50,000 owners?" (Science Commons Database Protocol FAQ)

Similarly, we do not support the use of licenses that (questionably) assert copyright and add well-meaning, but potentially problematic, restrictions on reuse, such as “non-commercial”, “no derivative” and "share-alike" conditions.

"... given the potential for significantly negative unintended consequences of using copyright, the size of the public domain, and the power of norms inside science, we believe that copyright licenses and contractual restrictions are simply the wrong tool [for data], even if those licenses and contracts are used with the best of intentions." (Science Commons Database Protocol FAQ)

Dryad’s use of CC0 to make the terms of reuse explicit has some important advantages:

Interoperability: Since CC0 is both human and machine-readable, other people and indexing services will automatically be able to determine the terms of use.
Universality: CC0 is a single mechanism that is both global and universal, covering all data and all countries. It is also widely recognized.
Simplicity: There is no need for humans to make, or respond to, individual data requests, and no need for click-through agreements. This allows more scientists to spend their time doing science.

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Mary Markland
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