| This article will appear in Nodalities Magazine, Issue 9.
by Kaitlin Thaney
Program Manager of Science Commons, Creative Commons
In the emerging data web, there have been multiple efforts working towards the same broad goal of data sharing (ie., the NeuroCommons, Linked Open Data, efforts of the World Wide Web Consortium), but are still unevenly distributed. Our understanding of the legal, social and technical issues is increasing, but still is at a very early stage.
This past fall at the International Semantic Web Conference in Chantilly, VA, USA, I joined three other leading minds to lead a tutorial examining some of the legal and social frameworks for sharing data in the emerging data web, focusing on an overview of the need for access, the social issues of applying Free-Libre/Open Source (FLOSS) licenses to data, and the approach we advocate at Creative Commons to help navigate this complex space — converging on the public domain.
Lessons Learned
Creative Commons as an organisation works to make knowledge sharing easy, legal and scalable – with applications in the culture space (music, text, film, art), education (open educational resources, virtual textbooks), and science (biological materials transfer, data sharing, Open Access, semantic web, patents). We maintain an integrated approach, and craft policy and legal tools to lower the barriers to knowledge sharing.
When it comes to data sharing, first and foremost, the information needs to be legally and technically accessible. The Open Access movement has increased awareness to this, using the Creative Commons licensing suite to unlock content, and has seen its share of qualified success. But what to do when the information you want to share and reuse falls outside the protections of copyright?
In short, it’s complicated.
This is the where the discussion of legal protections for data gets murky. Knowledge is not always copyrightable – it may be easy to discern the rights associated with journal articles, but what about data, ontologies, annotations, or research statements described in triples?
The emergence, adoption, and use of the free-libre/open licensing regimes has allowed for remix and reuse of software code, music, film, educational resources and scientific research in a way that otherwise would be difficult to achieve.
The successes of these licensing approaches has caused a change in the social ethos of licensing, instead using a traditional “all rights reserved” model to make something more free, rather than less.
But from our research, this approach is not ideal for data. The trend towards applying licenses, click-wrap agreements and other sorts of restrictions on scientific data is increasing, but with the undesired consequence of limiting the downstream use of this information, and even at times blocking interoperability. The costs are high, the terms are not always clear, nor the protections always legally sound, making it very difficult to scale for scientific uses. The result is a high barrier to entry to do meaningful analysis, annotation, search, etc. on the mass of data available currently that’s continuing to grow exponentially, and integrating with the literature available.
We advocate an approach of converging on the public domain, and requesting behaviours often found in the various flavours of free and open licensing through norms – not a legal construct. But first, let’s take a look at some of the issues to be aware of and their social implications to furthering the goal of linked open data.
Attribution v. Citation
Under US Copyright law, “Copyright does not protect facts, ideas, systems, or methods of operation, although it may protect the way these things are expressed.”Since facts are not covered by copyright, attribution – a license obligation – doesn’t seem to apply to ideas or facts either, since those rights are conditional on compliance with terms of the license.
Socially, the scholarly concept of citation is fairly well understood – credit where credit us due. It has long been viewed as an entrenched norm of good scientific practice.
But when it comes to the legalities of both terms and how to enact this behaviour, the devil is in the details, and the two are actually rather different when it comes to enforceability and applications / ramifications in the digital world.
In a copyright license, the word “attribution” is a legal requirement, whereas citation evokes more of a club mentality and social practice. Citation in its sole form is not assured or enforceable in the same way, but that’s not necessarily a downside. Ask yourself this, which one is more important – legal enforcement or credit enforced through professional reputation? Attribution – a relatively narrow legal term that can affect interoperability while at the same time possibly failing to provide what you really want? Or citation – an entrenched scientific norm that asks for credit where credit is due.
Implications of FLOSS toggles and directives on data sharing
These issues emerge when instead of focusing on maximizing interoperability of resources, one applies a property metaphor to data. And in the digital world, that tendency can have quite limiting ramifications to future use of the information, as technology continues to outpace the social components to data sharing.
Misunderstanding the legalities can lead to category errors on the social level, including unintentional infringement or on the other side of the spectrum, choosing not to use the resource for fear of infringement. The intentions are often good – believing that applying a less-restrictive copyright license is ensuring the data can be freely shared, reused, and built upon. But without existing precedent or involving a legal team, these issues make for a problematic area to navigate, creating additional confusion and burdens for the users, as well as data providers.
Let’s look at a few examples to gain a better understanding.
Non-Commercial – When used in the context of data, what is a commercial use of the data web? Is it the extraction of a subset, a query that may touch on the data set, hyperlinking?
Attribution – As detailed above, the definitions of attribution and citation are often conflated. Attribution speaks to the legal requirement triggered by the use of the work. But in the case of linked open data, if one were to run a query involving 30,000 data sources (something that is happening every day at an ever decreasing cost), would they then be required to attribute the contributors for all 30,000 databases? You can see how this unintended consequence of attribution stacking could impose a very daunting task for the researcher.
Share-Alike – This toggle specifies that any derivative product be relicensed under the same terms. In the example above of running a large query, all it would take would be one database licensed with a share-alike provision for the entire derivate work to then be under the same terms and no other license. This leads to compatibility issues
There are other external mechanisms and limitations imposed by various jurisdictions and countries that can have a profound effect on data-sharing, especially in terms of international data sharing efforts. These include the sui generis database directive in the European Union, Crown Copyright, “sweat of the brow” and “industrious collection” limitations, trade secrets and unfair competition laws, adding another dimension of complexity to an already complex arena.
After convening a series of meetings, roundtables and other discussions with members of the scientific community, the need emerged for a legally accurate and simple solution, that reduced and/or eliminated the need for one to make the distinction of what’s protected. The conflict between understanding the legal issues and complexities can best be resolved by a two-fold approach: (1) a reconstruction of the public domain and (2) the use of scientific norms to request behaviour through a non-license means.
Converging on the Public Domain (+ Norms)
We believe that the public domain is the best means to achieve maximum interoperability of data with the lowest imposed burdens on the user. This can be achieved through the use of a legal tool – either the Creative Commons CC0 Waiver or the Public Domain Dedication and License (PDDL) – waiving all intellectual property rights asserting that the provider makes no claims on the data. These tools put the work as closely into the public domain as possible.
It calls for data providers to waive all rights necessary for data extraction and re-use (ie., copyright, sui generis database rights, claims of unfair competition, implied contracts). It also requires the provider place no additional obligations such as copyleft or share-alike on the information, which could limit downstream use, as discussed above.
Science Commons also crafted the Protocol for Implementing Open Access Data – a protocol for evaluating database terms of use, in hopes of providing a unified framework for users to evaluate if any given database may be integrated with any other database.
The Protocol recommends one request behaviour, such as citation, through norms and terms of use rather than as a legal requirement based on copyright or contracts.
We are aware that different disciplines and jurisdictions call for different approaches, and this is not always a one-size-fits-all solution. With requesting behaviour through norms and terms of use rather than a legal construct, various scientific disciplines have the ability to develop their own norms for citation, allowing for legal certainty without constraining one community to the norms of another.
Final Thoughts
In the early days of the World Wide Web, there weren’t many free-libre licenses available, and after a debate over using GPL for the original web code, CERN chose to put it into the public domain. Getting the law out of the way was key to allow for network effects, and to the success of the Web.
Converge on the public domain and ensure the freedom to integrate. It’s the most scalable solution.
This work is licensed under a Creative Commons Attribution 3.0 License.
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