Intellectual property rights (IPR) management is an important part of any data management program. A builder of a database or other data resource will have an interest in who owns that resource and how others may use it. Someone who may populate that resource with data provided in part by others will want to make sure that all legal, ethical, and professional obligations that one may have to the provider of the data are met. Since the benefits of data sharing are so well known and documented, a researcher may wish to share their database and/or content with others. Others can only fully utilize external data if they know the terms of use (if any) for that data. This fact sheet provides a brief overview of some of the issues associated with managing IPR in data projects.
In any data project, there are likely to be two components. The first is the data collected, assembled, or generated. Think of it as the raw content in the system. It could be hourly temperature readings from a sensor, the age of individuals in a survey, recordings of individual voices, or photographs of plant specimens. The second component is the data system in which the data is stored and managed.
We usually do not think of data content separate from the system in which it is stored, but the distinction is important in terms of intellectual property rights. The question is what, if anything, is protected by copyright. Data that is factual has no copyright protection under U.S. law; it is not possible to copyright facts. Not all data is in the public domain. A project might, for example, use copyrighted photographs; the photographs are part of the project’s “data.” In many cases, the data in a data management system as well as the metadata describing that data will be factual, and hence not protected by copyright.
A database, on the other hand, can have a thin layer of copyright protection. Deciding what data needs to be included in a database, how to organize the data, and how to relate different data elements are all creative decisions that may receive copyright protection.
Because of the different copyright status of databases and data content, different mechanisms are required to manage each. Copyright can govern the use of databases and some data content (that which is itself original), but contract law, trademarks, and other mechanisms are required to regulate factual data.
In order to facilitate the reuse of data, it is imperative that others know the terms of use for the database and the data content. Fortunately, the Open Data Commons group (http://opendatacommons.org) has been developing legally binding tools to govern the use of data sets. Using a combination of copyright and contractual standards, they have created three standard licenses that one can use in conjunction with data projects. In addition, it is possible to articulate a set of “community norms” that complement the use of formal licenses. While not having the force of law, norms can express the shared beliefs of a community vis-à-vis data sharing and reuse.
The three ODC licenses are:
Creative Commons (http://www.creativecommons.org/) also has a library of standardized licenses, and some of them apply to data and databases. The ODC-By license, for example, is the equivalent of a Creative Commons Attribution license (CC BY). CC BY licenses, however, require copyright ownership of the underlying work, whereas the ODC-By license applies to works not protected by copyright (such as factual data)
The two CC licenses that are of greatest relevance to data management are:
There is no single right answer as to which license to assign to a database or content. Note, however, that anything other than an ODC PDDL or CC0 license may cause serious problems for subsequent scientists and other users. This is because of the problem of attribution stacking. It may be possible to extract data from a data set, use it in a research project, and still maintain information as to the source of that data. It is possible to create a data set derived from hundreds of sources with each source requiring acknowledgement. Furthermore, the data in the other databases may not have originated with it, but instead sourced from other databases that also demand attribution. Rather than legally require that everyone provide attribution to the data, it might be enough to have a community norm that says “if you make extensive use of data from this data set, please credit the authors.”
The ownership of works produced by University of Dayton faculty, students, and non-academic staff is governed by the University of Dayton Intellectual Property Policy. The precise answer will depend on whether the project was created as part of sponsored research; the employment status of the creator; and other considerations. Questions regarding this policy should be directed to the Vice President for Research.
CC0 (+BY). Cohen, Dan. 2013. http://www.dancohen.org/2013/11/26/cc0-by/. A call for using CC0 with data, tempered by an ethical obligation to attribute.
Copyright Guide for Scientific Software. Albert, Kendra, Bouquin, Daina, Farber, Alena, & Hoover, Russell. 2019. Zenodo. http://doi.org/10.5281/zenodo.3581326. A joint project of the Harvard Cyberlaw Clinic and the Center for Astrophysics, in association with the Software Preservation Network, that provides clear, easy-to-read answers to common questions about how scientific software and copyright interact.
Data Citation Developments. Kratz, John. 2013/ http://datapub.cdlib.org/2013/10/11/data-citation-developments/. An update on efforts to standardize data attribution requirements.
How to License Research Data. Ball, Alex. 2012. http://www.dcc.ac.uk/resources/how-guides/license-research-data. Written with British law in mind, but it has a good discussion of the pros and cons of the ODC licenses.
Licensing Open Data: A Practical Guide. Korn, Naomi and Oppenheim, Charles. 2011. http://discovery.ac.uk/files/pdf/Licensing_Open_Data_A_Practical_Guide.pdf. Another guide written with UK law in mind, but with a helpful comparison of CC and ODC licensing options.
Open Data. Wikipedia. http://en.wikipedia.org/wiki/Open_data
Open Licenses. Project Open Data. https://project-open-data.cio.gov/open-licenses/. The US Federal Government guide to open licenses and dedications.
RDA & CODATA Legal Interoperability of Research Data: Principles and Implementation Guidelines - Now Published. Research Data Alliance. https://www.rd-alliance.org/rda-codata-legal-interoperability-research-data-principles-and-implementation-guidelines-now. A set of practical guidelines for researchers dealing with legal aspects of sharing data.
Sharing Research Data and Intellectual Property Law: A Primer. Carroll, Michael W. 2015. http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002235. An introduction to the various kinds of property rights that can be associated with research data.
Adapted from the Research Data Management Service Group website (https://data.research.cornell.edu), Cornell University. Made available under a Creative Commons Attribution 4.0 International License: https://creativecommons.org/licenses/by/4.0/. Retrieved from https://data.research.cornell.edu/content/intellectual-property.