BioSharing is Caring: Being FAIR

FAIR: Findable, Accessible, Interoperable, Reusable
Source: Scientific Data via http://www.isa-tools.org/join-the-funfair/ March 16, 2016.

In my work for BioSharing, I get to see a lot of biological data standards. Although you might laugh at the odd dichotomy of multiple standards (rather than One Standard to Rule Them All), there are reasons for it. Some of those reasons are historical, such as a lack of cross-community involvement during inception of standards, and some are technical, such as vastly different requirements in different communities. The FAIR paper, published yesterday by Wilkinson et al. (and by a number of my colleagues at BioSharing) in Scientific Data, helps guide researchers towards the correct standards and databases by clarifying data stewardship and management requirements. If used correctly, a researcher can be assured that as long as a resource is FAIR, it’s fine.

This article describes four foundational principles—Findability, Accessibility, Interoperability, and Reusability—that serve to guide data producers and publishers as they navigate around these obstacles, thereby helping to maximize the added-value gained by contemporary, formal scholarly digital publishing. Importantly, it is our intent that the principles apply not only to ‘data’ in the conventional sense, but also to the algorithms, tools, and workflows that led to that data. All scholarly digital research objects—from data to analytical pipelines—benefit from application of these principles, since all components of the research process must be available to ensure transparency, reproducibility, and reusability.(doi:10.1038/sdata.2016.18)

This isn’t the first time curators, bioinformaticians and other researchers have shouted out the importance of being able to find, understand, copy and use data. But any help in spreading the message is more than welcome.

Standards
Source: https://xkcd.com/927/

Need more help finding the right standard or database for your work? Visit BioSharing!

Further information:

How can BioSharing help you? Give us 5 minutes and have your say!

BioSharing Enhancements Questionnaire: http://goo.gl/forms/BQ9lRMNQxE

Recently, I asked the opinions of the BioSharing Advisory Board and RDA Working Group members about how BioSharing is perceived and how they envision its use. The set of responses has helped the BioSharing team create a questionnaire whose purpose is to let us know which enhancements they find most important. Now it’s time to ask the wider life sciences community which of those enhancements should have the highest priority. Please take a look at our questionnaire and let us know what features you’d like to see on BioSharing.

Image from http://www.biosharing.org/pages/about/
Image from http://www.biosharing.org/pages/about/

As described on our site, BioSharing works to map the landscape of community developed standards in the life sciences, broadly covering biological, natural and biomedical sciences. BioSharing‘s goal is to ensure standards are informative and discoverable, monitoring their:

  • development, evolution and integration;
  • implementation and use in databases; and
  • adoption in data policies by funders and journals.

BioSharing works to serve those seeking information on the existing standards, identify areas where duplications or gaps in coverage exist and promote harmonization to stop wasteful reinvention, and developing criteria to be used in evaluating standards for adoption.

We would like your input as to which features we add first. Please take 5-10 minutes to answer our questionnaire, as the more responses we get, the more useful the questionnaire becomes. Your answers will help us prioritize our improvements to BioSharing’s capabilities in a way most appropriate to your needs.

BioSharing Enhancements Questionnaire: http://goo.gl/forms/BQ9lRMNQxE

Thanks!

Attribution vs Citation: Do you know the difference?

Often the words “attribution” and “citation” are used interchangeably. However, in the context of ensuring your work gets the referencing it deserves when others make use of it, it is important that the differences between these two concepts are clear. This article outlines the differences between attribution and citation, and suggests that what most scientists are interested in is not attribution, which can be ensured via licensing restrictions, but instead citation, which is a much tougher nut to crack.

This is a cross-posted, two-author item available both from my and Frank Gibson’s blog (his post).

Often the words “attribution” and “citation” are used interchangeably. However, in the context of ensuring your work gets the referencing it deserves when others make use of it, it is important that the differences between these two concepts are clear. This article outlines the differences between attribution and citation, and suggests that what most scientists are interested in is not attribution, which can be ensured via licensing restrictions, but instead citation, which is a much tougher nut to crack.

From xkcd, at http://xkcd.com/285/
From xkcd, at http://xkcd.com/285/

At ISMB last week, there were a number of conversations about the difference between attribution and citation. This topic was brought up again yesterday in a conversation between the authors of this post. It is an important distinction which is explored in this post.

First, some definitions for attribution and citation. These are not the only definitions possible, but for the purposes of this discussion, please keep these in mind.

Attribution: Acknowledgement of the use of someone else’s information, data, or other work. Crucially, while Wikipedia has a fairly straightforward definition of citation, it does NOT mention even common ways that attribution should be implemented (see Wikipedia attribution page).

Citation: When you publish a paper that makes use of someone else’s information (data, ontology, etc.), you include in that paper a reference to the work of that other person or group. Wikipedia states that it is a “reference to a published or unpublished source” whose prime purpose is of “intellectual honesty”.

Distinguishing between attribution and citation.
You can imagine that citation is a specific type of attribution, but attribution itself can be performed in any number of ways. For scientists, citation is much more useful to their careers as a result of the publish or perish environment.

So, what could attribution consist of? First, let’s take as an example the re-use of someone else’s ontology or specific sub-parts or classes of that ontology. Each class in an ontology is identified by a URI. Therefore, is importing the URL enough? With a URI is it clear where you got the class from? If it’s not enough, where do you put that reference or statement that you are re-using other classes: within the overall metadata of your own ontology? Alternatively, when attributing data is a reference to the originating paper or URL from where you downloaded the data enough? Where do you put that reference: within the metadata of your own document? As a citation? How much is enough attribution?

These questions cannot easily be answered.

A common-sense answer to the question of properly fulfilling requirements is to, at a minimum, first cite their information in your paper, and second include URL(s)/URI(s) in your metadata. But here we get to the crux of the matter: we’ve now stated that a useful way to ensure attribution is to cite the other person. But, if you think carefully, what’s more important for your impact assessments, and your work? It’s actually the citation itself. Sure, acknowledgement via extra referencing in the metadata of the person using your information is great, but what you really need is a citation in their work. If we aren’t careful, we will all make the easy mistake of conflating citation in papers with importing a licensed piece of information and how to mark its inclusion: the former is what we often are scored on and what we would really like, while the latter is the only thing a license enforces. Licensing with attribution requirements is not citation; you can make use of a licensed ontology, but this does not require you to cite it in a paper.

Attribution: the legal entity.

Important point: It’s easy to use a license such as the CC-BY, thinking that you’ll ensure citation, when in fact all you’re doing is ensuring attribution.

What are the implications of attribution? It can quickly get out-of-control and difficult to manage.
By requiring attribution in an ontology or data file, if someone imports information (such as a class from an ontology) into their own document, the new one must attribute the original. Continuing the ontology analogy, if there are 20-30 ontologies being used for a single project (which is not inconceivable in the coming years), there could be great difficulty in maintaining attribution for them all.

Important point: While licenses such as the CC-BY allow the attribution to be performed “in the manner specified by the author or licensor”, this could lead to 30 different licensors requiring potentially 30 different methods of attribution, and attribution stacking isn’t pretty.

Citation: the gentlemen’s club.

Can citation be assured? No. Well, maybe.
You can imagine citation as a gentlemen’s club, as propriety dictates that you should cite another’s work that you use, but there is no legal requirement to do so. Indeed, many believe that citation should not be enforced anyway. In contrast, attribution as required by licenses is a legal statement. However, let’s revisit the clause in CC-BY that states the author/licensor can specify the manner in which the attribution is given.

Important point: Could you use a license such as CC-BY, and state that the attribution must come in the form of, at a minimum, citation in the paper which describes the work being performed by the licensee?

Bottom line: which one is more important to you, as a scientist? Depends on the context.
This is difficult to answer. There aren’t very many guidelines available for us to analyse. The OBO Foundry does have a set of principles, the first of which states that “their [the ontology(ies) and their classes] original source is always credited and that after any external alterations, they must never be redistributed under the same name or with the same identifiers”. However, how this credit is attained is unclear, as described in various blog posts (Allyson, Frank, Melanie). As a result, the following conclusions came out of the OBO Foundry workshop this summer (Monday outcomes): it is “unclear if each ontology should develop their own bespoke license or use develop ‘CC-by’; how to give attribution? Generally use own judgment, here MIREOT mechanism can help when importing external terms into an ontology, giving class level attribution” (MIREOT web page, see also OWLED 2008 paper). Therefore, while they are aware of the problem, they don’t offer a consensus solution(s).

The flipside of this is that in order to use an ontology, you first have to write a paper and cite the classes you wish to import, then get on with the work. If you never get a paper and therefore a citation, is you ontology/data illegal? If you take the example of OBI, which imports several other ontologies and is an open community of developers, would a license restriction requiring citation actually prevent the work starting? This is probably a bit of a chicken-and-egg scenario, if it were ever to come a reality. In short, while there are some tempting possibilities, there doesn’t yet seem to be a useful solution.

In summary, it’s generally not attribution that people want (which can be licensed, even if you don’t like the layers of attribution that will require once you’re using multiple sources) but citation, which isn’t so easily licensed – yet. When deciding what sort of license to use (e.g. an open one like CC0 or an attribution-based one like CC-BY), you need to take into account expected usage. In some cases, for a leaf ontology, perhaps CC-BY is appropriate, as it isn’t intended to be imported by others, but you never know when your leaf will turn into something others import. Science Commons also believes that attribution is a very different beast, and shouldn’t be required when licensing data. They provided me with an answer to how to license ontologies recently that favored CC0.

So, if you really want citation and not attribution, consider an open license such as CC0 and make a gentlemanly (gentle-science-person-ly) request that if someone uses it AND publishes a paper on it, please cite it in the way you suggest. Alternatively, I’d be interested to hear if it would be possible to use an attribution-based license such as CC-BY and then require the attribution method be citation in a paper. Would this method work, and would it be polite? Your comments, please.

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