SPAR Ontologies migrated to GitHub

In the first days of January, we have completed the migration of all SPAR Ontologies to GitHub. The new SPAR Ontologies GitHub Organisation includes several repositories, one for each ontology included in SPAR (see, for instance, the one for CiTO). Among the advantages of this migration, this separation of concerns will make easier to post and handle issues and to gather new feedback from the community by using the GitHub issue tracker available in each repository.

The content negotiation mechanism of all the SPAR ontologies is now handled outside the SPAR Ontologies website, by means of the w3id.org service. Thus, in case of some issues in the website (e.g. server crashes), the ontologies will be reachable anyway. In addition, we have also released the new contribution guidelines for allowing the community to propose new ontologies to be added within the SPAR suite. We are now open to accept external contribution in a more structured way. To this end, we are in the process of releasing the new version of FAIR* Reviews ontology within the SPAR Ontologies, our very first early adopter of the aforementioned contribution guidelines.

Please do not forget to follow the SPAR Ontologies on Twitter for getting additional updates.

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The use of Named Graphs to enable ontology evolution

This is a re-publication of a Position Paper given at the W3C Workshop on the Semantic Web for Life Sciences, Cambridge, Massachusetts, USA.  27-28 October 2004, since the original is not presently available on the Web, and the paper contains some ideas I did not wish to get lost.

[A second related paper from that era, republished as a blog post on the Ontogenesis Knowledge Blog on 22nd January 2010, is entitled Ontologies for Sharing, Ontologies for Use by David Shotton, Chris Catton and Graham Klyne.  This is available at http://ontogenesis.knowledgeblog.org/312.]

The use of Named Graphs to enable ontology evolution

Position Paper, W3C Workshop on the Semantic Web for Life Sciences, Cambridge, Massachusetts, USA.  27-28 October 2004

Chris Catton chris.catton@zoo.ox.ac.uk and David Shotton david.shotton@zoo.ox.ac.uk

Image Bioinformatics Lab, University of Oxford, Dept. Zoology, South Parks Road, Oxford OX1 3PS, UK

[These were the e-mails and postal address of the authors at the time, but they are longer valid.]

Position: The dangers of static ontologies

The role of an ontology is to facilitate the understanding, sharing, re-use and integration of knowledge through the construction of an explicit domain model, thereby helping to address many of the difficulties currently experienced in managing large distributed on-line information resources.

With the volume of digital data now estimated to be doubling every month, soon the only way to handle much of this new information will be through the presuppositional ‘spectacles’ of an ontology. Already people look less and less at raw data, and as the volume accumulates few if any of us will have the time or the mental capacity to assimilate the new data, structure them in a meaningful way, and extract information without first processing the data through an ontology or some other similar machine-based organisational aid. This creates a potential ‘paradigm trap’, first identified by Duncan Davidson (Davidson, 2002). The philosopher Thomas Kuhn first used the term ‘paradigm’ to define the way we perceive, think about and value the world, based upon a particular vision of reality. He argued that changes to the current paradigm, “together with the controversies that almost always accompany them, are the defining characteristics of scientific revolutions” (Kuhn, 1966). There is a danger that building and using an ontology may fossilize the current paradigm in a particular field of knowledge, so that only information that fits the paradigm is actually ever seen by the user. Such an outcome would not itself halt scientific progress, since incremental knowledge that fits the current paradigm would still accumulate. It could, however, hinder or possibly even prevent the discovery and exploration of new and uncharted territory. Even in less extreme cases it is essential that ontologies can evolve as a field of study develops.

Factors favouring static ontologies

We perceive several inter-related influences that favour the fossilization of current domain paradigms into static ontologies:

1. Ontology building currently requires a high level of dedication and understanding, and consequently ontologies tend to be built by small communities of dedicated ‘monks’. These are usually led by ‘abbots’, relatively senior domain experts who are likely to be highly committed to encapsulating the dominant paradigm, and who may resist change.
2. Ontology building is a time-consuming and expensive exercise, and thus substantial logistic problems confront any newcomers wishing to involve themselves in such activities.
3. Ontology building quite rightly encourages the development of community consensus. There would thus be massive social pressures against anyone wishing to create an alternative ontology for use in an already populated domain.
4. The first ontology to be created for a particular domain of knowledge may assume a monopolistic position that becomes virtually unassailable, even if it has universally acknowledged weaknesses in its structure.
5. If a large volume of legacy data has been encoded with a successful ontology, this will make it difficult to introduce change.
6. Most ontologies currently under development have both good bits and bad bits, and users typically select the bits they want and ignore the rest. They may thus use a subsection of Ontology A to encode publications data, a subsection from Ontology B to encode personnel information, and most of Ontology C to categorise their biological results. As ontologies become widely used it is possible to imagine that the conceptualisation of a domain will be encoded not in a single ontology, but in a mosaic made up of segments from a number of different ontologies. This ability to pick and choose sections from a set of ontologies mitigates against the commonly held view that ontologies will evolve through a competitive ‘survival of the fittest’. There is no single ontology that can ‘succeed’ or ‘fail’ as a result of competitive selection pressure. For this reason, we believe that ontologies are unlikely to evolve in response to the same market forces that drive the development of applications software.

Possibilities for change within the present system

When and how does the conceptualisation of a domain change? Kuhn argued that “Just because it is a transition between incommensurables, the transition between competing paradigms cannot be made a step at a time, forced by logic and neutral experience” (Kuhn, 1966). This is a view that has wide and influential support, for example from Max Plank who wrote “a new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it” (Planck, 1949).

That viewpoint might be interpreted as speaking against the very possibility of reflecting a paradigm shift within an ontology. However, we believe this not to be the case, as outlined in the following sections. We distinguish two forms of paradigm shift, which we will call evolutionary and revolutionary. In an evolutionary shift, a significant new body of knowledge is appended to an existing conceptualisation, while in a revolutionary shift, the conceptualisation itself is restructured.¹

With hindsight, Albert Einstein’s relativity theory can be seen as an extreme example of an evolutionary shift. The old paradigm, Newtonian Mechanics, continues fundamentally unchanged. However, new restrictions are placed on it, since the laws once thought to be universal now only hold true for bodies moving at much less than the speed of light. New laws must be added to describe the case where bodies move at close to the speed of light. It is possible to imagine an ontology describing Newtonian Mechanics as a subgraph of an ontology describing General Relativity. In the new paradigm Newtonian mechanics is not wrong, but now applies under a limited set of conditions. There is a fundamental difference between this and the Copernican revolution. The Copernican revolution is an example of a revolutionary paradigm shift. The old laws no longer hold true. The Earth is not the centre of the universe. The old laws must be removed from the ontology, and replaced with a new set of laws to accommodate the new paradigm.

Evolutionary change of an ontology

As an example of how an evolutionary paradigm shift might be represented in an ontology, consider the graphs shown in Figs. 1 to 3. Fig. 1 shows a section of an ontology describing the development of adult mammalian bone marrow and brain, constructed according to the paradigm of twenty five years ago, when the consensus was very clearly that bone marrow developed from mesoderm and brain developed from ectoderm.

Subsequently, it was shown that adult mouse brains contain haemopoietic stem cells. Since it seemed unlikely that adult bone marrow stem cells would cross the blood-brain barrier to enter the adult brain, it was hypothesised that the brain cells were derived from foetal haemopoietic cells that entered the brain tissue before the barrier was established. (Bartlett, 1982). This proposal is reflected within the ontology given in Fig. 2, which is an extension of the graph shown in Fig 1.

Fig 1. Ontology of the dominant paradigm circa 1980. Haemopoietic cells develop only from mesoderm and neural and glial cells develop only from ectoderm. In this and subsequent figures, solid arrows represent owl:allValuesFrom restrictions – e.g. neural cells can develop only from ectoderm – while dashed arrows are owl:someValuesFrom restrictions.

Fig 2. Ontology of the new paradigm post 1982, reflecting the hypothesis that brain haemopoietic stem cells have been derived by the migration of foetal haemopoietic stem cells of mesodermal origin. This challenges the dominant paradigm that brain tissues are derived exclusively from ectoderm.

Fig 3. Ontology of the emerging paradigm post 2000, after it had been shown that adult haemopoietic stem cells of mesodermal origin can migrate into the brain and there develop into neural cells.

 

More recently, it has been shown by Brazelton et al. (2000) that haemopoietic stem cells from adult bone marrow can develop into neural cells in adult mouse brain. This striking demonstration of the migration potential and developmental plasticity of adult stem cells both challenges the assumption of Bartlett (1982) that haemopoietic stem cells do not cross the adult blood-brain barrier, thereby throwing in doubt Bartlett’s conclusion that they must have entered during foetal life, and, more fundamentally, negates the long-held belief that neuronal cells can only develop from embryonic ectoderm. An ontology that reflects these new findings is shown in Fig. 3.

Now imagine that the graph in Fig. 1 is part of a much larger developmental anatomy ontology. What should be the response to papers that challenge the accepted paradigm, given that many challenges to dominant paradigms are subsequently proven to be erroneous in some way? Kuhn would argue that it would be inappropriate to make a change, since “.. by ensuring that the paradigm will not be easily surrendered, resistance guarantees that scientists will not be lightly distracted and that the anomalies that lead to paradigm change will penetrate existing knowledge to the core”. But if the ontology is to be employed to assimilate the results in the first place, how can experimental scientists test their hypotheses without changing the ontology?

The ontology change from Fig 1 to Fig 2 does not present a serious problem for the experimental scientist working on a problem that provokes a crisis in the paradigm. She can simply create a new ontology of her own describing the subdomain in question, import the dominant ontology into it and add the appropriate links between the two. If this combined ontology fits the experimental data better, we would expect it to gather support, and eventually to be accepted as the consensus view. The new ontology succeeds by subsuming the old. The change from Fig 2 to Fig 3 creates a more serious problem. The ontology in Fig 2 is no longer a subgraph of Fig 3, since neural cells no longer develop only from foetal neuroepithelium. However, in practical terms, the old ontology may still be required to interpret a mass of legacy data. Furthermore, it is easy to see that although the present system can permit limited expression of evolutionary paradigm change, it is likely to lead to a haphazard collection of ontologies within which some subset of classes and properties embody the old paradigm, while others embody the new world view, with no obvious mechanism for distinguishing between them using currently available OWL constructs.

Requirements for creating evolvable ‘living ontologies’

The work of Brazelton et al. generates a revolutionary paradigm shift, where the old ontology no longer holds true. The present system does not permit easy organic development of ontologies in a manner that could accommodate such a change. We thus believe that it would be useful to create a mechanism that would enable ontologies both to evolve in a controlled manner by the accretion of new classes and relationships, and to accommodate revolutionary paradigm shifts while remaining to some degree backward compatible.

A key part of building such evolvable ‘living ontologies’ lies in creating the potential for making clearly defined changes. What is required is a mechanism not only for importing subgraphs from existing external ontologies, but also for replacing subgraphs within the ontology of interest with new versions that reflect the new paradigm, while at the same time marking the original subgraphs in such a manner that they remain available for the (re)interpretation of legacy metadata previously created using them.

Such a mechanism would allow users to state explicitly the differences between the current paradigm and the proposed new conceptualisation in a way that would allow the two conceptualisations to co-exist, avoiding an unmanageable proliferation of separate ontologies. This may theoretically be possible using current OWL constructs such as owl:versionInfo. However, owl:versionInfo can only be applied at the class level or the ontology level. Neither of these alternatives is the appropriate level of granularity to meet the needs discussed here. Rather, to allow such changes to the conceptualisation of a domain, we need to be able explicitly to select a subgraph from an existing OWL ontology, and to name it and define its properties.

A strategy for the required management of subgraphs within ontologies is made possible using Named Graphs (Carroll et al, 2004). Named Graphs are currently being proposed as an alternative to reification in RDF, and as such they address a number of issues associated with adding metadata to data. We propose that Named Graphs be employed to permit the addition of provenance and other metadata to subgraphs within an ontology. Of course, not all changes to an ontology will represent paradigm shifts, and users may need to know whether changes to relationships in an evolving ontology reflect relatively minor choices about the manner in which a domain being modelled, or more fundamental changes to the domain paradigm itself. Named Graphs would also enable such distinctions to be made.

One of the core motivations for the introduction of named graphs into RDF is to provide a framework for proof and trust. It is certainly possible to imagine this framework being easily transferred to OWL ontologies. So, for example, one user might be happy to trust the Gene Ontology completely, while another user, experimenting in an area where the paradigm is in crisis, might elect to trust the Gene Ontology with the exception of a particular subgraph defined by a single class and all its subclasses. This subgraph might eventually be replaced by a new one reflecting a new paradigm.

Conclusion

Scientific progress proceeds in a series of conceptual or technological leaps, followed by periods of consolidation. Before the introduction of ontologies into data analysis, community support for the dominant paradigm tended to restrain change. While such restraint has been acknowledged as performing a useful function, it is a blunt instrument. The introduction of defined ontologies into data analysis could make the introduction of radical change even more difficult to achieve. The solution proposed here does not solve all the problems of viewing data through the presuppositional lens of an ontology. Anomalies may still be missed simply because they do not fit the paradigm – as has always been the case in the practice of science. However, by clearly stating the positions of the dominant paradigm and the proposed changes to it, and by allowing users to give trust or confidence ratings to subgraphs, the process of change can be clearly documented. The use of Named Graphs to identify and describe subgraphs within existing ontologies potentially provides a powerful mechanism for clarifying differences between the dominant and emergent paradigms. As Francis Bacon observed “Truth emerges more readily from error than from confusion” (Spedding et al., 1896).

References

Spedding, J. Ellis, R. L. & Heath D. D. (eds.) (1905) The Works of Francis Bacon. G. Routledge & Sons, London.

Bartlett, p. (1982) Pluripotential hemopoietic stem cells in adult mouse brain. Proceedings of the National Academy of Sciences USA, 79: 2722-2725.

Carroll, J. J., Bizer, C., Hayes, P. and Stickler, P. (2004) Named Graphs, Provenance and Trust. Online at http://www.hpl.hp.com/techreports/2004/HPL-2004-57.

Davidson, D. (2002) The Mouse Atlas – an ontology for mapping gene function data to the mouse embryo. Proc. Conf. on Standards and Ontologies for Functional Genomics (SOFG). Hinxton, Cambridge, November 17-20, 2002.

Kuhn, T. S. (1996) The Structure of Scientific Revolutions, 3rd edition, p. vii. University of Chicago Press, Chicago, Illinois.

Planck, M. (1949) Scientific Autobiography and Other Papers. Philosophical Library, New York.

Brazelton, T.R., Rossi, F.M.V., Keshet, G.I., Blau, H.M. (2000) From marrow to brain: Expression of neuronal phenotypes in adult mice. Science 290: 1775-1779.

1    Kuhn would argue against the distinction we make here. In his view, all paradigm shifts are revolutionary, since they require a fundamentally different view of the world, and the appearance of evolution, when it is present, is simply a post hoc revision of what actually happened during the course of a paradigm shift. We do not intend to challenge this view, but for the purposes of illustration we choose to accept the revisionist position.

 

 

Mapping DataCite 3.1: updated ontology and mapping document

It is not the first time we introduce our work on mapping DataCite to RDF – as already discussed in a previous post on this blog.

Some news on this front: recently, David Shotton, Jan Ashton, Amy Barton, Egbert Gramsbergen, and Marie-Christine Jacquemot, and I have started a joint collaboration for producing a new version of the DataCite ontology and for updating existing mapping document from DataCite XML terms into RDF according to the current available DataCite Specification, i.e., the DataCite Metadata Schema 3.1 released in 2014.

Today we are very proud to announce the publication of three documents, which are the result of our hard work during the past five months:

• the new version of the DataCite Ontology – part of the SPAR Ontologies and summarised by the Graffoo diagram below – has been released and introduces several new entities for modelling new kinds of identifiers related to agents;
• the updated version of the mapping document according to the aforementioned DataCite Metadata Schema 3.1, which is available on FigShare (for easy citing):
  Peroni, S., Shotton, D., Ashton, J., Barton, A. J., Gramsbergen, E., Jacquemot, M.-C. (2016). DataCite2RDF: Mapping DataCite Metadata Schema 3.1 Terms to RDF. Version 3.3. http://dx.doi.org/10.6084/m9.figshare.2075356;
• an example of the conversion of an existing DataCite XML document into RDF according to the aforementioned mapping document, which is available on the SPAR Ontologies website as well as on FigShare (for easy citing):
  Peroni, S. (2016): Example of use of DataCite #2. figshare. https://dx.doi.org/10.6084/m9.figshare.2075353.

The Graffoo diagram introducing the main classes and properties of the DataCite Ontology.

As in the past blog posts on this topic, we warmly commend the use of this mapping and the related SPAR Ontologies (among which the DataCite Ontology) to all who wish to encode DataCite metadata in RDF, and welcome feedback on this work.

Open Article Gauge

Further to the previous post describing various types of open and closed access, I would like to bring people’s attention to a very useful service developed by Cottage Labs a year or so ago that automatically reports the degree of openness of various publications by looking at their license information.

Called Open Article Gauge, it is part of a family of resources and services called
HowOpenIsIt?, which also includes The Open Access Spectrum (OAS) developed by PLOS, SPARC, and OASPA, a written guide that makes it easier to determine how open journals and journal articles are across the spectrum between fully Libre Open Access and Closed Access.

Open Article Gauge reviews articles (identified by their DOIs or PubMed IDs) and identifies the licensing information associated with these publications. Where a license can be determined, the results page gives the name of the license, a link and details of the associated re-use rights.  The Open Article Gauge service is available as a website, an API, and as source code. More details are given on the Cottage Labs OAG page.

Describing open access

To permit computer-readable descriptions to be made of the various types of open access publication discussed in the previous blog post, I have expanded PSO, the Publication Status Ontology, whose use is described in an earlier blog post here, by the addition of the following new individuals to the class pso:Status:

• pso:gratis-open-access
• pso:libre-open-access
• pso:green-open-access
• pso:gold-open-access.

I have also revised the definitions of the following further individuals that were already members of the class pso:Status:

• pso:closed-access
• pso:open-access
• pso:embargoed
• pso:restricted-access
• pso:subscription-access.

This comprehensive set of terms permits the various access statuses of documents to be encoded in RDF and published on the Semantic Web.  For convenience of reference, the textual definitions that I have used for these terms (recorded as rdfs:comments in the PSO ontology), grouped in logical order, are given below.

pso:open-access

The status of a published work (typically a scholarly publication or a dataset) that is freely available via the Internet for third parties to read without payment of access or subscription fees, and (in the case of a work published under a full open-access license) that is freely available to download and reuse for any purposes including commercial ones, including modification of the original work, its integration with other material, and its re-publication, subject typically to a requirement that the original authors and the source of the original work are acknowledged in compliance with scholarly citation norms.

pso:gratis-open-access

The status of a published work which is free to read on-line, in contrast to subscription-access works, but to which licensing restrictions apply, limiting the possibilities for downloading, text mining, modification, re-publication or re-use of the published work.  The term Gratis Open Access thus signifies removal of the price barrier to view.  While both imply ‘free’ (a potentially ambiguous word), Gratis Open Access equates to ‘free as in beer’ while Libre Open Access (q.v.) equates to ‘free as in speech’.  Gratis Open Access is thus a necessary but not a sufficient condition for true Libre Open Access.   Many ‘open access’ publications by commercial scholarly publishers are only Gratis Open Access, while almost all publications by ‘pure’ Open Access publishers are Libre Open Access.

pso:libre-open-access

The status of a published work which is both free to read on-line, and to which additional usage rights apply, for example the right to text mine, make derivative works, re-use and re-publish the published work, such rights frequently being defined by application of an explicit license such as a Creative Commons license.

pso:gold-open-access

The status of a published work, typically a journal article, made available by the publisher on the publisher’s own web site for third parties to read without payment of access or subscription fees.  Gold open access has the benefit that the article is findable where you expect it to be, but licensing restrictions may limit the possibilities for downloading, text mining, modification, re-publication or re-use of the published work.  Gold open-access publication typically involves payment by the author or his/her institution to the publisher of an article processing charge (aka an author publishing charge).

pso:green-open-access

The status of a published work made available by the author, by self-archiving a version of the work for free and open public use in their institutional repository, in a central repository, or elsewhere, in parallel with publication of a subscription-access Version of Record of the work by a publisher.  The green open-access version of the work may be a preprint (the version of the article as first submitted for publication) or a postprint (the pre-publication version of the article after incorporation of authors’ responses to peer reviewers’ comments).  Its availability may have an embargo restriction imposed by the publisher of the subscription-access version of the work that prevents the green open-access version from being freely available until some substantial time after publication of the subscription-access journal issue containing that article.  A green open access work should be accompanied by a license explicitly defining usage rights, for example a Creative Commons Attribution License.

pso:subscription-access

The status of a published work, typically an article in a journal issue, that is not available to read without payment of an article access fee or a journal subscription fee for that publication.

pso:embargoed

The status of a published work that is subjected to a publication embargo, which means that the material cannot be published, or in the case of a press release that it cannot be reported on, until a particular date known as the embargo date.  For open-access journal articles, an embargoed article is one in which availability of the open-access version of the article is delayed by the publisher for a substantial embargo period, typically of six or twelve months, after subscription-access availability of the published work.

pso:restricted-access

The status of a work (typically a scholarly paper or a dataset) to which access is restricted.  For example, confidential information to which access is made available only to those who have been approved by the owner or copyright holder of the asset after personal application, or to those with appropriate security clearance, or to those within a partnership.

pso:closed-access

The status of a work (typically a private or secret paper or a confidential dataset) that is typically held unpublished in a ‘dark’ archive whose existence is unknown by the wider world, and that is only available to the owner or copyright holder of the asset.

pso:confidential

The status of a document containing information that must be kept confidential.

pso:non-confidential

The status of a document containing information that may be shared publicly.

pso:unpublished

The status of a work (for example a document or a dataset) that has not been published by the author, a publisher or a data repository.

Of relevance to these statuses are two financial terms within FRAPO, the Funding, Research Administration and Projects Ontology, previously described in this blog post: frapo:ArticleProcessingCharge and frapo:Subscription.

Open access journals – wheat, chaff and hopeful monsters

The Fifth Annual Conference on Open Access Scholarly Publishing, organized by OASPA, the Open Access Scholarly Publishers Association [1], was held in Riga, the capital of Latvia, on 18th-20th September 2013.  I was invited to attend to discuss the Open Citations Corpus, a repository of open bibliographic citation data initially harvested from the reference lists of open access journal articles.  This post contains my belated reflections on the major themes raised by that interesting meeting.

The conference, which was well organized by Claire Redhead, OASPA’s Membership & Communications Manager, was attended by 85 people, including representatives of some 37 publishers and of 22 other organizations including major funders, policy organizations and libraries, and a handful of other interested parties such as myself.  Both ‘pure’ Open Access publishers and more traditional publishers who publish a mixture of open-access, hybrid and subscription-access journals were represented.  The venue, the Radisson Blu Hotel, provided excellent accommodation and conference facilities, enabling us to work effectively, in five themed sessions of talks and discussion over two and a half days.

The lead keynote speaker for the Riga meeting was Lars Bjørnshauge, Director of DOAJ, the Directory of Open Access Journals, a marvelously useful information source that he founded in 2003 at the University of Lund, which since December 2012 has been under the supportive wing of IS4OA [2].

Lars started the meeting by exposing the first major theme, namely quality control in OA journals.  Given the ease of on-line publishing and the explosive growth of OA journals over the last few years, there is great current concern both in DOAJ and in OASPA to determine which of these open access journals are legitimate scholarly publications, and which are simply attempts on the part of fake or non-legitimate publishers to separate authors from their cash in the form of substantial article processing charges (APCs, aka author publication charges) in return for a mediocre service.  Lars suggested a number of criteria by which OA journals should be judged, include the following:

• That journals should provide the names and contact details for the editorial board.
• That journal articles should have a clear and transparent peer reviewing policy.
• That journal articles should be published under a Creative Commons CC-By attribution license, so that readers’ rights to re-use the articles are clear.
• That journal articles should have DOIs (Digital Object Identifiers), typically, for scholarly articles, DOIs issued to registered publishers by CrossRef.
• That journal articles should be accompanied by machine-readable metadata.
• That publishers should archive digital journal articles for future reference, and that this should be done in machine-readable formats such as an XML DTD such as JATS (the NISO Journal Article Tag Suite), rather than as a PDF document.

To this end, DOAJ and OASPA, together with the Committee on Publication Ethics and the World Association of Medical Editors, have recently jointly published a set of Principles of Transparency and Best Practice in Scholarly Publishing against which to evaluate all OA journals.

The second major theme of the Riga meeting, opened by Michael Jubb of the Research Information Network in the following talk, concerned the exact nature of scholarly OA publishing and its financial implications.  Michael outlined the striking progress being made in the UK to implement recent OA mandates for publication of research work funded by public purse, discussing both the Finch Report and the Research Councils UK’s Policy on Open Access.  This requires that articles be published under Creative Commons CC-By licenses, so that the content may be freely mined and otherwise re-used – the ideal situation for the reader.

This highlighted the distinction, often veiled for nominally open access publications from commercial publishers, between the two types of open access, characterised as Gratis versus Libre:

• Gratis Open Access signifies removal of the price barrier alone, giving a right to read the article off the screen.  However, the publication is still restricted by licenses that do not permit it to be downloaded or reused in any way.
• Libre Open Access signifies removal both of the price barrier and at least some of the permission barriers limiting reuse, giving rights to text-mine and re-use the article.

Thus, while both imply ‘free’ (a potentially ambiguous word), Gratis Open Access equates to ‘free as in beer’, while Libre Open Access equates to ‘free as in speech’, an analogy for which Peter Murray-Rust is to be thanked. Gratis Open Access is thus a necessary but not a sufficient condition for true Libre Open Access.  Many ‘open access’ publications by commercial scholarly publishers are only Gratis Open Access, while almost all publications by ‘pure’ Open Access publishers are Libre Open Access.

Michael also discussed the tension between Gold Open Access (OA article published on publisher’s web site), which typically involves payment of APCs, and has the benefit that the article is findable where you expect it to be, and Green Open Access, where the publisher permits the author to publish, in an institutional repository or similar third-party site, a preprint (the version of the article as first submitted for publication) or a postprint (the pre-publication version of the article after incorporation of authors’ responses to peer reviewers’ comments), often with an embargo restriction that prevents the article from being freely available until some substantial time after publication of the subscription-access journal issue containing that article.  The latter (Green OA) is the cheaper way for UK universities to comply with the RCUK policy, but means that potential readers may have difficulty finding the article, the content of which (if it is a preprint) may not be the same as the published Version of Record.

Representatives of other funding agencies and policy organizations similarly set forth their OA agendas.

The third theme to emerge from the conference was the contentious issue of hybrid journals, initially set forth by Liz Ferguson of Wiley-Blackwell.  Hybrid journals are scholarly journals in which one has to pay a subscription to view the majority of articles, but which may also contain OA articles for which the authors have had to pay substantial APCs.  The bone of contention is the degree to which commercial publishers should or do lower their journal subscription charges as the number of OA articles within them rises, to avoid what is politely termed “double dipping”, i.e. getting academics to pay publishers not just once but twice for the privilege of reading their own works of scholarship.  On this topic, several publishers claimed that they were doing the honourable thing.  Someone commented “The only way for hybrid is to take the publisher’s word”!

Falk Reckling of FWF (the Austrian Science Fund) told the conference of the Austrian experiment to avoid increased library payments to publishers while achieving open access publication, in which publishers were directly reimbursed for all papers funded by FWF, and the amount paid was then deducted from the subscriptions paid to them by the Austrian Library Consortium the following year.  He reported that most big publishers, including Elsevier, Wiley and Taylor & Francis, rejected that proposal.  Falk concluded by saying that only by working together internationally could funding agencies succeed in forcing change on the publishers, a sentiment echoed particularly by Cameron Neylon of the Public Library of Science.

Victoria Gardner of Taylor & Francis surprised me by pointed out that the average cost of publishing an article in the humanities and social sciences (HSS) was more than three times that in science, technology and medicine (STM), largely because of the papers were larger and had higher rejection rates.  She stated that the author-pays APC model was not financially viable for HSS, where many researchers, particularly early in their careers, lack funding income that could be used for that purpose.  There was thus tension in the debate “OA is unworkable for the Humanities” versus “OA is the future” that was not resolved.

Apart from the costs of OA, and particularly of hybrid journals, the other discussion issue concerned their future.  Are hybrid journals stepping stones to a fully open-access world, or are they hopeful monsters, doomed to extinction?  Liz Ferguson reported Wiley to have ~1,200 hybrid journals that between them had published only about 3,500 articles – on average just three articles per journal – with many journals having no OA uptake at all.  Several other publishers reported their experiences with hybrid journals.  But Georg Botz of Science Europe told the meeting flatly that “the hybrid model is not a working and viable pathway to OA.”

Apart from these main themes, there were talks from a number of leading OA publishers about their progress and achievements, and an interesting discussion about the growing trend of Open Access book publication led by Eelco Ferwerda of OAPEN, an open access library of books in the humanities and social sciences, and Cecy Marden of the Wellcome Trust, who discussed funding of OA monographs and the importance of Europe PubMed Central as a repository for OA publications.

The final morning of the conference saw presentations on a number of separate additional themes, including a “meet the OASPA members” session containing inspiring presentations by Brian Hole of Ubiquity Press, who described how quality OA publishing could be achieved at a fraction of the conventional costs discussed above, and by Lyubo Penev of Pensoft Publishers, an innovative OA publisher of journals relating to biological taxonomy, who described the Pensoft Writing Tool, an integrated online collaborative authoring, editing, reviewing and publishing platform that facilitates semantic enhancements and the publication of datasets accompanying articles (see also http://www.pensoft.net/page.php?P=31&SESID=auzykddds), that I have mentioned in a previous blog post.

It was during that session that I gave my invited talk entitled Open Citations Corpus – freeing scholarly citation data, described in a separate Open Citations Blog post.

In summary, OASPA’s Fifth Annual Conference on Open Access Scholarly Publishing revealed the world of open access journal publishing to be one of rapid growth and innovation, and of clear tensions regarding quality control, cost, licensing, and applicability to HSS.  It was clear that commercial academic publishers were attempting to hang on to established modes of publishing, funding and tight licensing while making limited concessions towards openness in the form of hybrid journals and a smaller number of OA journals under terms that benefit them financially.  The elephant in the room, never fully articulated, was the extent to which, and for how long, the commercial publishers’ traditional business model of high profit margins can withstand the competition of the newer Open Access publishers, particularly those offering radically cheaper publishing avenues for scholars.  Cameron Neylon reminded us that disruptive technologies achieve market dominance not by being disruptive but by addressing a recognised and current need, so that their adoption then drives the disruption.

Clearly for the foreseeable future we will have a transitional mixed publishing economy in which ‘pure’ OA journals will exist alongside subscription-access and hybrid journals, with a plurality of business models.  Improvements in mechanisms for micropayments and for splitting payments between multiple authors’ institutions are required.  Funders’ mandates are driving expansions of Gold and Green OA publishing and minimizing restrictions to reuse by adoption of more permissive CC-By licensing, but universities are struggling to find funds to pay OA APCs while maintaining conventional journal subscription payments.  Embargos to access and lack of interoperability between institutional repositories continue to restrict the usefulness of Green OA.  So there is real momentum towards OA, but mixed progress and great disparity between nations.  Further change is inevitable and to be welcomed.

[1]     OASPA was established in 2008 to represent the interests of Open Access (OA) journal publishers globally in all scientific, technical and scholarly disciplines.  Paul Peters from the Hindawi Publishing Corporation is currently Chair of the OASPA Board, and is editor of the OASPA Blog.   The presentations from the Riga meeting are currently available from http://oaspa.org/conference/presentations-coasp-2013/.  The 6^th Conference on Open Access Scholarly Publishing (COASP) will be hosted by UNESCO at their Paris Headquarters from September 17th – 19th, 2014.  Further information will be posted on the OASPA conference page (http://oaspa.org/conference/) as it becomes available. Details of the inaugural OASPA Asia conference, to be held in Bangkok in June 2014, are presently given at http://oaspa.org/conference/. 

[2]     IS4OA (Infrastructure Services for Open Access) is a Community Interest Company based in the United Kingdom, led by Caroline Sutton, the immediate past-president of OASPA and by Alma Swan, a consultant working in the field of scholarly communication who has a long history of supporting open access initiatives.  IS4OA acts as an umbrella organisation for open access activities and services that are of value to the academic community and beyond, providing business structure and expertise and a means of obtaining and channelling financial support for these activities and services.

Extending CiTO to enable use of the Open Annotation Data Model to describe citations

Characterizing CiTO properties – the CiTO Functions Ontology

[This post was modified on 20 October 2017 by David Shotton, to reflect the change in CiTO,  the Citation Typing Ontology, of the name of the class cito:CitationAct to the new name cito:Citation, with a revised definition.  This has required changing the text “cito:CitationAct” to “cito:Citation” in several places in this post.  However, the sense of this post has not changed.]

CiTO, the Citation Typing Ontology, contains 41 object properties that can be used to characterize the nature of a bibliographic citation linking the citing paper to the citing paper, plus an equal number of their inverse properties.  Some of these are also appropriate for the characterization of data citations, as described here.

These can be classified into factual properties (e.g. cito:usesDataFrom) and rhetorical properties, with the latter being sub-grouped into positive properties (e.g. cito:supports), neutral properties (e.g. cito:reviews) and negative ones (e.g. cito:critiques).

These sub-groupings are described in a new extension ontology, the CiTO Functions Ontology available from http://www.essepuntato.it/2013/03/cito-functions.

However, despite this extensive list of CiTO properties, there will be situations in which the purpose of making a citation cannot be adequately expressed using these CiTO properties.  In such situations, it is now possible to use the new Open Annotation Data Model (http://www.openannotation.org/spec/core/) to define the reason for, or the nature of, the citation.

New CiTO class and properties to use with the Open Annotation Data Model

To make this straightforward, we require a mechanism that permits the citation itself to be objectified, so that it can become the object of an RDF triple defined using a URI.  To facilitate this, we have added a new class to CiTO, cito:Citation, that defines and describes the citation itself:

cito:Citation

A citation is a conceptual directional link from a citing entity to a 
cited entity, created by a human performative act of making a citation, 
typically instantiated  by the inclusion of a bibliographic reference 
(biro:BibliographicReference) in the reference list of the citing entity, 
or by the inclusion within the citing entity of a link, in the form of 
a HTTP Uniform Resource Identifier (URI), to a resource on 
the World Wide Web. 

To complement this class, three new object properties have been added to CiTO:

cito:hasCitationCharacterization

A property that links a cito:Citation to its characterization made by 
using a CiTO citation characterization property such as cito:confirms.

cito:hasCitingEntity

A property that relates a cito:Citation to the citing entity.

cito:hasCitedEntity

A property that relates a cito:Citation to the cited entity.

Adopting the same philosophy as used for the other CiTO object properties, we have avoided adding domain and range restrictions to these properties, enabling them to be used in circumstances that we do not foresee.

Reifying citation statements

This new CiTO class cito:Citation, and its accompanying new object properties cito:hasCitingEntity, cito:hasCitationCharacterization and cito:hasCitedEntity, can be employed to reify direct citation act statements made using the CiTO citation object property cito:cites or one of its sub-properties. For example, the following RDF statement:

:paperA cito:extends :paperB .

can be alternatively described as follows:

:thisCitation a cito:Citation ;
     cito:hasCitingEntity :paperA ;
     cito:hasCitationCharacterization cito:extends ;
     cito:hasCitedEntity :paperB .

This usage involved OWL2 punning, whereby a CiTO object property, such as the aforementioned cito:extends, is used as the object of the OWL assertion:

:thisCitation cito:hasCitationCharacterization cito:extends .

Using such OWL2 punning (described at http://www.w3.org/TR/2009/WD-owl2-new-features-20090611/#F12:_Punning), the CiTO object property is considered as a proper named individual of the class owl:Thing.

Such reification of citation acts can be very useful, since it permits one to combine these CiTO properties with other vocabularies, or to handle situations in which none of the citation characterizations available in CiTO are applicable.  Such situations can be resolved by the creation of a user-defined citation characterization, for example by using the Open Annotation Data Model.

Introducing the Open Annotation Data Model

Use of the Open Annotation Data Model is well described by Robert Sanderson in his SlideShare presentation at http://www.slideshare.net/azaroth42/oai8-openanno.   In this model, an annotation is described as a member of the class oa:Annotation, which has a body containing the annotation itself defined by oa:hasBody, and an annotation target (the thing to which the annotation relates) defined by oa:hasTarget, as shown in the following figure.

Legend: The Open Annotation Basic Data Model (from Robert Sanderson’s SlideShare presentation at http://www.slideshare.net/azaroth42/oai8-openanno).

Using the Open Annotation Data Model to characterize citations

In our case, the target of the annotation is a member of the class cito:Citation, while the body, i.e. the textual content of the annotation itself, is described using the W3C Content Vocabulary (http://www.w3.org/TR/Content-in-RDF10/) as a member of the class cnt:ContentAsText, which the property cnt:chars relates to the text string actually providing the annotation.

As shown in the figure, an OA annotation can be further characterized by the motivation for making the annotation, defined by oa:isMotivatedBy.  In our case, the appropriate motivation is oa:commenting, an instance of the class oa:Motivation.

Thus characterization of a bibliographic citation using the Open Annotation Data Model can take the following form:

:thisAnnotation a oa:Annotation;
     oa:motivatedBy oa:commenting ;
     oa:hasBody [ a cnt:ContentAsText ;
          cnt:chars "I'm citing that paper because it initiated 
                     this whole new field of research." ] ;
     oa:hasTarget [ a cito:Citation;
          cito:hasCitingEntity :PaperA ;
          cito:hasCitationEvent cito:cites ;
          cito:hasCitedEntity :PaperB ] .

Simple and flexible!  We commend use of the Open Annotation Data Model to make such “free-hand” citation characterizations.

FRAPO, the Funding, Research Administration and Projects Ontology

FRAPO, the Funding, Research Administration and Projects Ontology, is a CERIF-compliant ontology available from http://purl.org/cerif/frapo/ for describing administrative information relating to grant funding and research projects.  It can be used for the characterization of grant applications, funding bodies, research projects, project partners, etc., in other words the sort of information stored in Current Research Information Systems (CRIS).   It can also be used to describe other types of projects, for example building projects and educational projects.

FRAPO, which is written in OWL2-DL, imports FOAF, the Friend of a Friend Vocabulary for characterizing people.  FRAPO is designed to be used in conjunction with SCoRO, the Scholarly Contributions and Roles Ontology, described in a previous blog post, that provides structured vocabulary terms to describe the contributions and roles of scholars, and the organizations of which they are members, with respect to projects, research investigations and other academic activities describable using FRAPO, and to the scholarly journal articles and other outputs that result from them.

Terms for documents of relevance to the scholarly domain covered by FRAPO, including grant applications, project plans, project reports, datasets and journal articles, are already provided by FaBiO, the FRBR-aligned Bibliographic Ontology, and are therefore not included within FRAPO.

The basic concepts within the FRAPO model are shown in the following figure.

Legend: The basic concepts within the FRAPO model.

FRAPO also permits descriptions of various types of applications, funding programs, infrastructure entities (e.g. services and research facilities), and a wide range of financial entities (e.g. accounts, contracts, quotations, purchases, invoices and payments), and the relationships between them (e.g. has application outcome, is manufactured by, is purchased by, has dispatch date, has purchase order number, has acronym) not shown in the diagram above.

As soon as it is available, a Graffoo technical diagram of the FRAPO structure will be added to this post.

A discussion of the manner in which FRAPO and SCoRO relate to CERIF, the Common European Research Information Framework, will be the subject of a subsequent post.  Suffice it to say now that while CERIF has a relational database model, making automated conversion of CERIF metadata to ‘clean’ RDF difficult, FRAPO and SCoRO are OWL2-DL ontologies designed for expressing the same concepts cleanly as Linked Data.

Additionally, by working together and with the other SPAR ontologies, and by employing the Time-indexed Value in Context Pattern (TVC) discussed in the SCoRO blog post, they enable both the contexts and the time frames of roles and contributions to academic endeavours to be clearly articulated.

SCoRF, the Scholarly Contributions Report Form

SCoRF, the Scholarly Contributions Report Form, is a metadata entry tool, in the form of an Excel spreadsheet familiar to all researchers, that makes easy the tasks of entering details describing the contributions of scholars to research investigations and of authors to the scholarly journal articles that result from them, and of describing their roles as researchers and authors.

SCoRF uses controlled vocabulary terms defined in SCoRO, the Scholarly Contributions and Roles Ontology, which, as explained in the previous blog post, imports and expands PRO, the Publishing Roles Ontology.

In SCoRF, these terms are structured into drop-down lists attached to the spreadsheet cells, from which the user selects appropriate options, permitting rapid metadata entry in a way that all but eliminating the need for typing. No new or unfamiliar technology is required either by authors or publishers. The exercise of ascribing contributions and roles to the people involved in an average journal article using SCoRF should take no more that 15 minutes (excluding thinking time!), and the resulting report is suitable for submission to a publisher together with the manuscript to which the report relates.

The inclusion of ontology terms within an Excel spreadsheet has been made possible by the use of RightField, described in [1], an application developed by Stuart Owen and colleagues at the University of Manchester as part of the SysMO-DB Project. A RightField-enabled Excel spreadsheet such as SCoRF contains ‘hidden’ sheets with information concerning the origins and versions of ontologies used in the annotation, that can be viewed using the RightField Inspector, and from which RDF-encoded metadata can be extracted. For the scholar, the main advantages of using RightField are that it enables users to create consistent annotations without having to change their working practice or understand the underlying SCoRO ontology – everything is embedded in the Excel spreadsheet.

In conformance with the recommendations in the final report of the recent International Workshop on Contributorship and Scholarly Attribution, the SCoRF spreadsheet permits authorship contributions, intellectual contributions, experimental contributions and organizational contributions to be separately recorded, the individual members of the classes scoro:AuthorshipContribution, scoro:IntellectualContribution, scoro:ExperimentalContribution and scoro:OrganizationalContribution) being explicitly listed in the first column of the spreadsheet.

The items in the drop-down list associated with each of the ‘contribution effort’ cells, in each of these ‘contribution’ rows in the spreadsheet, represent the three individuals of the class scoro:ContributionEffort, namely scoro:solo-effort, scoro:major-effort and scoro:minor-effort. This enables the effort expended by one person on a particular contribution, relative to the efforts expended by others on that same contribution, to be specified on a simple four-point scale – ‘contributed all the effort’, ‘contributed major effort’, ‘contributed minor effort’, or ‘contributed no effort’ (the default contribution, expressed by leaving the cell blank).

Roles are recorded separately from contributions, within the categories authorship roles, data roles, investigation roles and project roles. The items in the drop-down lists associated with the ‘role’ cells of the spreadsheet represent individuals within the classes scoro:AuthorshipRole, scoro:DataRole, scoro:InvestigationRole and scoro:ProjectRole, for example scoro:corresponding-author, scoro:data-curator, scoro:research-assistant and scoro:project-manager, respectively.

As an example, the following table lists the possible values for authorship roles and authorship contributions specified within SCoRO.

Authorship roles Article guarantor Author Consortium author Corresponding author Illustrator Photographer Principal author Senior author

Authorship contributions Approved final manuscript Prepared the illustrations Prepared supplementary information Published data Revised the manuscript Wrote the manuscript draft

Similar lists of SCoRO controlled vocabulary terms for all the other types of role and contribution are given in the SCoRF Help worksheet that accompanies the Report worksheet. If the contribution choices provided by SCoRO are inappropriate, additional contributions can be specified under ‘Other’ and entered manually.

The following figure shows the region of the blank SCoRF Report worksheet concerned with roles, displaying the drop-down list of controlled vocabulary terms from SCoRO from which the user can select his or her authorship role for the article under consideration. In recognition that people may have more than one role, up to four authorship roles, two data roles, two investigation roles and two project roles may be specified in the SCoRF spreadsheet for any one person.

Legend: The Roles section of the SCoRF Report worksheet, with a drop-down list of authorship roles taken from SCoRO, the Scholarly Contributions and Roles Ontology.

The second diagram shows that region of the SCoRF Report worksheet concerned with recording a person’s contributions to various tasks, the effort involved in making each contribution being selectable from a drop-down list.

Legend: The first part of the Contributions section of the SCoRF Report worksheet. The drop-down list for the selected cell enables this contributor’s effort expended on the task of writing the manuscript draft to be specified.

As an example of how the SCoRF Report worksheet might be used in practice, the following figure shows the roles and contributions for myself and for Katie Portwin, the first two authors in our “Adventures in Semantic Publishing” paper [2].

Legend: The region of a completed SCoRF Report worksheet showing the first two authors of Reference [2], providing information both about the research project and the journal article reporting its results. Text entries shown with a green background are ontology class labels drawn directly from SCoRO and used to pre-populate the SCoRF spreadsheet. Text entries with a purple background are ontology instance labels drawn directly from SCoRO, those in the second and third columns (providing information for contributors 1 and 2) having been selected from drop-down lists. Note that the only information that had to be manually entered into the form (by typing or by pasting from another source) is contained in the few cells having an orange background. (To simplify and compact the spreadsheet for display in this figure, unnecessary columns and unused rows have been removed.)

Completing the SCoRF report form for all four authors of that paper took me about ten minutes, demonstrating that with this tool the creation of rich metadata about scholarly roles and contributions is not an arduous task. The completed exemplar form for our “Adventures in Semantic Publishing” paper, of which this figure shows a selected region, is available at http://purl.org/spar/scoro/Exemplar_Report_Form.xls.

The SCoRF spreadsheet, published under a CC-By attribution license, is generic and easy to modify, and thus could be customized by a publisher for incorporation into a journal’s manuscript submission system. I commend its use to the academic community and to scholarly publishers.

Reference

[1]    K.Wolstencroft, S.Owen, M.Horridge, O.Krebs, W.Mueller, JL. Snoep, F.Preez, C.Goble (2011). RightField: Embedding ontology annotation in spreadsheets. Bioinformatics, 27 (14): 2021-2022. doi:10.1093/bioinformatics/btr312.

[2]    Shotton D, Portwin K, Klyne G, Miles A (2009). Adventures in semantic publishing: exemplar semantic enhancement of a research article. PLoS Computational Biology 5: e1000361. http://dx.doi.org/10.1371/journal.pcbi.1000361.

SCoRO, the Scholarly Contributions and Roles Ontology

SCoRO, the Scholarly Contributions and Roles Ontology, is a new CERIF-compliant ontology for use by authors, publishers and research administrators, for describe the contributions and roles of scholars, and the organizations of which they are members, with respect to projects, research investigations and other academic activities, and to the scholarly journal articles and other outputs that result from them.

The need for such a disciplined way of describing scholarly contributions and roles was articulated at the International Workshop on Contributorship and Scholarly Attribution held at Harvard University on 16 May 2012. At that workshop, an early version of the SCORO ontology was presented. The current version has been refined and improved as a result of the feedback received and the recommendations contained within the workshop’s Final Report.

Clearly, the present informal system of ascribing scholarly roles and contributions to the authors of academic papers people is ill-suited to the needs of the digital age, where machine-readable metadata to describe and accompany on-line articles is desirable.

In particular, the order in which authors’ names appear in a paper’s author list is a highly imprecise and ambiguous method of signaling credit, since its meaning varies significantly between academic disciplines. At least three different conventions are in common usage:

• Alphabetical, widely used in disciplines such as mathematics to indicate a commitment not to distinguish between the relative importance of the different authors;
• Sequence determines credit, where authors are listed in order of declining importance; and
• First author – last author emphasis, the norm in the biomedical sciences, usually interpreted as meaning that the first author did most of the work while the last author is the senior author who has contributed the intellectual driving force, while intermediate authors made less important contributions.

Some journals now insist on author contribution statements at the end of articles, but these generally relate to a different topic, namely investigation contributions, rather than attribution of authorship credit.

For example, the acknowledgements in one Nature paper published in November 2007 are exemplary in their simplicity and clarity:

• Experimental
  
  • A.C. and J.H.H. conducted the observations.
  • A.C. processed the data.
  • P.W.L. performed the modelling.
• Authorship
  • A.C. wrote the main paper.
  • P.W.L. wrote the Supplementary Information.
• General
  
  • All authors discussed the results and implications, and commented on the manuscript at all stages.

However, such contribution statements can be more specific, complex and idiosyncratic, as exemplified in another paper from the same issue of Nature:

• J.L., J.R.S. and J.W.L. conceived the Brainbow strategies.
• J.R.S. and J.W.L. supervised the project.
• J.L. built initial constructs and validated them in vitro and in vivo.
• T.A.W. performed all cerebellar axonal tracing and colour profile analysis with programs developed with J.L.
• H.K. performed all live imaging experiments.
• R.W.D. generated Brainbow-1.0 lines expressing cytoplasmic XFPs.
• R.A.B. generated Brainbow-1.1 constructs and lines.
• J.L., T.A.W. and R.W.D. screened mouse lines.

Note in this second case how detailed domain knowledge is required to understand the meaning of some of the contributions, e.g. “conceived the Brainbow strategies”, “built initial constructs”, “validate constructs” or “screened mouse lines”.

Another instance of detailed author attribution occurs in the March 2011 issue of Nature Genetics, and took the following form:

• B.G., J.B., R.C.H. and G.P.P. conceived and designed the study.
• B.G., J.B. and D.M. implemented the process, built and populated the databases.
• K.R.P., F.C.C. and H.F. performed experiments.
• B.K.S., D.J.A., A.N.B., B.C., P.F., A.E.F., A.F., R.G., M.V.E.G., M.G., R.J.G., P.C.G., C.L.H., J.D.H., M.J., P.J., E.K., P.K., S.M., K.M., J.O., A.P., M.N.P., P.P., S.Pa., L.P., M.R., S.S., I.S., M.S., S.L.T., J.T.-S., R.T., T.W., J.S.W., C.W., B.Z. and G.P.P. contributed data.
• B.G., J.B., D.R.H. and S.Ph. analyzed results.
• R.C.H. and G.P.P. supervised data analysis.
• D.M., W.M., C.R., D.H.K.C. and H.W. provided expertise and infrastructure.
• B.G., J.B., D.R.H., K.R.P., S.Ph., R.C.H. and G.P.P. wrote the paper.

The authors of this paper concluded

“Our project provides the first example of implementing microattribution to incentivise submission of all known genetic variation in a defined system. It has demonstrably increased the reporting of human variants, leading to a comprehensive online resource for systematically describing human genetic variation in the globin genes and other genes contributing to hemoglobinopathies and thalassemias.”

However, one drawback of this system of author contribution statements as practiced is that the contributions of non-authors such as research technicians are poorly acknowledged, despite the fact that they may have contributed significantly to the research investigation whose results are reported in the article.

The Harvard – Wellcome Trust workshop concluded that we need an easy and more straightforward way to define the contributions of both authors and non-authors, in a manner that distinguishes:

• Intellectual contributions, including the conception and design of experiments;
• Experimental contributions, including provision of experimental material, undertaking experiments and analyzing data;
• Organizational contributions, including fund-raising and project management; and
• Authorship contributions, such as drafting the paper and preparing the illustrations.

The workshop participants were not keen on the idea that the relative effort of different people to such contributions should be accounted for using numerical quantitation, e.g. “Dr X contributed 80% and Dr Y contributed 20% of the effort to the contribution of revising the manuscript”. This decision was largely reached both because assigning contribution efforts with mathematical precision could not be achieve, and also because such numbers would be of little practical usefulness.

Rather, it was thought sufficient to say that someone was solely responsible for a particular contribution, played a major role in it, played a minor role in it, or had no part in it.

SCoRO meets this requirement by creating a limited controlled vocabulary of generic terms to describe contributions within these four general categories. It also provides the option of specifying the effort for each contribution, relative to that of others:

• Solely responsible for this contribution.
• Contributed major effort.
• Contributed minor effort.

The default position is that a person played no part in a particular contribution, which is assumed unless one of the other effort categories is specified.

In addition to specifying such contributions, SCoRO distinguishes and permits the separate definition of individuals’ roles, under the following categories:

• Investigation roles, such as Principle Investigator, Research Assistant or Technician;
• Project roles, including Project Leader and Project Manager;
• Data roles, such as Data Creator, Data Manager or Curator; and
• Authorship roles, including Corresponding Author, Senior Author, Article Guarantor, and Consortium Author (to cover entries in author lists such as “. . . and members of the MalariaGen Consortium”).

This distinction between roles and contributions is useful, since, for example, people other than the PI can be active in contributing to the leadership of an investigation, and people other than the formal Data Manager can be involved in managing data.

The basic conceptual structure of SCoRO is as shown in the following diagram:

     Legend: The basic concepts within the SCoRO model.

Additionally, SCoRO provides terms for organizational, financial and teaching roles relevant to academic activities which are unrelated to scholarly research and journal article authorship, but which are useful in other circumstances. Publishing roles, for example those of editor and reviewer, have previously been separately covered in PRO, the Publishing Roles Ontology, which is imported into SCoRO.

This import of PRO into SCoRO permits us to employ a standard ontology design pattern called the Time-indexed Value in Context Pattern (TVC) [1], that is already part of PRO. This pattern permits one to specify both the context and the time-period for a particular contribution or role, if required, by introducing one level of indirection between the object and the location, via the class tvc:ValueInTime, as explained in the PRO section of a recent blog post on use of the SPAR ontologies: Libraries and linked data #5: Using the SPAR ontologies to publish bibliographic records.

This ontology design pattern is exemplified in the following RDF statement:

foaf:Agent pro:holdsRoleInTime [ a pro:RoleInTime ;
        pro:withRole pro:editor ] .

Here, the domain of pro:withRole is not foaf:Agent, but rather an anonymous member of the class pro:RoleInTime, which itself is the range of the property pro:holdsRoleInTime, for which the domain is foaf:Agent. The range of pro:withRole is the class pro:Role, and its sub-classes pro:PublishingRole, scoro:InvestigationalRole, scoro:OrganizationalRole, etc., whose members permit specific roles to be specified. New roles can easily be added, simply by inserting new individual members into the appropriate subclass of pro:Role.

This single step of indirection permits contextual and temporal attributes to be specified, putting that role into context. Exactly the same use of TVC and of individuals within the class scoro:Contribution and its sub-classes may be used for scoro:withContribution, enabling contributions also to be time-limited and given contexts.

Examples of this design pattern being used both for two roles and for a contribution, with specification of the context of both roles, the time interval during which the second role of Principal Investigator was valid, and the context of the contribution, are given in the following example:

:ourInvestigation a frapo:Investigation ;
   dcterms:title "Experiments in Semantic Publishing" ;
   frapo:hasOutput :Adventures .

:Adventures a fabio:JournalArticle ;
   dcterms:bibliographicCitation "Shotton D, Portwin K, Klyne G, 
      Miles A (2009). Adventures in semantic publishing: exemplar 
      semantic enhancement of a research article.
      PLoS Computational Biology 5: e1000361." ;
   dcterms:creator :Shotton , :Portwin , :Klyne , :Miles ;
   prism:doi "10.1371/journal.pcbi.1000361" .

:Shotton a foaf:Person ; foaf:name "David Shotton" ;
   scoro:hasORCID "0000-0001-5506-523X" ;

   pro:holdsRoleInTime [ a pro:RoleInTime ;
      pro:withRole scoro:author , scoro:senior-author ;
      scoro:relatesToPublication :Adventures ] ;

   pro:holdsRoleInTime [ a pro:RoleInTime ;
      pro:withRole scoro:principal-investigator ;
      tvc:atTime [ a ti:timeInterval ;
         ti:hasIntervalStartDate "2008-05-01"^^xsd:date ;
         ti:hasIntervalEndDate "2009-04-17"^^xsd:date ] ;
      scoro:relatesToEntity :ourInvestigation ] ;

   scoro:makesContribution [a scoro:ContributionSituation ;
      scoro:withContribution scoro:conceives-project ;
      scoro:withEffort scoro:major-effort ;
      scoro:hasContributionContext :ourInvestigation] .

[This RDF is expressed in Turtle. For an introduction to Turtle, see here.]

In the above example, SCoRO is used in combination with FaBiO, the FRBR-aligned Bibliographic Ontology, that provides structured vocabulary terms to characterize scholarly publications, and with FRAPO, the Funding, Research Administration and Projects Ontology, to be described in a subsequent post, that provides structured vocabulary terms to describe research administration, research funding, and the projects and investigations that such funding supports.

SCoRO also makes it easy to assert in a machine-readable manner that two authors on a paper, for example the first and second authors in an author list, have equal principal authorship roles, as shown in the following Turtle statements:

:author-1 pro:holdsRoleInTime :role1 .
:role1 
a pro:RoleInTime ;
   pro:withRole scoro:principal-author ;
   tvc:withinContext :ourJointPaper .

:author-2 pro:holdsRoleInTime :role2 .

:role2 
a pro:RoleInTime ;
   pro:withRole scoro:principal-author ;
   tvc:withinContext :ourJointPaper ;
   scoro:isEqualToRoleInTime :role1 .

:ourJointPaper a fabio:JournalArticle ;
   dcterms:creator :author-1 , author-2 .

In a similar manner, two contributions can be declared to be the same, using the property scoro:isEqualToContributionSituation to equate one scoro:ContributionSituation with another.

A fuller and more accurate graphical description of SCoRO, that shows the use of pro:RoleInTime and scoro:ContributionSituation to permit the inclusion of contextual information, is given in the following Graffoo diagram.

     Legend: Graffoo representation of the SCoRO ontology.

SCoRO is written in OWL 2 DL, and imports FOAF, the Friend of a Friend Ontology and PRO, the Publishing Roles Ontology. As with all SPAR Ontologies, we use content negotiation to handle the SCoRO URL http://purl.org/spar/scoro/, employing LODE, the Live OWL Documentation Environment, to deliver human-readable documentation of SCoRO if this URL is presented by a Web browser, or delivering the scoro.owl file if it is presented by an ontology editor such as Protégé.

As with any ontology. the existence of SCoRO is of little use on its own. People require an easy-to-use tool for the creation of SCoRO-specific metadata detailing the contributions and roles of people in relation to a particular research investigation and the publications arising from it. For this, we have created the SCoRF, the Scholarly Contributions Report Form, which makes entry of contributions and attribution metadata an easy task, as described in the next blog post.

Reference

[1]    Peroni S, Shotton D and Vitali F (2012). Describing roles and statuses and their temporal extents: a general pattern with applications in scholarly publishing. In Proceedings of the 8th International Conference on Semantic Systems (i-Semantics 2012): pages 9-16. http://dx.doi.org/10.1145/2362499.2362502.