OpenCitations Access Tokens: how they work and why they are important

Since its inauguration in 2010, OpenCitations has always granted free access to its services to users throughout the world, with no requirement for registration or sign-up. Programmatic access to OpenCitations data can be obtained either via our SPARQL endpoints and our REST APIs. In addition, OpenCitations data – available in CSV, Scholix, and RDF formats – can be downloaded from data dumps made periodically and stored on Figshare, so as to enable large-scale analyses using the whole content of the data sets, and also be obtained via our user-friendly text-based search and browsing interfaces.

One of OpenCitations’ priorities is (and will always be) to keep its data globally open and available at zero cost and without restriction for third-party analysis and re-use. As a matter of sustainability, OpenCitations relies on financial support from the scholarly community, which includes those institutions that use OpenCitations data. However, OpenCitations has not so far had in place a proper system to monitor its users, and the main evidence of the impact of OpenCitations in different academic fields and countries has been incompletely obtained from direct contacts with our members and donors across the world, our collaborations with international projects, and the interactions on our social platforms (Twitter and LinkedIn).

We would now like to institute a system that enables us to follow the usage and assess the impact of OpenCitations more reliably. For this purpose, we are now happy to announce the launch of the OpenCitations Access Token System for access to the OpenCitations data and services.

An OpenCitations Access Token is an opaque character string that anonymously identifies a unique user of the OpenCitations APIs. OpenCitations assigns an access token only if authorized to do so by each user, who can request a token by inserting his/her email address into the access form and clicking “Get token”. Upon submission of such a request, each user will automatically receive a personal access token by email. Users can save their personal access token and reuse it every time calling the APIs of OpenCitations, by passing it as a value for the key access-token in the header of each API call. 

Obtaining and using an OpenCitations Access Token is thus easy. It only requires a simple form request, and then the insertion of your personal token into the API call header when using OpenCitations REST APIs. OpenCitations will not store users’ email addresses or any personal information, so that the users’ privacy will be totally safeguarded. The token system just provides a simple mechanism for identifying unique users, for which the use of IP addresses is insufficient.

Obtaining an OpenCitations Access Token will take the user only a few seconds and needs to happen only once. You can request your OpenCitations Access Token here

https://opencitations.net/accesstoken 

Use of an OpenCitations Access Token is not compulsory. However, token use will help OpenCitations incredibly, by enabling us to monitor the number of the unique users accessing our data and services, providing objective anonymized evidence of the number of institutions and researchers accessing our data either occasionally or on a regular basis, which we can then employ to demonstrate the usefulness of OpenCitations in the research environment. While the token system will initially be employed just for API calls (the most used service we offer), it will subsequently be extended to our other forms of data access.

OpenCitations exists for the people that use its data for research purposes every day, and thanks to their support. This is why obtaining precise knowledge of how many researchers and institutions are accessing our services is essential to us, since it will enable us to present the uniqueness and value of OpenCitations to new communities of stakeholders, and thus to make it possible to enlarge the already enthusiastic and diverse group of people and institutions supporting and using our Open Science Infrastructure.

To summarize: Getting and using an OpenCitations Access Token is voluntary, easy, and does not cost you anything. However, it will help OpenCitations a great deal. Please get your own token now, and use it next time you access OpenCitations. Thank you very much!

Cite this article as: Chiara Di Giambattista, "OpenCitations Access Tokens: how they work and why they are important," in OpenCitations blog, 02/09/2022, https://opencitations.hypotheses.org/1535.

 

Coverage of open citation data approaches parity with Web of Science and Scopus

Guest blog post by Alberto Martín-Martín, Facultad de Comunicación y Documentación, Universidad de Granada, Spain <albertomartin@ugr.es>

In this post, as a contribution to Open Access Week, Alberto Martín-Martín shares his comparative analysis of COCI and other sources of open citation data with those from subscription services, and comments on their relative coverage.

Comprehensive bibliographic metadata is essential for the development of effective understanding and analysis across all phases of the research workflow. Commercial actors have historically filled the role of infrastructure providers of bibliographic and citation data, but their choice of subscription-based business models and/or restrictive user licenses has significantly limited how users and other parties can access, build upon, and redistribute the information available on those platforms. Locking bibliographic and citation metadata behind these barriers is problematic, as it hinders innovation and is an obstacle to reproducibility.

Fortunately, the process of digital transformation that scientific communication is currently undergoing is providing us with the tools to get closer to the ideal of science as a public good. One of the most successful initiatives in this area is Crossref, arguably the single most critical piece of research metadata infrastructure currently in existence. I consider the best thing about it to be its commitment to openness. Not only is Crossref responsible for minting many of the DOIs that are assigned to academic publications, but it also publishes metadata about these publications (for over 120+ million records in their latest public data file) without imposing any access or reuse limitations.

Crossref metadata has already boosted innovation in a variety of academic-oriented tools. New discovery services such as Dimensions, The Lens, and Scilit all take advantage of Crossref metadata to keep their indexes up to date with the latest publications. The open-source reference manager Zotero is able to pull metadata associated with a given DOI from Crossref’s servers, providing an easy way to populate one’s personal reference collection that is more reliable than using Google Scholar. The Unpaywall database uses Crossref metadata (among other data sources) to keep track of which documents are Open Access, and this data is in turn used by Unsub, a service that helps libraries make more informed decisions about their journal subscriptions.

Historically, citation indexing has been a functionality available only from a few subscription-based data sources (most notably Web of Science and Scopus), or from free but largely restricted sources (e.g., Google Scholar). In recent years, however, commercial exclusivity over citation data has been waning. Digital publishing workflows make it easier for publishers to deposit the list of cited references along with the rest of the metadata when they register a new document in Crossref, and many are already doing it. Crossref’s policy is to make these lists of references publicly available by default, although publishers can elect to prevent their public release. From this, it follows that if most publishers deposited their reference lists in Crossref and consented to make them open, a comprehensive open citation index, one that is free of the restrictions present in traditional platforms, could be built.

The Initiative for Open Citations (I4OC) is an advocacy group that has been working since 2017 to achieve this precise goal, and it has already managed to convince a large number publishers (over two thousand) to open the references they deposit in CrossRef. In the first half of 2021, Elsevier, the American Chemical Society, and Wolters Kluwer joined this group, so that today all the major scholarly publishers now support I4OC and have open references at Crossref, with the exception of IEEE (the Institute of Electrical and Electronics Engineers). Thanks to the efforts of I4OC and the collaboration of publishers, 88% of the publications for which publishers have deposited references in CrossRef are now open. This has allowed organizations such as OpenCitations (one of the founding members of I4OC) to create a non-proprietary citation index using these data, namely COCI, the OpenCitations Index of Crossref open DOI-to-DOI citations. Other open citation indexes such as the NIH Open Citation Collection (NIH-OCC) and Refcat have also been recently released.

How do such open citation indexes compare to long-established indexes? In 2019, I set out with colleagues to analyze the coverage of citations contained within the most widely used academic bibliographic data sources (Web of Science, Scopus, and Google Scholar) to a selected corpus of 2,515 highly-cited English-language documents published in 2006 from 252 subject categories, and to compare this to the coverage provided by some of the more recent data sources (Microsoft Academic, Dimensions, and COCI). At that time, COCI was the smallest of the six indexes, containing only 28% of all citations. For comparison, Web of Science contained 52%, and Scopus contained 57%.

There are a number of reasons for those differences: first, at that point some of the larger commercial publishers including Elsevier, IEEE, and ACS, which routinely deposit references in Crossref, had not yet opened them. Second, many smaller publishers still do not deposit their reference lists in Crossref. Third, COCI only captures citation relationships between documents that have DOIs, thus missing citations to publications that lack them. Finally, while for our study data collection from all sources was carried out during May/June of 2019, COCI at that time had not been updated since November 2018, which increased its disadvantage when compared to other data sources with more frequent updates.

Since Elsevier is the largest academic publisher in the world, its recent opening of references at Crossref resulted in a significant increase in the total number of openly available Crossref references. The most recent version of COCI (dated 3 September 2021, and based on open references to works with DOIs within the Crossref dump dated August 2021) now contains both the processed references from Elsevier, and the references in the most recently published articles by ACS (the complete backfile of ACS references will appear in future versions of COCI).

Given these significant developments, how much has the picture changed? To find this out, I updated our 2019 analysis using the version of COCI released on September 3rd 2021 and the NIH-OCC dataset released in the same month. To carry out a reasonably fair comparison while reusing the data extracted in 2019 from the other sources, I employed the same corpus of target documents, and only used citations in which the citing document was published before the end of June 2019. The intention was to learn how much the coverage of open citation data has grown as a result of the subsequent opening of reference lists in Crossref that were not public in 2019, and similar efforts.

The combination of COCI’s and NIH-OCC’s September 2021 releases contained more than 1.62 million citations to our sample corpus of documents from all areas, a 91% increase over the 0.85 million citations that we were able to recover in 2019 from COCI alone. Considering the citations available in all data sources, 53% of all citations are now available from these two open sources under CC0 waivers, up from the 28% we found in 2019. This coverage now surpasses the 52% found by Web of Science, and is much closer to the 54% found by Dimensions, and the 57% covered by Scopus. The relative overlap between COCI and the other data sources has also significantly increased: in 2019 COCI found 47% of the citations available in Web of Science, whereas now open citation data sources find 87% of the WoS citations. In the case of Scopus, in 2019 COCI found 44% of the citations available in Scopus: the percentage available from open sources has now increased to 81%. The number of citations found by COCI but not present in the other data sources has also widened slightly. These data are presented graphically in Figure 1.

Fig. 1. Percentage of citations found by each database, relative to all citations (first row), and relative to the number of citations found by the other databases (subsequent rows).

Where are these new citations coming from? Well, as we might expect, references from articles published in Elsevier journals comprise the lion’s share of the newly found citations in open data sources (close to half of all new citations), as shown in Figure 2. But there are also some IEEE citations here. This is because until recently reference lists from IEEE publications were available in the ‘limited’ Crossref category to members of Crossref Metadata Plus, a paid-for service that provides a few additional advantages over the free services Crossref provides. As a member of Crossref Metadata Plus, OpenCitations obtained these reference lists while they were available and included them in COCI. Subsequently, IEEE decided to make their references completely closed, explaining why references from more recent IEEE publications are not included in COCI.

Fig 2. The increases between 2019 and 2021 of citations indexed by open sources (COCI + NIH-OCC) from the articles of different publishers

There can be no doubt that open citation data is of benefit to the entire academic community. Thanks to COCI, NIH-OCC, and similar initiatives, and despite some setbacks, we are already witnessing how open infrastructure can help us develop models and practices that are better aligned with the opportunities that our current digital environment offers and the challenges that our society faces.

Conclusion: The coverage of citation data available under CC0 waivers from open sources is now comparable to that from subscription sources such as Web of Science and Scopus, offering a viable alternative upon which to base open and reproducible metrics of academic performance.

Cite this article as: davidshotton, "Coverage of open citation data approaches parity with Web of Science and Scopus," in OpenCitations blog, 27/10/2021, https://opencitations.hypotheses.org/1420.

Elsevier endorses DORA and opens its journal article reference lists

We congratulate and thank Elsevier, the world’s largest academic publisher, for endorsing the DORA Declaration on Research Assessment (https://sfdora.org/), thereby joining the hundreds of other publishers and scientific organizations which have endorsed DORA over the previous eight years, and also for making a commitment to open the references from all its journal articles submitted to Crossref. The text of Elsevier’s endorsement, dated 16th December 2020, is to be found at https://www.elsevier.com/connect/advancing-responsible-research-assessment, and includes the statement:

“We will make reference lists for all articles published in Elsevier journals openly available via Crossref so they can be available for reuse. This means other important initiatives like I4OC can draw on this metadata.”

Particular thanks are due to Kumsal Bayazit, Elsevier’s CEO, and to Andrew Plume, head of Elsevier’s International Center for the Study of Research (ICSR), for spearheading this change in stance on the part of Elsevier, which until this week has been alone among the major scholarly publishers in keeping its reference lists at Crossref closed, for which it has attracted much criticism from the academic community.

This change of heart on the part of Elsevier now means that by next spring, after Crossref has had a chance to implement this change in status over the large corpus of Elsevier journal metadata, the reference lists of articles in the vast majority of the world’s academic journals will be open, enabling such metadata to be used to enhance publication discovery and enable transparent research assessment.  The I4OC web site and COCI, OpenCitations Index of Crossref open DOI-to-DOI citations, will reflect this change once it has happened.

The Institute of Electrical and Electronics Engineers (IEEE), the American Chemical Society (ACS), and the University of Chicago Press now stand alone as the only significant scholarly publishers who choose not to make their publication reference lists open.

Cite this article as: davidshotton, "Elsevier endorses DORA and opens its journal article reference lists," in OpenCitations blog, 20/12/2020, https://opencitations.hypotheses.org/1165.

The Social Dilemma and open academic analytics

Last night I watched the Netflix documentary The Social Dilemma (https://www.netflix.com/title/81254224), in which former employees of the big Silicon Valley social media companies expose the serious and sometimes tragic or even fatal consequences that social media may have on individual lives. These social media services are run by commercial companies under pressure from shareholders to make ever increasing profits. In this situation, the ultimate consumers of these services becomes not the individuals using them, but the advertisers, and the users of these services (ourselves) become the commodities whose user profiles and personal preferences are sold by the social media companies to the advertisers for use in targetting adverts.

The Social Dilemma is a compelling documentary, since it is told by those who know (since they helped build and run the systems). It is particularly relevant to those who have pre-teen and teenage children, whose lives and personal interactions are increasingly being shaped and to a large extent controlled by social media, particularly during the current Covid-19 lock-downs. As recent events in the United States have highlighted, social media also pose fundamental issues around the definition of “facts” and “beliefs”, moving the debate from epistemology to politics and affecting the future of our societies.

From social media to academic analytics

Jason Priem’s self-portrait as a phrenology illustration.

From https://www.flickr.com/photos/26158205@N04/4307548673. (CC BY-SA 2.0)

Jason Priem is co-founder of ImpactStory, Depsy, UnPayWall and other open analytic and open science infrastructures and services (https://our-research.org/projectsthat deserve ongoing support from the academic community.

Academic analytics is the application of statistical, predictive modelling, data mining and artificial intelligence (AI) techniques to analyse, evaluate and summarize various types of organizational, educational and bibliographic data derived from higher educational and research institutions, in order to provide numerical results that can be used to guide strategic planning and decision-making practices in these contexts. It is increasingly used for student and faculty assessment, for deciding the allocation of funding, and for evaluating the standing and productivity both of individual academic departments and of entire universities.

Examples of such analyses include the degree of cross-institutional and international authorship of scholarly publications, and their citation counts excluding self-citations, used as indicators of the importance of research project outputs; the correlation of student grades with their interactions with university services such as libraries and virtual learning environments, used improve the learning performance of individual students; and the drop-out rates and degree distributions of different universities, employed to evaluate the quality of teaching. Those using such analyses include not only university administrators and individual academics, but also, in the case of learning analytics, increasingly the students themselves and their parents.

The relevance of The Social Dilemma to academic analytics is that these, like social media, are increasingly controlled by commercial companies under similar pressures to turn a profit. Here it is the universities and their academic data that become the consumed commodities, while the commercial suppliers of academic analytical services are the financial beneficiaries of these data.

There are, of course, differences between these two situations. While social media companies and academic analytics companies both have shareholders that expect profits and users to whom they provide services, the social media companies have advertisers that bring in revenue, while academic analytics companies get most of their revenue directly from the academic community itself. There is thus a relatively close connection between those who provide the raw data and those who pay for the analytical services built over these data. Since the academic community is both data provider and the one who pays the piper, this means that the social dilemma around research analytics should be easier to resolve than the social dilemma surrounding social media.

A further important difference is the following: while participation in social media is strictly voluntary, most of the academic community are evaluated through data analytics and AI without their express consent. Information on faculty members is being collected and used with little or no recourse for the individuals affected, since there are few, if any, rights to disclosure, rights to opt out of data analytics and AI-powered reviews and decisions, rights to review the data for errors, rights to correct errors, or rights to appeal decisions based on such analytics. Academic positions carry with them the expectation of academic freedom, the principles of which are hard to reconcile with the intense individual scrutiny built into the deployment of academic analytics and AI.

The dangers of commercial analytic platforms in academia

In May 2020, Amy Brand and Claudio Aspesi published their seminal article In pursuit of open science, open access is not enough (Science 368: 574-577. https://doi.org/10.1126/science.aba3763), in which they argued cogently about the dangers of commercial dominance of academic data analytics and knowledge infrastructures, and the need for open alternatives. Details of this growing commercial dominance of academic analytics, among other platforms and services, are given in the excellent analysis by Penny C. S. Andrews in her chapter The Platformization of Open (https://doi.org/10.7551/mitpress/11885.003.0027), in the book Reassembling Scholarly Communications: Histories, Infrastructures, and Global Politics of Open Access edited by Martin Paul Eve and Jonathan Gray (The MIT Press, 2020: https://doi.org/10.7551/mitpress/11885.001.0001).

Take, for example, the major university rankings, such as the Times Higher Education ranking. These rankings are extremely powerful. They rely on proprietary data, ironically to a significant extent made freely available to the producers of the rankings by universities, which are then used to define how the performance of universities should be assessed. Times Higher Education, for instance, presents its World University Rankings as “the definitive list of the top universities globally” (https://www.timeshighereducation.com/world-university-rankings). The performance criteria used by the Times Higher Education ranking, and a few other major university rankings, now play an important role in the decision-making processes of universities all over the world. However, because the underlying data are proprietary, it is hard to challenge the rankings or to use the data to provide alternative perspectives on university performance. It has become increasingly difficult for universities to develop strategic priorities that do not align with the performance criteria used by the major university rankings. For example, at one major European university, discussions about the development of an open science strategy explicitly take into account the possible negative effects of open science practices on its position in the major university rankings.

Application of the message of The Social Dilemma to the realm of scholarly information shows how the rise of commercially controlled academic analytics might fundamentally threaten academic freedom and access to truth itself. As Penny Andrews points out, several of the big players in academic publishing and scholarly communication are now building suites of products based around scholarly data and analytics, whose platforms rarely have open and transparent governance, and are encouraging universities to subscribe to such suites, sometimes in deals that, in the name of open science, bundle access to the institution’s scholarly data and provision of analytics based upon them with open access publication of that institution’s scholarly outputs, as, for example, in the Dutch Universities’ recent deal with Elsevier (https://tinyurl.com/y5v7ua7u). By gaining proprietorial control of such data, and by providing the default means of information transfer and workflows between a university’s administrative CRIS systems, academic libraries and individual researchers, such commercial companies lock universities and national consortia into non-interoperable situations in which their academic data, whether relating to their own standing, to the sources and distribution of their external research funding, or to the publication records and relative academic merits of their faculty members, are no longer fully under their own control.

The issues posed by the commercial deployment of data analytics are clearly compounded when these services are performed by companies which conduct other business with the academic community. A researcher who is faced with the question of where to publish her next article can be forgiven for deciding that, at the margin, it cannot hurt to submit it to a journal owned by the company tasked with assessing her research performance. There is a massive conflict of interest when companies that derive significant parts of their profits from publishing research also assess it and offer guidance on what projects should be funded next.

The urgent need for open community-governed infrastructures

For the reasons discussed above, the present situation in academia is dire. The academic community should take control of the data analytics infrastructures it uses, which need to be kept open, with transparent governance, to ensure the healthy functioning of the academic community. While the existing scholarly publishing infrastructure is well-established and hard to change quickly, the use of data analytics and AI in academia is still nascent and in flux. Hence it should be relatively easy to prevent ceding complete control of these activities to commercial vendors, who, of course, are merely doing what they exist to do, namely to maximize profits for their owners and shareholders.

Resolving this situation is within the grasp of the academic community, and its clear responsibility, although this will not be without difficulties. It may be much easier for a university administrator to authorize payment for a subscription to academic analytical services from a commercial supplier “that knows what it is doing” than it is to collaborate with colleagues from other academic institutions – often seen as competitors – to develop or fund alternative services that are independent, open and transparently managed, with all the implications that has in terms of the creation of salaried posts, recruitment or retraining of staff, premises, administration, etc. However now is the time to act, even during the current pandemic-induced economic recession, before commercial lock-in becomes a reality. Given the huge sums that universities already spend on subscription services of various types, it is clear that the primary problem is not the redeployment of existing financial resources, but is more fundamentally philosophical: whether or not academia wishes to be in control of its own data, or beholden to commercial interests. The development of community-controlled platforms providing open academic analytical services should now be made a priority, and appropriate sustained financial support for these platforms should be provided by the academic community, including governmental and charitable funders of research.

This week’s online OPERA conference “The Future of Open Research Analytics” (18-19 November 2020; https://deffopera.dk/opera-conference-november-2020/), hosted by the Danish OPERA Project (https://deffopera.dk/), provides a timely forum in which to discuss these issues. 

I would like to acknowledge and thank Ludo Waltman and Claudio Aspesi for reviewing drafts of this blog post, and for their important and insightful suggestions for its improvement and expansion, which I have incorporated with their permission.

Cite this article as: davidshotton, "The Social Dilemma and open academic analytics," in OpenCitations blog, 16/11/2020, https://opencitations.hypotheses.org/1151.
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