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    <title>Evaluating the impact of open access policies on research institutions</title>
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      <article itemscope="" itemtype="http://schema.org/Article" data-itemscope="root">
        <h1 itemprop="headline">Evaluating the impact of open access policies on research
          institutions</h1>
        <meta itemprop="image"
          content="https://via.placeholder.com/1200x714/dbdbdb/4a4a4a.png?text=Evaluating%20the%20impact%20of%20open%20access%20policies%20on%20research%20institutions">
        <ol data-itemprop="authors">
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Chun-Kai (Karl) Huang"><span
              data-itemprop="givenNames"><span itemprop="givenName">Chun-Kai</span><span
                itemprop="givenName">(Karl)</span></span><span data-itemprop="familyNames"><span
                itemprop="familyName">Huang</span></span><span data-itemprop="emails"><a
                itemprop="email"
                href="mailto:karl.huang@curtin.edu.au">karl.huang@curtin.edu.au</a></span><span
              data-itemprop="affiliations"><a itemprop="affiliation"
                href="#author-organization-1">1</a></span>
          </li>
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Cameron Neylon"><span data-itemprop="givenNames"><span
                itemprop="givenName">Cameron</span></span><span data-itemprop="familyNames"><span
                itemprop="familyName">Neylon</span></span><span data-itemprop="affiliations"><a
                itemprop="affiliation" href="#author-organization-1">1</a><a itemprop="affiliation"
                href="#author-organization-2">2</a></span>
          </li>
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Richard Hosking"><span data-itemprop="givenNames"><span
                itemprop="givenName">Richard</span></span><span data-itemprop="familyNames"><span
                itemprop="familyName">Hosking</span></span><span data-itemprop="affiliations"><a
                itemprop="affiliation" href="#author-organization-2">2</a></span>
          </li>
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Lucy Montgomery"><span data-itemprop="givenNames"><span
                itemprop="givenName">Lucy</span></span><span data-itemprop="familyNames"><span
                itemprop="familyName">Montgomery</span></span><span data-itemprop="affiliations"><a
                itemprop="affiliation" href="#author-organization-1">1</a><a itemprop="affiliation"
                href="#author-organization-2">2</a></span>
          </li>
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Katie S Wilson"><span data-itemprop="givenNames"><span
                itemprop="givenName">Katie</span><span itemprop="givenName">S</span></span><span
              data-itemprop="familyNames"><span itemprop="familyName">Wilson</span></span><span
              data-itemprop="affiliations"><a itemprop="affiliation"
                href="#author-organization-1">1</a></span>
          </li>
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Alkim Ozaygen"><span data-itemprop="givenNames"><span
                itemprop="givenName">Alkim</span></span><span data-itemprop="familyNames"><span
                itemprop="familyName">Ozaygen</span></span><span data-itemprop="affiliations"><a
                itemprop="affiliation" href="#author-organization-1">1</a></span>
          </li>
          <li itemscope="" itemtype="http://schema.org/Person" itemprop="author">
            <meta itemprop="name" content="Chloe Brookes-Kenworthy"><span
              data-itemprop="givenNames"><span itemprop="givenName">Chloe</span></span><span
              data-itemprop="familyNames"><span
                itemprop="familyName">Brookes-Kenworthy</span></span><span
              data-itemprop="affiliations"><a itemprop="affiliation"
                href="#author-organization-1">1</a></span>
          </li>
        </ol>
        <ol data-itemprop="affiliations">
          <li itemscope="" itemtype="http://schema.org/Organization" itemid="#author-organization-1"
            id="author-organization-1"><span itemprop="name">Centre for Culture and Technology,
              School of Media, Creative Arts and Social Inquiry, Curtin University</span>
            <address itemscope="" itemtype="http://schema.org/PostalAddress" itemprop="address">
              <span itemprop="addressLocality">Perth</span><span
                itemprop="addressCountry">Australia</span></address>
          </li>
          <li itemscope="" itemtype="http://schema.org/Organization" itemid="#author-organization-2"
            id="author-organization-2"><span itemprop="name">Curtin Institute for Computation,
              Curtin University</span>
            <address itemscope="" itemtype="http://schema.org/PostalAddress" itemprop="address">
              <span itemprop="addressLocality">Perth</span><span
                itemprop="addressCountry">Australia</span></address>
          </li>
        </ol><span itemscope="" itemtype="http://schema.org/Organization" itemprop="publisher">
          <meta itemprop="name" content="Unknown"><span itemscope=""
            itemtype="http://schema.org/ImageObject" itemprop="logo">
            <meta itemprop="url"
              content="https://via.placeholder.com/600x60/dbdbdb/4a4a4a.png?text=Unknown">
          </span>
        </span><time itemprop="datePublished" datetime="2020-09-14">2020-09-14</time>
        <ul data-itemprop="genre">
          <li itemprop="genre">Feature Article</li>
        </ul>
        <ul data-itemprop="keywords">
          <li itemprop="keywords">open access</li>
          <li itemprop="keywords">meta-research</li>
          <li itemprop="keywords">research policy</li>
          <li itemprop="keywords">universities</li>
          <li itemprop="keywords">scholarly publishing</li>
          <li itemprop="keywords">repositories</li>
          <li itemprop="keywords">None</li>
        </ul>
        <ul data-itemprop="identifiers">
          <li itemscope="" itemtype="http://schema.org/PropertyValue" itemprop="identifier">
            <meta itemprop="propertyID"
              content="https://registry.identifiers.org/registry/publisher-id"><span
              itemprop="name">publisher-id</span><span itemprop="value"
              data-itemtype="http://schema.org/Number">57067</span>
          </li>
          <li itemscope="" itemtype="http://schema.org/PropertyValue" itemprop="identifier">
            <meta itemprop="propertyID" content="https://registry.identifiers.org/registry/doi">
            <span itemprop="name">doi</span><span itemprop="value">10.7554/eLife.57067</span>
          </li>
          <li itemscope="" itemtype="http://schema.org/PropertyValue" itemprop="identifier">
            <meta itemprop="propertyID"
              content="https://registry.identifiers.org/registry/elocation-id"><span
              itemprop="name">elocation-id</span><span itemprop="value">e57067</span>
          </li>
        </ul>
        <section data-itemprop="description">
          <h2 data-itemtype="http://schema.stenci.la/Heading">Abstract</h2>
          <meta itemprop="description"
            content="The proportion of research outputs published in open access journals or made available on other freely-accessible platforms has increased over the past two decades, driven largely by funder mandates, institutional policies, grass-roots advocacy, and changing attitudes in the research community. However, the relative effectiveness of these different interventions has remained largely unexplored. Here we present a robust, transparent and updateable method for analysing how these interventions affect the open access performance of individual institutes. We studied 1,207 institutions from across the world, and found that, in 2017, the top-performing universities published around 80–90% of their research open access. The analysis also showed that publisher-mediated (gold) open access was popular in Latin American and African universities, whereas the growth of open access in Europe and North America has mostly been driven by repositories.">
          <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The proportion of research
            outputs published in open access journals or made available on other freely-accessible
            platforms has increased over the past two decades, driven largely by funder mandates,
            institutional policies, grass-roots advocacy, and changing attitudes in the research
            community. However, the relative effectiveness of these different interventions has
            remained largely unexplored. Here we present a robust, transparent and updateable method
            for analysing how these interventions affect the open access performance of individual
            institutes. We studied 1,207 institutions from across the world, and found that, in
            2017, the top-performing universities published around 80–90% of their research open
            access. The analysis also showed that publisher-mediated (gold) open access was popular
            in Latin American and African universities, whereas the growth of open access in Europe
            and North America has mostly been driven by repositories.</p>
        </section>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="introduction">Introduction
        </h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">While there is substantial
          disagreement on the best route to achieve open access, the idea that research outputs
          should be freely available is broadly shared. Over the past decade, there has been a large
          increase in the volume of publications available open access (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib19">Piwowar et al.,
              2018</a></cite>), and this looks set to continue: indeed, a recent projection
          estimates that by 2025, 44% of all journal articles will be available as open access (OA)
          and that 70% of article views will be to OA articles (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib20">Piwowar et al.,
              2019</a></cite>).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">This massive increase has
          largely been driven by policy initiatives. Medical research funders in the UK, such as the
          Wellcome Trust and Medical Research Council, and the National Institutes of Health in the
          US have led a wide range of funder policy interventions. Universities such as Harvard
          University, University of Liège, University of Southampton and others developed local
          polices and infrastructures that became more widely adopted. In 2018, a <a
            href="https://www.coalition-s.org/" itemscope=""
            itemtype="http://schema.stenci.la/Link">coalition of funders</a> set out an initiative
          called Plan S that requires all scholarly publications funded by public grants to be made
          immediately open access. This is the most ambitious, and therefore the most controversial,
          policy initiative to date with questions raised about the approach (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib21">Rabesandratana,
              2019</a></cite>; <cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib7">Haug, 2019</a></cite>; <cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib3">Barbour and Nicholls,
              2019</a></cite>), implementation details (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib15">McNutt, 2019</a></cite>; <cite
            itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib6">Gómez-Fernández,
              2019</a></cite>; <cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib4">Brainard, 2019</a></cite>; <cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib2">Agustini and Berk,
              2019</a></cite>), and unintended side effects for existing programs outside North
          America and North-western Europe (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib5">Debat and Babini,
              2019</a></cite>; <cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib1">Aguado-López and Becerril-García, 2019</a></cite>).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">A recent report showed a link
          between the monitoring of policy and its effectiveness, demonstrating that research
          outputs supported by funders that implemented monitoring and compliance checks for their
          policies were more likely to be published open access (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib13">Larivière and Sugimoto,
              2018</a></cite>). By comparison, open access for works funded by Canadian funders,
          which did not monitor compliance, were shown to lag substantially even when disciplinary
          effects were taken into account.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">There is a need for critical
          and inclusive evaluation of open access performance that can address regional and
          political differences. For example, the <a href="https://en.wikipedia.org/wiki/SciELO"
            itemscope="" itemtype="http://schema.stenci.la/Link">SciELO</a> project has successfully
          implemented an electronic publishing model for journals resulting in a surge of
          publisher-mediated open access (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib18">Packer, 2009</a></cite>; <cite
            itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib27">Wang et al.,
              2018</a></cite>). Recent work showed that, for biomedical research, there was a
          greater level of open access for articles published from countries with a lower GDP,
          particularly for those in sub-Saharan Africa (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib12">Iyandemye and Thomas,
              2019</a></cite>). This provides evidence of national or regional effects on
          publication cultures that lead to open access. Meanwhile, another study showed that, for
          the field of Global Health, lower-ranked institutions are more likely to publish in closed
          outlets (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib24">Siler
              et al., 2018</a></cite>). They suggest this is due to the cost of article processing
          charges showing the importance of considering institutional context when examining open
          access performance.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Despite the scale and success
          (at least in some areas) of policy interventions, there is limited comparative and
          quantitative research about which policy interventions have been the most successful. In
          part this is due to a historical lack of high-quality data on open access, the
          heterogeneous nature of the global scholarly publishing endeavour, and the consequent lack
          of any baseline against which to make comparisons.</p>
        <h3 itemscope="" itemtype="http://schema.stenci.la/Heading" id="aim-of-study">Aim of Study
        </h3>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We have argued (<cite
            itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib17">Montgomery et al.,
              2018</a></cite>) that the key to understanding and guiding the cultural changes that
          underpin a transition to openness is analysis at the level of research institutions. While
          funders, national governments, and research communities create the environments in which
          researchers operate, it is within their professional spaces that choices around
          communication, and their links to career progression and job security are strongest.
          Analysis of how external policy leads to change at the level of universities is critical.
          However, providing accurate and reliable data on open access at the university level is a
          challenge.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The most comprehensive work on
          open access at the university level currently available is that included in the CWTS
          Leiden Ranking (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib22">Robinson-Garcia et al., 2019</a></cite>; <cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib23">Robinson-Garcia et al.,
              2020</a></cite>). This utilises an internal Web of Science database and data from <a
            href="https://unpaywall.org/" itemscope=""
            itemtype="http://schema.stenci.la/Link">Unpaywall</a> to provide estimates of open
          access over a range of timeframes. These data have highlighted the broad effects of funder
          policies (notably the performance of UK universities in response to national policies)
          while also providing standout examples from regions that are less expected (for instance
          Bilkent University in Turkey).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">A concern in any university
          evaluation is the existing disciplinary bias in large bibliographic sources used to
          support rankings. For example, the coverages of Web of Science and Scopus were shown to be
          biased toward the sciences and the English language (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib16">Mongeon and Paul-Hus,
              2016</a></cite>). If we are to make valid comparisons of universities across
          countries, regions and funders to examine the effectiveness of open access policy
          implementation there is a critical need for evaluation frameworks that provide fair,
          inclusive and relevant measurement of open access performance.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Alongside coverage of data
          sources are issues of scope (which institutions, what set of objects), metrics (numbers or
          proportions) and data completeness. Our pragmatic assessment is that any evaluation
          framework should be tied to explicit policy goals and be shaped to deliver that. Following
          from our work on open knowledge institutions (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib17">Montgomery et al.,
              2018</a></cite>) our goals in conducting an evaluation exercise and developing the
          framework are as follows: (i) Maximise the amount of research content that is accessible
          to the widest range of users, focusing on existing formal research content for which
          metadata quality is sufficiently high to enable analysis; (ii) Develop an evaluation
          framework that drives an elevation of open access and open science issues to a strategic
          issue for all research-intensive universities; (iii) Develop a framework that is sensitive
          to and can support universities taking a range of approaches and routes towards delivering
          on these goals.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In terms of a pragmatic
          approach to delivering these goals we intend to:</p>
        <ol itemscope="" itemtype="http://schema.org/ItemList">
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="1">
            <meta itemprop="url" content="#1">Focus on research-intensive institutions, using
            existing rankings as a sample set.
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="2">
            <meta itemprop="url" content="#2">Seek to maximise the set of objects which we can
            collect and track while connecting them to institutions (i.e., increase recall but not
            at the expense of precision).
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="3">
            <meta itemprop="url" content="#3">Focus on proportions of open access as a performance
            indicator rather than absolute numbers.
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="4">
            <meta itemprop="url" content="#4">Publicly report on the details of performance for high
            performing institutions (and provide strategic data on request to others).
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="5">
            <meta itemprop="url" content="#5">Report on the diversity of paths being taken to
            deliver overall access by a diverse group of universities.
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="6">
            <meta itemprop="url" content="#6">Develop methodology that is capable of identifying
            which policy interventions have made a difference to outcome measures and any
            ‘signature’ of those effects.
          </li>
        </ol>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">With the above in mind, this
          study proposes a set of requirements for evaluating open access performance at the
          institutional level, and presents a large-scale analysis of universities by drawing and
          integrating data from multiple data sources. This work differs from the CWTS Leiden
          Rankings by extending the coverage of research outputs beyond the Web of Science. The data
          workflow we have developed is also transparent, reproducible, and updateable, which makes
          robust and longitudinal analysis more easily attainable. We emphasise that a simple
          numerical ranking of universities cannot be justified given there is minimal significant
          difference across them. Instead, we highlight how the resulting comprehensive overview of
          the open access landscape and the underlying trends over time can provide deep insights on
          effects of policy interventions.</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="methods">Methods</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">To map the rate and degree of
          progress to open access, we developed a reproducible workflow capable of quantifying a
          wide range of open access characteristics at the institutional level. The overall workflow
          is summarised diagrammatically in <a href="#fig1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 1</a>. This includes mapping open access
          definitions and the Unpaywall information we used to construct them. Briefly, we gather
          output metadata from searches in <a
            href="https://www.microsoft.com/en-us/research/project/academic/" itemscope=""
            itemtype="http://schema.stenci.la/Link">Microsoft Academic</a> (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib25">Sinha et al., 2015</a></cite>;
          <cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib28">Wang et al.,
              2019</a></cite>), Web of Science and Scopus, for each university. From this full set
          we gather the corresponding Crossref DOIs from the metadata of each output focusing on
          this set. Unpaywall is consulted to determine open access status. Detailed discussions of
          the data sources, precise data snapshots used, and technical details of the data
          infrastructure can be found in <a href="#supp1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>. The code used in the
          workflow is available via Zenodo at the following <a
            href="https://doi.org/10.5281/zenodo.3693221" itemscope=""
            itemtype="http://schema.stenci.la/Link">link</a>.</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig1" title="Figure 1">
          <label data-itemprop="label">Figure 1</label><img src="index.html.media/fig1.jpg"
            alt="fig1" itemscope="" itemtype="http://schema.org/ImageObject">
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading" id="analysis-workflow">
              Analysis workflow.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Diagrammatic summary of how
              data is collected and mapped against open access definitions using information from
              Unpaywall metadata.</p>
          </figcaption>
        </figure>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We have decided to focus mainly
          on total open access, publisher-mediated open access (i.e., gold), and repository-mediated
          open access (i.e., green) due to the ease of comprehension, data quality, and ability to
          show potential effects of selected policies (<a href="#table1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Table 1</a>). Levels of hybrid open access and
          green in home repository for selected universities (ones for which we have more confidence
          in the data) are also included to further support the analysis of policy effects.</p>
        <table id="table1" itemscope="" itemtype="http://schema.org/Table">
          <caption><label data-itemprop="label">Table 1</label>
            <div itemprop="caption">
              <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
                id="definitions-of-open-access">Definitions of open access.</h4>
              <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Summary of different
                types of open access (OA) used in scholarly publishing. These definitions are not
                always mutually exclusive. For example, an article can be both Gold OA and Green OA.
                However, articles that are Green Only do not have any common element with articles
                classified as Gold OA by definition. This study focuses on the following categories:
                Total OA, Gold, Hybrid, Green and Green in Home Repo. Further discussions on open
                access definitions can be found in <a href="#supp1" itemscope=""
                  itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>.</p>
            </div>
          </caption>
          <thead>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <th itemscope="" itemtype="http://schema.stenci.la/TableCell">OA type</th>
              <th itemscope="" itemtype="http://schema.stenci.la/TableCell">Description</th>
            </tr>
          </thead>
          <tbody>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Total OA</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is free to read online, either via the publisher website or in an OA repository.
              </td>
            </tr>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Gold</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is either published in a journal listed by the Directory of Open Access Journals
                (DOAJ), or (if journal not in DOAJ) is free to read via publisher with any license.
              </td>
            </tr>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Hybrid</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is published in a journal not listed by DOAJ, but is free to read from publisher
                with any license.</td>
            </tr>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Bronze</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is free to read online via publisher without a license.</td>
            </tr>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Green</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is free to read online via an OA repository.</td>
            </tr>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Green Only</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is free to read online via an OA repository, but is not available for free via the
                publisher.</td>
            </tr>
            <tr itemscope="" itemtype="http://schema.stenci.la/TableRow">
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">Green in Home Repo</td>
              <td itemscope="" itemtype="http://schema.stenci.la/TableCell">A research output that
                is free to read online via the matched affiliation’s institutional repository.</td>
            </tr>
          </tbody>
        </table>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">As we have noted previously
          (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib8">Huang et al.,
              2020</a></cite>), there is a sensitivity associated to the choices in bibliographic
          data sources when they are used to create a ranking. For this analysis we therefore chose
          to combine all three datasets: Microsoft Academic, Web of Science and Scopus. In the
          companion white paper (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib9">Huang et al., 2020</a></cite>) we provide a comprehensive sensitivity
          analysis on the use of these different datasets, the use of different versions of
          Unpaywall, and the relations between confidence levels and sample size.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Briefly, it is our view that to
          provide a robust assessment of open access performance the following set of essential
          requirements must be met:</p>
        <ol itemscope="" itemtype="http://schema.org/ItemList">
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="1">
            <meta itemprop="url" content="#1">The set of outputs included in each category and a
            traceable description of how they were collected must be transparently described.
            Provided here by a description of the data sources and the procedures used to collect
            DOIs for each institution (<a href="#supp1" itemscope=""
              itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>). In this article,
            institutions define the categories of outputs but they could also be categorised by
            individuals, disciplines, or countries etc.
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="2">
            <meta itemprop="url" content="#2">A clearly defined, open and auditable data source on
            open access status. Provided here by a defined and identified Unpaywall snapshot (<a
              href="#supp1" itemscope="" itemtype="http://schema.stenci.la/Link">Supplementary file
              1</a>).
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="3">
            <meta itemprop="url" content="#3">A clearly defined and implementable description of how
            open access status data is interpreted in the form of the SQL query used to establish
            open access status categories for each DOI (<a href="#fig1" itemscope=""
              itemtype="http://schema.stenci.la/Link">Figure 1</a> and <a href="#supp1" itemscope=""
              itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>). We decided to
            include the checkmark &#39;is_oa = TRUE’ in the description of Bronze open access as
            this makes a slight difference to the numbers obtained from Unpaywall.
          </li>
          <li itemscope="" itemtype="http://schema.org/ListItem" itemprop="itemListElement">
            <meta itemprop="position" content="4">
            <meta itemprop="url" content="#4">Provision of derived data and analysis in auditable
            form. Provided here the derived data as open data (<cite itemscope=""
              itemtype="http://schema.stenci.la/Cite"><a href="#bib10">Huang et al.,
                2020</a></cite>), code for the analysis of derived data as Jupyter notebooks (<cite
              itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib11">Huang et al.,
                2020</a></cite>), and upstream data analysis in the form of SQL queries used (<cite
              itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib10">Huang et al.,
                2020</a></cite>).
          </li>
        </ol>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We have limited our data
          sharing in two ways. Firstly, we do not provide the full list of DOIs obtained from each
          source, due to Terms of Service restrictions. Secondly, we have not identified
          institutions individually except for those that fall within the top 100 globally for total
          open access, publisher-mediated open access, or repository-mediated open access. Both
          derived datasets of the de-anonymised top 100 and the full dataset containing all
          institutions in anonymised form are made available (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib10">Huang et al., 2020</a></cite>).
        </p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="results">Results</h2>
        <h3 itemscope="" itemtype="http://schema.stenci.la/Heading"
          id="global-universities-in-terms-of-total-open-access-gold-open-access-and-green-open-access">
          Global universities in terms of total open access, gold open access and green open access
        </h3>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In <a href="#fig2" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 2</a>, we present the open access
          performance of universities in different regions for the categories of total open access,
          publisher-mediated open access (‘gold’) and repository-mediated open access (‘green’) for
          publications assigned to the year 2017 (see <a href="#fig2s1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 2—figure supplement 1</a> for equivalent
          plots for 2016 and 2018). We have chosen to focus on 2017 as this is the most recent year
          for which we have the most confidence on the completeness of data, taking into
          consideration the data collection process and issues surrounding embargoes. However, we do
          observe consistent general patterns across results for all three years. The top 100
          institutions in each of the open access categories (for 2017) are also provided in <a
            href="#fig2s2" itemscope="" itemtype="http://schema.stenci.la/Link">Figure 2—figure
            supplement 2</a>. This is, to our knowledge, the first set of university rankings that
          provides a confidence interval on the quantitative variable being ranked and compensates
          for the multiple comparisons effect (see <a href="#supp1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Supplementary file 1</a> for details). Across
          this top 100, the statistical difference between universities at the 95% confidence shows
          that a simple numerical ranking cannot be justified.</p>
        <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
          data-execution_count="1" data-programminglanguage="python">
          <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
            slot="text"><code>import pandas as pd
import seaborn as sns
import warnings
import matplotlib.pyplot as plt
warnings.filterwarnings(&quot;ignore&quot;)
from analysis import charts
plt.style.use(&#39;seaborn-white&#39;)
sns.set_context(&#39;paper&#39;)
# Read version of data as published eLife article
full = pd.read_csv(&#39;institutional_oa_evaluation_2020_full_paper_dataset_2020_08_06.csv&#39;)
named = pd.read_csv(&#39;institutional_oa_evaluation_2020_named_unis_dataset_2020_08_06.csv&#39;)
## Helper functions ##

# Data cleanup required, mainly on country names #
def clean_geo_names(df):
    country_clean = { &quot;country&quot; : {
        &quot;United Kingdom of Great Britain and Northern Ireland&quot; : &quot;United Kingdom&quot;,
        &quot;Iran (Islamic Republic of)&quot; : &quot;Iran&quot;,
        &quot;Korea, Republic of&quot; : &quot;South Korea&quot;,
        &quot;Taiwan, Province of China&quot; : &quot;Taiwan&quot;
                              }
                    }
    df.replace(to_replace = country_clean, inplace=True)

    df.loc[df.country.isin([&#39;Canada&#39;, &#39;United States of America&#39;]), &#39;region&#39;] = &#39;North America&#39;
    df.replace(&#39;Americas&#39;, &#39;Latin America&#39;, inplace=True)
    return df

# Creating nice column names for graphing
def nice_column_names(df):
    cols = [
        (&#39;Open Access (%)&#39;, &#39;percent_oa&#39;),
        (&#39;Total Green OA (%)&#39;, &#39;percent_green&#39;),
        (&#39;Total Gold OA (%)&#39;, &#39;percent_gold&#39;),
        (&#39;Green Only OA (%)&#39;, &#39;percent_green_only&#39;),
        (&#39;Green in Institutional Repository (%)&#39;, &#39;percent_in_home_repo&#39;),
        (&#39;Hybrid OA (%)&#39;, &#39;percent_hybrid&#39;),
        (&#39;Total Publications&#39;, &#39;total&#39;),
        (&#39;Change in Open Access (%)&#39;, &#39;total_oa_pc_change&#39;),
        (&#39;Change in Green OA (%)&#39;, &#39;green_pc_change&#39;),
        (&#39;Change in Gold OA (%)&#39;, &#39;gold_pc_change&#39;),
        (&#39;Change in Total Publications (%)&#39;, &#39;total_pc_change&#39;),        
        (&#39;Year of Publication&#39;, &#39;published_year&#39;),
        (&#39;University Name&#39;, &#39;name&#39;),
        (&#39;Region&#39;, &#39;region&#39;),
        (&#39;Country&#39;, &#39;country&#39;),
            ]
    for col in cols:
        if col[1] in df.columns.values:
            df[col[0]] = df[col[1]]

    return df

# Function for creating percent_changes year on year
def calculate_pc_change(df, columns, 
              id_column=&#39;grid_id&#39;, 
              year_column=&#39;published_year&#39;,
              column_name_add=&#39;_pc_change&#39;):
    df = df.sort_values(year_column, ascending=True)
    for column in columns:
        new_column_name = column + column_name_add
        df[new_column_name] = list(df.groupby(id_column)[column].pct_change()*100)   
    return df

# Function for calculating confidence intervals
def calculate_confidence_interval(df, columns,
                                  total_column=&#39;total&#39;,
                                  column_name_add=&#39;_err&#39;):
    for column in columns:
        new_column_name = column + column_name_add
        df[new_column_name] = 100*3.43*(
                                            df[column] / 100 *
                                                   (
                                                    1 - df[column] / 100
                                                   ) /
                                            df[total_column]
                                                )**(.5)
    return df
# Do the data cleanup and a few calculations for graphing
clean_geo_names(full)
clean_geo_names(named)
full = calculate_confidence_interval(full,
                                 [&#39;percent_gold&#39;, 
                                  &#39;percent_green&#39;, 
                                  &#39;percent_oa&#39;])
named = calculate_pc_change(named, 
              [&#39;gold&#39;, 
               &#39;green&#39;, 
               &#39;total_oa&#39;, 
               &#39;total&#39;])
named = calculate_confidence_interval(named,
                                 [&#39;percent_gold&#39;, 
                                  &#39;percent_green&#39;, 
                                  &#39;percent_oa&#39;])
full = nice_column_names(full)
named = nice_column_names(named)
full_all = full # Reserve unfiltered full data for Figure 2 Supp 3

# Filter data by selected confidence level/margin of error and conditions of estimation
full = full[(full.percent_green_err&lt;17)&amp;
                            (full.total*full.percent_green/100&gt;5)&amp;
                              ((full.total*(1-full.percent_green/100)&gt;5))&amp;
                              (full.percent_gold_err&lt;17)&amp;
                              (full.total*full.percent_gold/100&gt;5)&amp;
                              ((full.total*(1-full.percent_gold/100)&gt;5))&amp;
                              (full.percent_oa_err&lt;17)&amp;
                              (full.total*full.percent_oa/100&gt;5)&amp;
                              ((full.total*(1-full.percent_oa/100)&gt;5))]</code></pre>
        </stencila-code-chunk>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig2" title="Figure 2">
          <label data-itemprop="label">Figure 2</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="9" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>sns.set_context(&quot;paper&quot;,rc={&quot;legend.fontsize&quot;:14,&quot;axes.labelsize&quot;:14},font_scale=1.75)
figures2 = charts.BoxScatter(full, 2017, &#39;region&#39;, [&#39;Open Access (%)&#39;,
                                                         &#39;Total Gold OA (%)&#39;,
                                                         &#39;Total Green OA (%)&#39;])
figures2.process_data()
figures2.plot(figsize=(15,5));</code></pre>
            <figure slot="outputs"><img src="index.html.media/3c8ea006971d0485237d912f318ddeb6.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="open-access-performance-of-different-geographical-regions">Open access performance
              of different geographical regions.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Percentages of
              institutional Total OA, Gold OA and Green OA (left to right) grouped by regions for
              2017. Parallel figures for 2016 and 2018 are provided in <a href="#fig2s1"
                itemscope="" itemtype="http://schema.stenci.la/Link">Figure 2—figure supplement
                1</a>.</p>
          </figcaption>
        </figure>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig2s1"
          title="Figure 2 - figure supplement 1"><label data-itemprop="label">Figure 2 - figure
            supplement 1</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="14" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>sns.set_context(&quot;paper&quot;,rc={&quot;legend.fontsize&quot;:14,&quot;axes.labelsize&quot;:14},font_scale=1.75)
figures2supp1a = charts.BoxScatter(full, 2016, &#39;region&#39;, [&#39;Open Access (%)&#39;,
                                                         &#39;Total Gold OA (%)&#39;,
                                                         &#39;Total Green OA (%)&#39;])
figures2supp1a.process_data()
figures2supp1b = charts.BoxScatter(full, 2018, &#39;region&#39;, [&#39;Open Access (%)&#39;,
                                                         &#39;Total Gold OA (%)&#39;,
                                                         &#39;Total Green OA (%)&#39;])
figures2supp1b.process_data()
figures2supp1a.plot(figsize=(15,5));
figures2supp1b.plot(figsize=(15,5));</code></pre>
            <figure slot="outputs"><img src="index.html.media/00918a75b64c1034390337d5b4dc4061.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"><img
                src="index.html.media/ba3c933e4c321214cdae916a094f81b3.png" alt="" itemscope=""
                itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="open-access-performance-of-different-regions-in-2016-and-2018">Open access
              performance of different regions in 2016 and 2018.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Percentages of
              institutional Total OA, Gold OA and Green OA (left to right) grouped by regions for
              2016 and 2018, respectively.</p>
          </figcaption>
        </figure>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig2s2"
          title="Figure 2 - figure supplement 2"><label data-itemprop="label">Figure 2 - figure
            supplement 2</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="15" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>sns.set_context(&quot;paper&quot;,rc={&quot;legend.fontsize&quot;:10,&quot;axes.labelsize&quot;:10},font_scale=1)
#from matplotlib.patches import Patch
from matplotlib.lines import Line2D
legend_elements = [Line2D([0], [0], color=&#39;orange&#39;, lw=8, label=&#39;Asia&#39;),
                   Line2D([0], [0], color=&#39;limegreen&#39;, lw=8, label=&#39;Europe&#39;),
                   Line2D([0], [0], color=&#39;dodgerblue&#39;, lw=8, label=&#39;North America&#39;),
                   Line2D([0], [0], color=&#39;brown&#39;, lw=8, label=&#39;Latin America&#39;),
                   Line2D([0], [0], color=&#39;magenta&#39;, lw=8, label=&#39;Africa&#39;),
                   Line2D([0], [0], color=&#39;red&#39;, lw=8, label=&#39;Oceania&#39;)]
# Create the figure
fig, ax = plt.subplots(figsize=(16,0.7))
ax.legend(handles=legend_elements, loc=&#39;lower center&#39;, frameon=True, ncol=6)
plt.axis(&#39;off&#39;)
plt.show()
params = [
            {
            &#39;chart_class&#39;: charts.ConfidenceIntervalRank,
            &#39;rankcol&#39;: &#39;Open Access (%)&#39;,
            &#39;errorcol&#39;: &#39;percent_oa_err&#39;,
            &#39;filter_name&#39;: &#39;published_year&#39;,
            &#39;filter_value&#39;: 2017
            },
            {
            &#39;chart_class&#39;: charts.ConfidenceIntervalRank,
            &#39;rankcol&#39;: &#39;Total Gold OA (%)&#39;,
            &#39;errorcol&#39;: &#39;percent_gold_err&#39;,
            &#39;filter_name&#39;: &#39;published_year&#39;,
            &#39;filter_value&#39;: 2017
            },
            {
            &#39;chart_class&#39;: charts.ConfidenceIntervalRank,
            &#39;rankcol&#39;: &#39;Total Green OA (%)&#39;,
            &#39;errorcol&#39;: &#39;percent_green_err&#39;,
            &#39;filter_name&#39;: &#39;published_year&#39;,
            &#39;filter_value&#39;: 2017
            }
]
# Filter data by selected confidence level/margin of error and conditions of estimation
figdata = named[(named.percent_green_err&lt;17)&amp;
                              (named.total*named.percent_green/100&gt;5)&amp;
                              ((named.total*(1-named.percent_green/100)&gt;5))&amp;
                              (named.percent_gold_err&lt;17)&amp;
                              (named.total*named.percent_gold/100&gt;5)&amp;
                              ((named.total*(1-named.percent_gold/100)&gt;5))&amp;
                              (named.percent_oa_err&lt;17)&amp;
                              (named.total*named.percent_oa/100&gt;5)&amp;
                              ((named.total*(1-named.percent_oa/100)&gt;5))]
figure2supp2 = charts.Layout(figdata, params)
figure2supp2.process_data()
figure2supp2.plot(wspace=1.36);</code></pre>
            <figure slot="outputs"><img src="index.html.media/f77691acd033e03a79211e38f4b212d6.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"><img
                src="index.html.media/13c7ca629aad9600e914580ed341f2b0.png" alt="" itemscope=""
                itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="top-100-universities-in-terms-of-performance-in-total-open-access-publisher-mediated-open-access-gold-oa-and-repository-mediated-open-access-green-oa-for-2017">
              Top 100 universities in terms of performance in total open access, publisher-mediated
              open access (gold OA) and repository-mediated open access (green OA) for 2017.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The black lines represent
              the OA% as calculated from the data. The colour bars are 95% confidence intervals
              calculated with Šidák correction to compensate for the multiple comparisons effect.
              The colours represent the regions as per <a href="#fig2" itemscope=""
                itemtype="http://schema.stenci.la/Link">Figure 2</a>. Evidently, universities
              topping this list achieve around 80–90% OA.</p>
          </figcaption>
        </figure>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig2s3"
          title="Figure 2 - figure supplement 3"><label data-itemprop="label">Figure 2 - figure
            supplement 3</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="16" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>figure2supp3 = charts.BoxScatter(full_all, 2017, &#39;country&#39;, [&#39;Open Access (%)&#39;,
                                                         &#39;Total Gold OA (%)&#39;,
                                                         &#39;Total Green OA (%)&#39;])
figure2supp3.process_data()
figure2supp3.plot();</code></pre>
            <figure slot="outputs"><img src="index.html.media/fcd96cb97c3f9c34b372d874e3e29d99.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="percentage-of-institutional-total-oa-gold-oa-and-green-oa-left-to-right-grouped-by-country-for-2017">
              Percentage of institutional Total OA, Gold OA and Green OA (left to right) grouped by
              country for 2017.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The colours represent the
              regions as in <a href="#fig2" itemscope=""
                itemtype="http://schema.stenci.la/Link">Figure 2</a>. The overlaid boxplots exclude
              outliers as determined using the standard interquartile methods (i.e. values more than
              1.5 interquartile range away from the first or third quartile are deemed outliers).
              Countries are ordered by their median Total OA% (left panel). This figure includes
              small universities (those with significantly fewer research outputs) which are left
              out of the main article.</p>
          </figcaption>
        </figure>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The high performance of a
          number of Latin American and African universities, together with a number of Indonesian
          universities, particularly with respect to gold open access, is striking. For Latin
          America this is sensitive to our use of Microsoft Academic as a data source, showing the
          importance of an inclusive approach. The outcomes for Indonesian universities are also
          consistent with the latest report on country-level analysis (<cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib26">Van Noorden, 2019</a></cite>).
          These suggest that the narrative of Europe and the USA driving a publishing-dominated
          approach to open access misses a substantial part of the full global picture.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The highest performers in terms
          of open access via repositories are dominated by UK universities. This is not surprising
          given the power of the open access mandate associated with the Research Excellence
          Framework to drive university behaviour. It is perhaps interesting that few US
          universities appear in this group (with CalTech and MIT the exceptions). This suggests
          that while the National Institutes of Health mandate has been very effective at driving
          open access to the biomedical literature, limited inroads have been made into other
          disciplines in the US context, despite the White House memorandum. As was seen in the
          Leiden Ranking, Bilkent University from Turkey also emerges as a standout performer.</p>
        <h3 itemscope="" itemtype="http://schema.stenci.la/Heading"
          id="the-global-picture-and-its-evolution">The global picture and its evolution</h3>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The levels of total open
          access, publisher-mediated open access and repository-mediated open access for 1,207
          universities for publications in 2017 was also grouped by country (<a href="#fig2s3"
            itemscope="" itemtype="http://schema.stenci.la/Link">Figure 2—figure supplement 3</a>).
          Amongst countries with a large number of universities in the dataset, the UK is a clear
          leader with Indonesia, Brazil, Columbia, the Netherlands, and Switzerland showing a strong
          performance.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">To examine the global picture
          for the 1,207 universities in our dataset and to interrogate different paths to open
          access, we plot the overall level of repository-mediated (‘green’) and publisher-mediated
          (‘gold’) open access for each university over time coloured by region as previously (<a
            href="#fig3" itemscope="" itemtype="http://schema.stenci.la/Link">Figure 3</a>).</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig3" title="Figure 3">
          <label data-itemprop="label">Figure 3</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="17" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>sns.set_context(&quot;paper&quot;,rc={&quot;legend.fontsize&quot;:14,&quot;axes.labelsize&quot;:16},font_scale=2)
figure3 = charts.ScatterPlot(full, 
                                   &#39;Total Green OA (%)&#39;, 
                                   &#39;Total Gold OA (%)&#39;, 
                                   &#39;Year of Publication&#39;, 2017,
                                   hue_column=&#39;Region&#39;, 
                                   size_column=&#39;Total Publications&#39;)
figure3.process_data()
figure3.plot(xlim=(0,119), ylim=(0,100), figsize=(10,8));</code></pre>
            <figure slot="outputs"><img src="index.html.media/c43c43692516f3676c9f69f8cf042c15.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="comparing-the-level-of-gold-and-repository-mediated-open-access-of-individual-universities">
              Comparing the level of gold and repository-mediated open access of individual
              universities.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Publisher-mediated open
              access (gold OA) vs repository-mediated open access (green OA) by institution for
              2017. Each point plotted is a university, with size indicating the number of outputs
              analysed and colour showing the region. Articles can be open access through both
              publisher and repository routes so x and y values do not sum to give total open
              access. Animated version with figures for each year between 2007 to 2018 can be seen
              in <a href="#fig3video1" itemscope="" itemtype="http://schema.stenci.la/Link">Figure
                3—animation 1</a>.</p>
          </figcaption>
        </figure>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig3video1"
          title="Figure 3 - animation 1"><label data-itemprop="label">Figure 3 - animation
            1</label><video controls="" itemscope="" itemtype="http://schema.org/VideoObject">
            <source src="index.html.media/Figure3_animation.mp4">
            <p>Your browser does not support video elements.</p>
          </video></figure>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Overall universities in Oceania
          (Australia and New Zealand) and North America (Canada and the US) lag behind comparators
          in Europe (on repository-mediated open access) and Latin America (on publisher-mediated
          open access). Asian universities are highly diverse: there are some high performers in the
          top 100 institutions, particularly for publisher-mediated open access, but many also lag
          behind (<a href="#fig2s2" itemscope="" itemtype="http://schema.stenci.la/Link">Figure
            2—figure supplement 2</a>). Africa is also highly diverse but with a skew towards high
          performance, with an emphasis on publisher-mediated open access (i.e. gold open access).
          This may reflect our sampling which is skewed towards institutions with the largest
          (formally recorded) publishing volumes, many of which receive significant portions of
          their funding from international donors with strong open access requirements. Latin
          American institutions show high levels of publisher-mediated open access throughout the
          period illustrated. This is due to substantial infrastructure investments in systems like
          SciELO starting in the 1990s.</p>
        <h3 itemscope="" itemtype="http://schema.stenci.la/Heading"
          id="investigating-the-possible-effects-of-policy-interventions">Investigating the possible
          effects of policy interventions</h3>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">If our goal is to provide data
          on the effectiveness of interventions then our analysis should be capable of identifying
          potential effects of policy change. In 2012, the UK Research Councils, following the Finch
          Report, provided additional funding to individual universities to support open access
          publishing. The amount of additional funding relates to existing research council funding.
          In <a href="#fig4" itemscope="" itemtype="http://schema.stenci.la/Link">Figure 4A</a>, we
          show the annual change in publisher-mediated open access for three UK universities with
          the largest additional funding, and three with significantly less additional funding
          (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib14">Lawson,
              2018</a></cite>). In either 2012 or 2013, a slight increase in publisher-mediated open
          access across all the universities could be detected. As the additional funding tails off
          in 2015, the rate of growth falls back. Similarly, there was an increase in the proportion
          of hybrid open access publications, which largely require article processing charges, and
          an increase in proportion of hybrid open access within all publisher-mediated open access
          around the same period (<a href="#fig4s1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 4—figure supplement 1A and B</a>).</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig4" title="Figure 4">
          <label data-itemprop="label">Figure 4</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="20" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code># Sort rows by grid id and year then calculate annual changes to gold and hybrid OA
named = named.sort_values([&#39;grid_id&#39;, &#39;published_year&#39;])
named[&#39;Change in % Gold&#39;] = named.percent_gold.diff()
named[&#39;Change in % Hybrid&#39;] = named.percent_hybrid.diff()
sns.set_context(&quot;paper&quot;,rc={&quot;legend.fontsize&quot;:10,&quot;axes.labelsize&quot;:10},font_scale=1)
plots = [
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [
                &#39;grid.83440.3b&#39;, # University College London 
                &#39;grid.5335.0&#39;, # University of Cambridge 
                &#39;grid.8756.c&#39;, # University of Glasgow
                &#39;grid.6571.5&#39;, # Loughborough University
                &#39;grid.11914.3c&#39;, # University of St Andrews
                &#39;grid.11201.33&#39;, #Plymouth University
                    ],
            &#39;y_column&#39;: &#39;Change in % Gold&#39;,
            &#39;markerline&#39; : 2012
            },
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [
                &#39;grid.6571.5&#39;, # Loughborough University
                &#39;grid.5337.2&#39;, # University of Bristol
                &#39;grid.7445.2&#39;, # Imperial College
                &#39;grid.83440.3b&#39;, # University College London
                &#39;grid.5170.3&#39;, # TU Denmark
                &#39;grid.20861.3d&#39;, # CalTech
                    ],
            &#39;y_column&#39;: &#39;Green in Institutional Repository (%)&#39;,
            &#39;markerline&#39; : 2015
            },
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [    
                &#39;grid.5132.5&#39;, # Leiden University
                &#39;grid.4830.f&#39;, # University of Groningen
                &#39;grid.5477.1&#39;, # Utrecht University
                &#39;grid.5590.9&#39;, # Radboud University Nijmegen
                &#39;grid.12380.38&#39;, # VU University Amsterdam
                #&#39;grid.6852.9&#39;, # Eindhoven University of Technology
                    ],
            &#39;y_column&#39; : &#39;Hybrid OA (%)&#39;,
            &#39;markerline&#39; : 2015
            },
            {
            &#39;year_range&#39;: (2012,2019),
            &#39;unis&#39;: [
                &#39;grid.7445.2&#39;, # Imperial College
                &#39;grid.20861.3d&#39;, # CalTech
                &#39;grid.5335.0&#39;, # University of Cambridge 
                &#39;grid.21107.35&#39;, # Johns Hopkins
                &#39;grid.9759.2&#39;, # University of Kent
                &#39;grid.205975.c&#39; # UC, Santa Cruz
                    ],
            &#39;y_column&#39;: &#39;Total Green OA (%)&#39;,
            &#39;markerline&#39; : 2017,
            &#39;ylim&#39; : (50,70)
            }
]
figure4 = charts.TimePlotLayout(named, plots)
figure4.process_data()
fig = figure4.plot(figsize=(15,10), 
             wspace=0.3, 
             ylabel_adjustment=0.025, 
             panel_labels=True, 
             panellable_adjustment=0.02)
axes = fig.axes
for ax in axes[0:6]:
    ax.set_ylim(-1,7)
for ax in axes[6:12]:
    ax.set_ylim(0,70)
for ax in axes[12:17]:
    ax.set_ylim(6,19)
for ax in axes[17:19]:
    ax.set_ylim(43,72)</code></pre>
            <figure slot="outputs"><img src="index.html.media/14c8bd610453ab512be0c9e303027e74.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="monitoring-the-effect-of-policy-interventions-for-selected-groups-of-universities">
              Monitoring the effect of policy interventions for selected groups of universities.
            </h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">(<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">A</strong>) The annual change in
              percentage (rolling current year percentage minus the previous year percentage) of
              gold OA for six UK universities. The top three universities are those with the largest
              additional funding compared to the bottom three universities which received less
              additional funding. (<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">B</strong>) The annual percentage of green
              OA through the home institutional repositories of four UK universities compared to
              high performing universities from elsewhere. (<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">C</strong>) The annual percentages of
              hybrid OA at five universities in the Netherlands. (<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">D</strong>) Three pairs of UK and US
              universities, selected based on having a similar size and level of green OA. The
              annual percentages of total green OA are depicted for each university. Additional
              figures are provided in <a href="#fig4s1" itemscope=""
                itemtype="http://schema.stenci.la/Link">Figure 4—figure supplement 1</a>.</p>
          </figcaption>
        </figure>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig4s1"
          title="Figure 4 - figure supplement 1"><label data-itemprop="label">Figure 4 - figure
            supplement 1</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="21" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>named[&#39;% Hybrid in Gold OA&#39;] = named.hybrid/named.gold*100 #calculate proportion of hybrid in gold
plots = [
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [
                &#39;grid.83440.3b&#39;, # University College London 
                &#39;grid.5335.0&#39;, # University of Cambridge 
                &#39;grid.8756.c&#39;, # University of Glasgow
                &#39;grid.6571.5&#39;, # Loughborough University
                &#39;grid.11914.3c&#39;, # University of St Andrews
                &#39;grid.11201.33&#39;, #Plymouth University
                    ],
            &#39;y_column&#39;: &#39;Hybrid OA (%)&#39;,
            &#39;markerline&#39; : 2012
            },
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [
                &#39;grid.83440.3b&#39;, # University College London 
                &#39;grid.5335.0&#39;, # University of Cambridge 
                &#39;grid.8756.c&#39;, # University of Glasgow
                &#39;grid.6571.5&#39;, # Loughborough University
                &#39;grid.11914.3c&#39;, # University of St Andrews
                &#39;grid.11201.33&#39;, #Plymouth University
                    ],
            &#39;y_column&#39;: &#39;% Hybrid in Gold OA&#39;,
            &#39;markerline&#39; : 2012
            },
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [    
                &#39;grid.5132.5&#39;, # Leiden University
                &#39;grid.4830.f&#39;, # University of Groningen
                &#39;grid.5477.1&#39;, # Utrecht University
                &#39;grid.5590.9&#39;, # Radboud University Nijmegen
                &#39;grid.12380.38&#39;, # VU University Amsterdam
                #&#39;grid.6852.9&#39;, # Eindhoven University of Technology
                    ],
            &#39;y_column&#39; : &#39;Total Gold OA (%)&#39;,
            &#39;markerline&#39; : 2014
            },
            {
            &#39;year_range&#39;: (2008,2018),
            &#39;unis&#39;: [    
                &#39;grid.5132.5&#39;, # Leiden University
                &#39;grid.4830.f&#39;, # University of Groningen
                &#39;grid.5477.1&#39;, # Utrecht University
                &#39;grid.5590.9&#39;, # Radboud University Nijmegen
                &#39;grid.12380.38&#39;, # VU University Amsterdam
                #&#39;grid.6852.9&#39;, # Eindhoven University of Technology
                    ],
            &#39;y_column&#39; : &#39;Hybrid OA (%)&#39;,
            &#39;markerline&#39; : 2014
            }
]
figure4supp = charts.TimePlotLayout(named, plots)
figure4supp.process_data()
fig = figure4supp.plot(figsize=(15,10), 
             wspace=0.3, 
             ylabel_adjustment=0.025, 
             panel_labels=True, 
             panellable_adjustment=0.02)
axes = fig.axes
for ax in axes[0:6]:
    ax.set_ylim(0,20)
for ax in axes[6:12]:
    ax.set_ylim(25,70)
for ax in axes[12:17]:
    ax.set_ylim(10,40)
for ax in axes[17:23]:
    ax.set_ylim(6,19)</code></pre>
            <figure slot="outputs"><img src="index.html.media/f880514e8e04327c874616408986761c.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="monitoring-changes-in-the-percentage-of-oa-publications-for-selected-groups-of-universities-from-the-uk-and-the-netherlands">
              Monitoring changes in the percentage of OA publications for selected groups of
              universities from the UK and the Netherlands.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">(<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">A</strong>) The annual percentages of
              Hybrid OA publications for six UK universities. The top three are those that received
              the largest additional funding to support open access publishing compared to the
              bottom three that received less additional funding. (<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">B</strong>) For the same set of UK
              universities, this panel shows the proportion of Hybrid OA publications within Total
              Gold OA publications. (<strong itemscope=""
                itemtype="http://schema.stenci.la/Strong">C</strong>) The annual percentages of
              Total Gold OA for five Dutch universities, showing steady increase in Total Gold OA.
              (<strong itemscope="" itemtype="http://schema.stenci.la/Strong">D</strong>) The annual
              percentages of Hybrid OA for the same five Dutch universities, showing a sharp
              increase in Hybrid OA around 2014 and 2015.</p>
          </figcaption>
        </figure>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph"><a href="#fig4" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 4B</a> shows the growth of content in UK
          university repositories from 2000 to 2017 compared to two universities from other regions.
          In 2015, to be included in the UK Research Excellence Framework, universities had to
          deposit their research outputs in a repository. This policy shift was profound because it
          relates to an assessment exercise and funding which covers all disciplinary areas, and all
          universities. The dominance of UK universities in the top 100 for both overall open access
          and repository-mediated open access, as well as the commitment to achieve 100% open access
          coverage being made by such a large number of universities, is potentially driven in large
          part by that intervention.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Next, we investigated how the
          take up of hybrid open access publishing options in the Netherlands were influenced by
          deals with Springer in 2015, and Wiley in 2016 (<a href="#fig4" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 4C</a>). These deals essentially allow
          authors from Dutch universities to publish their work open access in a list of hybrid
          journals at no cost. We found that across the Netherlands levels of publishing in hybrid
          open access journals show a sharp turn of increase from 2014 onwards with a less
          pronounced effect (more smooth increases) for publishing in pure (i.e., gold) open access
          (compare <a href="#fig4s1" itemscope="" itemtype="http://schema.stenci.la/Link">Figure
            4—figure supplement 1C and D</a>).</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Finally, in <a href="#fig4"
            itemscope="" itemtype="http://schema.stenci.la/Link">Figure 4D</a> we show the possible
          effect of subtle differences in policy relating to acceptable embargo periods. UK research
          and funding council polices have been aggressive in reducing embargo lengths, mandating
          six months for STEM subjects and twelve months for humanities and social science (HSS)
          subjects. The potential effect of embargoes can be seen in the data for
          repository-mediated open access as a dip in the most recent years of publication. Using
          Unpaywall data from late 2019, we see a dip in repository-mediated open access performance
          for UK universities in 2018 but a limited effect on 2017. By comparison with three of the
          highest performing US universities, comparable in size and overall ranking (see <a
            href="#fig2s2" itemscope="" itemtype="http://schema.stenci.la/Link">Figure 2—figure
            supplement 2</a>) we see an extended dip in performance, indicative of an acceptance of
          longer embargoes.</p>
        <h3 itemscope="" itemtype="http://schema.stenci.la/Heading"
          id="different-institutional-paths-towards-open-access">Different institutional paths
          towards open access</h3>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In <a href="#fig3" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figures 3</a> and <a href="#fig4" itemscope=""
            itemtype="http://schema.stenci.la/Link">4</a> we see evidence of different paths towards
          open access, depending on the context and resources. The idea of mapping these paths is
          shown explicitly for a subset of universities in <a href="#fig5" itemscope=""
            itemtype="http://schema.stenci.la/Link">Figure 5</a>. This shows the paths taken by a
          selection of Latin American institutions and two sets of UK universities over time. For
          the UK universities shown, three received substantial funding from the UK research
          councils for open access publishing, whereas the other three received less additional
          funding and followed an alternate route, emphasising repository-mediated open access.</p>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig5" title="Figure 5">
          <label data-itemprop="label">Figure 5</label>
          <stencila-code-chunk itemscope="" itemtype="http://schema.stenci.la/CodeChunk"
            data-execution_count="22" data-programminglanguage="python">
            <pre class="language-python" itemscope="" itemtype="http://schema.stenci.la/CodeBlock"
              slot="text"><code>sns.set_context(&quot;paper&quot;,rc={&quot;legend.fontsize&quot;:14,&quot;axes.labelsize&quot;:16},font_scale=2)
comparison = [&#39;grid.83440.3b&#39;, # University College London 
              &#39;grid.5335.0&#39;, # University of Cambridge 
              &#39;grid.8756.c&#39;, # University of Glasgow
              &#39;grid.6571.5&#39;, # Loughborough University
              &#39;grid.11914.3c&#39;, # University of St Andrews
              &#39;grid.11201.33&#39;, #Plymouth University
              &#39;grid.11899.38&#39;, # University of Sao Paolo
              &#39;grid.410543.7&#39;, # Sao Paulo State University
              #&#39;grid.9486.3&#39;, # National Autonomous University of Mexico
              &#39;grid.411221.5&#39; # Universidade Federal de Pelotas           
             ]

colorpalette_sel_uni=[
                &#39;green&#39;,
                &#39;red&#39;,
                &#39;maroon&#39;,
                &#39;royalblue&#39;,
                &#39;darkviolet&#39;,
                &#39;darkorange&#39;,
                &#39;grey&#39;,
                &#39;blue&#39;,
                #&#39;pink&#39;,
                &#39;lightcoral&#39;
]

figure5 = charts.TimePath(named, (2007,2018), 
                   comparison, 
                   &#39;Total Green OA (%)&#39;, &#39;Total Gold OA (%)&#39;,
                   hue_column=&#39;University Name&#39;)

figure5.process_data()
figure5.plot(xlim=(0,119), ylim=(0,100), figsize=(10,8), colorpalette=colorpalette_sel_uni)</code></pre>
            <figure slot="outputs"><img src="index.html.media/06b59336affd4a4bfba14408fa412228.png"
                alt="" itemscope="" itemtype="http://schema.org/ImageObject"></figure>
          </stencila-code-chunk>
          <figcaption>
            <h4 itemscope="" itemtype="http://schema.stenci.la/Heading"
              id="comparing-different-paths-to-open-access-gold-oa-versus-green-oa-for-a-selected-set-of-universities-from-2007-to-2017">
              Comparing different paths to open access (gold OA versus green OA) for a selected set
              of universities from 2007 to 2017.</h4>
            <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">This figure compares the
              different open access routes taken by three groups of universities: three UK
              universities (University College London, University of Cambridge and University of
              Glasgow) that received substantial funding for open access publishing (combined gold
              and green OA increases), three UK universities (Loughborough University, University of
              St Andrews and Plymouth University) that received less funding (more green OA
              focused), and three Latin American universities (more gold OA focused). The dots
              represent the % of total gold OA publications and % of total green OA publications for
              the specified universities for each year from 2007 to 2017, where the arrow indicates
              the direction of time.</p>
          </figcaption>
        </figure>
        <figure itemscope="" itemtype="http://schema.stenci.la/Figure" id="fig5video1"
          title="Figure 5 - animation 1"><label data-itemprop="label">Figure 5 - animation
            1</label><video controls="" itemscope="" itemtype="http://schema.org/VideoObject">
            <source src="index.html.media/Figure5_animation.mp4">
            <p>Your browser does not support video elements.</p>
          </video></figure>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In contrast, the Latin American
          institutions already have high levels of publisher-mediated open access at our earliest
          time point, as discussed earlier. However, our data suggests a fall in overall open access
          amongst Latin American universities from 2012 onwards, which we ascribe to an increased
          pressure to publish in ‘international’ journals that are often subscription based, and for
          which Latin American scholars are reluctant or unable to pay hybrid article processing
          charges.</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading" id="discussion">Discussion</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Our results have significant
          implications for the details of policy interventions. Firstly, we have demonstrated the
          ability to detect signals of policy interventions in the behaviour of institutions. We see
          potential effects and results arising from the efforts of national funders and policy
          makers, particularly in the UK. The combined policy change and funding provided by the UK
          Research Councils in 2012 is associated with an increase in the level of
          publisher-mediated open access, and the level of increase appears to be associated with
          the level of funding provided. Similarly, the requirement for outputs to be deposited in a
          repository for eligibility for the 2021 Research Excellence Framework is associated with
          substantial increase in repository-mediated open access around 2015.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">These findings may also have
          implications for deciding on the effectiveness of directly funding open access publishing.
          It is perhaps surprising to some readers that the overall levels of publisher-mediated
          open access in the UK are not higher. Specific funders, most notably the Wellcome Trust,
          have achieved very high levels of open access for articles from research they support
          through the provision of funding for open access publication. In addition, the UK Research
          Councils invested significant resources in supporting gold open access. However, these
          have not translated to high levels of publisher-mediated open access across the full
          diversity of outputs of UK institutions. The majority gains over the past five years have
          come from repository-mediated open access.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In the animated version of <a
            href="#fig3" itemscope="" itemtype="http://schema.stenci.la/Link">Figure 3</a> (<a
            href="#fig3video1" itemscope="" itemtype="http://schema.stenci.la/Link">Figure
            3—animation 1</a>), there is a clear signal of saturation with respect to
          publisher-mediated open access (gold open access) for European and North American
          universities. With few exceptions, institutions do not achieve levels of gold open access
          greater than 40% and this level is stable from 2014 to 2018. Similarly, in <a href="#fig4"
            itemscope="" itemtype="http://schema.stenci.la/Link">Figure 4</a> we see evidence of
          shifts in response to stimuli (funding and policy interventions) which then stabilise.
          Even those UK universities with very high levels of repository-mediated open access
          (green) see a slowing down of the rise in levels a few years after the Research Excellence
          Framework policy intervention.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">These signals suggest that
          achieving 100% open access may be very difficult, and possibly expensive to achieve. There
          will always be areas and cases where open access is challenging. Current challenges
          include disciplinary areas such as the humanities where suitable business models and
          venues are still developing, as well as types of content, particularly books, where there
          is greater overlap between scholarly and general publishing. Both of these could be
          addressed rapidly through direct funding, but this may not be the most efficient approach.
          Achieving ‘100% open access’ may therefore require a tighter definition of exactly which
          outputs are in scope. For those areas where we see signals of saturation much lower than
          100% these are likely signals of the complexity of the system, and of large categories of
          outputs where open access is harder to achieve, or the motivation of institutions
          (including authors, libraries, and other support staff) to achieve it is lower.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In comparison to results
          presented by <cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib22">Robinson-Garcia et al., 2019</a></cite>, <cite itemscope=""
            itemtype="http://schema.stenci.la/Cite"><a href="#bib23">Robinson-Garcia et al.,
              2020</a></cite>, our analysis shows significantly improved performance of Latin
          American universities. This is driven by our inclusion of data sources beyond Web of
          Science, which has resulted in increased publisher-mediated open access for Latin America
          (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a href="#bib9">Huang et al.,
              2020</a></cite>). Similarly, our results also depict more clear observations of some
          high performing African and Asian universities. These produce a slightly different view in
          contrast to the one where UK universities dominate the top-ranking positions for open
          access.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">For Latin America, this result
          indicates how effective infrastructures such as SciELO can be at supporting the uptake of
          open access practices. In the case of Africa, there may be effects of funder requirements
          (with funders such as the Bill and Melinda Gates Foundation and Wellcome Trust that have
          strong open access requirements playing a significant role) as well as disciplinary
          spread. In both cases we are likely to have a limited view of the full diversity of
          research outputs due to their poor capture in information systems from the North Atlantic.
        </p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The continued leadership of
          Latin American institutions on publisher-mediated open access levels is the continuation
          of a trend set more than a decade ago through the provision of publishing infrastructures.
          Taken alongside the clear response in the Netherlands for hybrid open access in response
          to publish and read agreements, this suggests that increasing levels of open access
          publishing through article processing charges is potentially expensive compared to the
          costs of providing infrastructure.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Another interesting natural
          experiment is how the strength of funder actions is associated with overall change in
          levels of open access. In the Netherlands and the UK in particular, but also in the US,
          where funder policies have moved from encouragement, to mandates, to monitoring with
          sanctions for non-compliance, there are substantial shifts in overall levels of open
          access. By contrast, in countries where policy remains effectively at the level of a
          recommendation, such as Australia, levels of open access lag significantly. Recent
          increases in reporting requirements by Australian funders might therefore be expected to
          lead to a detectable signal over the next 12–24 months.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">The value of analysis at the
          level of universities is that we gain a picture of open access performance across a
          diverse research ecosystem. We see differences across countries and regions, and
          differences between universities within countries. Overall, we see that there are multiple
          different paths towards improving access, and that different paths may be more or less
          appropriate in different contexts. Most importantly, while further research is needed to
          unpick the details of the differences in open access provision, we hope this work provides
          a framework that enables this longitudinal analysis to be taken forward and used wherever
          it is needed.</p>
        <h2 itemscope="" itemtype="http://schema.stenci.la/Heading"
          id="limitations-and-further-work">Limitations and further work</h2>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">Our analysis process includes
          automated approaches for collecting the outputs related to specific universities, and the
          analysis of those outputs. Currently the addition of new universities, and the updating of
          large data sources is partly manual (<a href="#supp1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>), but we also expect to
          automate this in the near future. As a result, our analysis has limitations in its
          capacity to provide comparable estimates of open access status across all universities,
          but does provide a reproducible and transparent view of overall global performance.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">There are challenges to be
          addressed with respect to small universities and research organisations, and we have taken
          a necessarily subjective view of which institutions to include (see <a href="#supp1"
            itemscope="" itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>). Our
          approach systematically leaves out universities with very small numbers of outputs (i.e.,
          less than 100 outputs), and universities with very extreme open access proportions as
          these are the universities for which we have less statistical confidence in the results.
          This is also in-line with our intended focus on research-intensive universities. These
          small institutions are of significant interest but will require a different analysis
          approach. We include a country-level summary result for the full set of institutions
          (including small institutions left out from the main article) in our data set in <a
            href="#fig2s3" itemscope="" itemtype="http://schema.stenci.la/Link">Figure 2—figure
            supplement 3</a>. We recognise that the inclusion of universities beyond our initial
          selection can also potentially change the results.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We have used multiple sources
          of bibliographic information with the goal of gaining a more inclusive view of research
          outputs. Despite this, there are still limitations in the coverage of these data sources,
          and a likely bias towards science, technology, engineering and maths (STEM) disciplines.
          In addition, the focus of Unpaywall on analysis of outputs with Crossref DOIs means that
          we are missing outputs for disciplines (humanities) and output types (books) where the use
          of DOIs is lower. While we have performed additional sensitivity analysis on the use of
          different data sources (<cite itemscope="" itemtype="http://schema.stenci.la/Cite"><a
              href="#bib9">Huang et al., 2020</a></cite>), further work is required to understand
          the relationships between disciplinary biases in data sources and the influence of
          external policies (such as those of the National Institutes of Health and the Wellcome
          Trust) on repositories. In addition, due to the nature of this work and to limitations on
          the use of Web of Science and Scopus APIs, we have collected data from these two sources
          over a period of time. Although we expect such changes to be small, those effects are not
          clearly represented in our data. For other data sources we are able to precisely define
          the data dump used for our analysis, supporting reproducibility as well as modified
          analyses. We also recognise that our longitudinal analysis is done post hoc from a fixed
          time point (i.e., looking back). Our results for a given year of publication will not be
          the same as the levels of open access that would have been observed <em itemscope=""
            itemtype="http://schema.stenci.la/Emphasis">in</em> that year, due to embargoes and
          moving paywalls.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">In this article, we have drawn
          comparisons between publisher-mediated open access and repository-mediated open access to
          identify different institutional paths to open access. The overall trends are retained if
          we separate out outputs that are only available through repositories (i.e., not free to
          access via publishers) and compare these to publisher-mediated open access instead.
          However, we recognise that at the individual university level, this can be dependent on
          institutional policy and whether the corresponding data can be properly captured by
          current systems that determines open access status.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">There is significant
          opportunity for improving the data sources on sets of outputs and how they can be grouped
          (e.g. by people, discipline, organisation, country, etc.). Improvements to institutional
          identifier systems such as the Research Organisation Registry, increased completeness of
          metadata records, particularly that provided by publishers via Crossref on affiliation,
          ORCIDs and funders, and enhancing the coverage of open access status data (for instance by
          incorporating data from CORE and BASE), will all enhance coverage. There are also
          opportunities to expand the coverage by incorporating a wider range of bibliographic data
          sources.</p>
        <p itemscope="" itemtype="http://schema.stenci.la/Paragraph">We have sought to make our
          methodology and approach as reproducible and reusable as is practicable. The main
          challenges lie in the level of accessibility to the closed data sources (i.e., Web of
          Science and Scopus) and more generally with data sources that are not available in the
          form of identifiable snapshots (see <a href="#supp1" itemscope=""
            itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>). In addition,
          semi-automated processing and manual searches are required to link institutional
          identifiers across multiple data sources (as discussed in detail in <a href="#supp1"
            itemscope="" itemtype="http://schema.stenci.la/Link">Supplementary file 1</a>). For the
          rest of the framework, we have provided transparent descriptions and source code that
          allow reprocessing, as described in the next section. Further work is required to provide
          a complete and deployable framework for replication but we are making progress in this
          area (see <a href="https://github.com/The-Academic-Observatory/observatory-platform"
            itemscope=""
            itemtype="http://schema.stenci.la/Link">https://github.com/The-Academic-Observatory/observatory-platform</a>
          for an example).</p>
        <section data-itemprop="references">
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