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I dumped all the CGSpace DOIs and resolved them with my crossref_doi_lookup.py script
Then I did some work to add missing abstracts (about 900!), volumes, issues, licenses, publishers, and types, etc
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I dumped all the CGSpace DOIs and resolved them with my crossref_doi_lookup.py script
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<h2 class="blog-post-title" dir="auto"><a href="https://alanorth.github.io/cgspace-notes/2024-05/">May, 2024</a></h2>
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<time datetime="2024-05-01T10:39:00+03:00">Wed May 01, 2024</time>
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<h2 id="2024-05-01">2024-05-01</h2>
<ul>
<li>I dumped all the CGSpace DOIs and resolved them with my <code>crossref_doi_lookup.py</code> script
<ul>
<li>Then I did some work to add missing abstracts (about 900!), volumes, issues, licenses, publishers, and types, etc</li>
</ul>
</li>
</ul>
<h2 id="2024-05-05">2024-05-05</h2>
<ul>
<li>Spend some time looking at duplicate DOIs again…</li>
</ul>
<h2 id="2024-05-06">2024-05-06</h2>
<ul>
<li>Spend some time looking at duplicate DOIs again…</li>
</ul>
<h2 id="2024-05-07">2024-05-07</h2>
<ul>
<li>Discuss RSS feeds and OpenSearch with IWMI
<ul>
<li>It seems our OpenSearch feed settings are using the defaults, so I need to copy some of those over from our old DSpace 6 branch</li>
</ul>
</li>
<li>I saw a patch for an interesting issue on DSpace GitHub: <a href="https://github.com/DSpace/DSpace/issues/9544">Error submitting or deleting items - URI too long when user is in a large number of groups</a>
<ul>
<li>I hadn’t realized it, but we have lots of those errors:</li>
</ul>
</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ zstdgrep -a <span style="color:#e6db74">'URI Too Long'</span> log/dspace.log-2024-04-* | wc -l
</span></span><span style="display:flex;"><span>1423
</span></span></code></pre></div><ul>
<li>Spend some time looking at duplicate DOIs again…</li>
</ul>
<h2 id="2024-05-08">2024-05-08</h2>
<ul>
<li>Spend some time looking at duplicate DOIs again…
<ul>
<li>I finally finished looking at the duplicate DOIs for journal articles</li>
<li>I updated the list of handle redirects and there are 386 of them!</li>
</ul>
</li>
</ul>
<h2 id="2024-05-09">2024-05-09</h2>
<ul>
<li>Spend some time working on the IFPRI 2020–2021 batch
<ul>
<li>I started by checking for exact duplicates (1.0 similarity) using DOI, type, and issue date</li>
</ul>
</li>
</ul>
<h2 id="2024-05-12">2024-05-12</h2>
<ul>
<li>I couldn’t figure out how to do a complex join on withdrawn items along with their metadata, so I pull out a few like titles, handles, and provenance separately:</li>
</ul>
<pre tabindex="0"><code class="language-psql" data-lang="psql">dspace=# \COPY (SELECT i.uuid, m.text_value AS uri FROM item i JOIN metadatavalue m ON i.uuid = m.dspace_object_id WHERE withdrawn AND m.metadata_field_id=25) TO /tmp/withdrawn-handles.csv CSV HEADER;
dspace=# \COPY (SELECT i.uuid, m.text_value AS title FROM item i JOIN metadatavalue m ON i.uuid = m.dspace_object_id WHERE withdrawn AND m.metadata_field_id=64) TO /tmp/withdrawn-titles.csv CSV HEADER;
dspace=# \COPY (SELECT i.uuid, m.text_value AS submitted_by FROM item i JOIN metadatavalue m ON i.uuid = m.dspace_object_id WHERE withdrawn AND m.metadata_field_id=28 AND m.text_value LIKE 'Submitted by%') TO /tmp/withdrawn-submitted-by.csv CSV HEADER;
</code></pre><ul>
<li>Then joined them:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ csvjoin -c uuid /tmp/withdrawn-title.csv /tmp/withdrawn-handles.csv /tmp/withdrawn-submitted-by.csv > /tmp/withdrawn.csv
</span></span></code></pre></div><ul>
<li>This gives me an insight into who submitted at 334 of the duplicates over the past few years…</li>
<li>I fixed a few hundred titles with leading/trailing whitespace, newlines, and ligatures like ff, fi, fl, ffi, and ffl</li>
</ul>
<h2 id="2024-05-13">2024-05-13</h2>
<ul>
<li>Export a list of IFPRI information products with handle links and CONTENTdm links:</li>
</ul>
<pre tabindex="0"><code>$ csvgrep -c 'dc.description.provenance[en_US]' -m 'CONTENTdm' cgspace.csv \
| csvcut -c 'id,dc.description.provenance[en_US],dc.identifier.uri[en_US]' \
| tee /tmp/ifpri-redirects.csv \
| csvstat --count
2645
</code></pre><ul>
<li>I discovered the <code>/server/api/pid/find</code> endpoint today, which is much more direct and manageable than the <code>/server/api/discover/search/objects?query=</code> endpoint when trying to get metadata for a Handle (item, collection, or community)
<ul>
<li>The “pid” stands for permanent identifiers apparently, and we can use it like this:</li>
</ul>
</li>
</ul>
<pre tabindex="0"><code>https://dspace7test.ilri.org/server/api/pid/find?id=10568/118424
</code></pre><h2 id="2024-05-15">2024-05-15</h2>
<ul>
<li>I got journal titles for 2,900 journal articles that were missing them from Crossref</li>
</ul>
<h2 id="2024-05-16">2024-05-16</h2>
<p>Helping IFPRI with some DSpace 7 API support, these are two queries for items issued in 2024:</p>
<ul>
<li><a href="https://dspace7test.ilri.org/server/api/discover/search/objects?query=dcterms.issued:2024">https://dspace7test.ilri.org/server/api/discover/search/objects?query=dcterms.issued:2024</a></li>
<li><a href="https://dspace7test.ilri.org/server/api/discover/search/objects?query=dcterms.issued_dt%3A%5B2024-01-01T00%3A00%3A00Z%20TO%20%2A%5D">https://dspace7test.ilri.org/server/api/discover/search/objects?query=dcterms.issued_dt%3A%5B2024-01-01T00%3A00%3A00Z%20TO%20%2A%5D</a> — note the Lucene search syntax is URL encoded version of <code>:[2024-01-01T00:00:00Z TO *]</code></li>
</ul>
<p>Both of them return the same number of results and seem identitical as far as I can see, but the second one uses Solr date indexes and requires the full Lucene datetime and range syntax</p>
<p>I wrote a new version of the <code>check_duplicates.py</code> script to help identify duplicates with different types</p>
<ul>
<li>Initially I called it <code>check_duplicates_fast.py</code> but it’s actually not faster</li>
<li>I need to find a way to deal with duplicates from IFPRI’s repository because there are some mismatched types…</li>
</ul>
<h2 id="2024-05-20">2024-05-20</h2>
<p>Continue working through alternative duplicate matching for IFPRI</p>
<ul>
<li>Their item types are sometimes different than ours…</li>
<li>One thing I think I can say for sure is that the default similarity factor in my script is 0.6, and I rarely see legitimate duplicates with such similarity so I might increase this to 0.7 to reduce the number of items I have to check</li>
<li>Also, the difference in issue dates is currently 365, but I should reduce that a bit, perhaps to 270 days (9 months)</li>
</ul>
<h2 id="2024-05-22">2024-05-22</h2>
<ul>
<li>Finalize and upload the IFPRI 2020–2021 batch set
<ul>
<li>I used a new technique to get missing licenses via Crossref (it’s Python 2 because of OpenRefine’s Jython):</li>
</ul>
</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">import</span> urllib2
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span>doi <span style="color:#f92672">=</span> cells[<span style="color:#e6db74">'cg.identifier.doi[en_US]'</span>]<span style="color:#f92672">.</span>value
</span></span><span style="display:flex;"><span>url <span style="color:#f92672">=</span> <span style="color:#e6db74">"https://api.crossref.org/works/"</span> <span style="color:#f92672">+</span> doi
</span></span><span style="display:flex;"><span>useragent <span style="color:#f92672">=</span> <span style="color:#e6db74">"Python (mailto:a.o@cgiar.org)"</span>
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span>request <span style="color:#f92672">=</span> urllib2<span style="color:#f92672">.</span>Request(url<span style="color:#f92672">.</span>encode(<span style="color:#e6db74">"utf-8"</span>), headers<span style="color:#f92672">=</span>{<span style="color:#e6db74">"User-Agent"</span> : useragent})
</span></span><span style="display:flex;"><span>get <span style="color:#f92672">=</span> urllib2<span style="color:#f92672">.</span>urlopen(request)
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span><span style="color:#66d9ef">return</span> get<span style="color:#f92672">.</span>read()<span style="color:#f92672">.</span>decode(<span style="color:#e6db74">'utf-8'</span>)
</span></span></code></pre></div><h2 id="2024-05-23">2024-05-23</h2>
<ul>
<li>Finalize last of the duplicates I found for the IFPRI 2020–2021 batch set (those that we missed initially due to mismatched types)</li>
<li>Export a new list of IFPRI redirects from CONTENTdm:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ csvgrep -c <span style="color:#e6db74">'dc.description.provenance[en_US]'</span> -r <span style="color:#e6db74">'Original URLs? from IFPRI CONTENTdm'</span> cgspace.csv <span style="color:#ae81ff">\
</span></span></span><span style="display:flex;"><span><span style="color:#ae81ff"></span> | csvcut -c 'id,dc.description.provenance[en_US],dc.identifier.uri[en_US]' \
</span></span><span style="display:flex;"><span> | tee /tmp/ifpri-redirects.csv \
</span></span><span style="display:flex;"><span> | csvstat --count
</span></span><span style="display:flex;"><span>4004
</span></span></code></pre></div><p>I found a way to get abstracts from PLOS</p>
<ul>
<li>They offer an API that returns XML including the JATS-formatted abstracts</li>
<li>I created a new column in OpenRefine by fetching specially crafted URLs based on the DOIs using this GREL:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>"https://journals.plos.org/plosone/article/file?id=" + cells['doi'].value + '&type=manuscript'
</span></span></code></pre></div><p>Then used <code>value.parseXml()</code> on the resulting text to extract the abstract’s text:</p>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>value.parseXml().select("abstract")[0].xmlText()
</span></span></code></pre></div><p>This doesn’t preserve <code><p></code> tags though…</p>
<ul>
<li>Oh, nice, this does!</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>forEach(value.parseHtml().select("abstract p"), i, i.htmlText()).join("\r\n\r\n")
</span></span></code></pre></div><p>For each paragraph inside an abstract, get the inner text and join them as one string separated by two newlines…</p>
<ul>
<li>Ah, some articles have multiple abstracts, for example: <a href="https://journals.plos.org/plosone/article/file?id=https://doi.org/10.1371/journal.pntd.0001859&type=manuscript">https://journals.plos.org/plosone/article/file?id=https://doi.org/10.1371/journal.pntd.0001859&type=manuscript</a></li>
<li>I need to select the abstract that does <strong>not</strong> have any attributes (using <a href="https://jsoup.org/apidocs/org/jsoup/select/Selector.html">Jsoup selector syntax</a>)</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>forEach(value.parseXml().select("abstract:not([*]) p"), i, i.xmlText()).join("\r\n\r\n")
</span></span></code></pre></div><p>Testing <code>xsv</code> (Rust) versus <code>csvkit</code> (Python) to filter all items with DOIs from a DSpace dump with 118,000 items:</p>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ time xsv search -s doi <span style="color:#e6db74">'doi\.org'</span> /tmp/cgspace-minimal.csv | xsv <span style="color:#66d9ef">select</span> doi | xsv count
</span></span><span style="display:flex;"><span>27339
</span></span><span style="display:flex;"><span>xsv search -s doi 'doi\.org' /tmp/cgspace-minimal.csv 0.06s user 0.03s system 98% cpu 0.091 total
</span></span><span style="display:flex;"><span>xsv select doi 0.02s user 0.02s system 40% cpu 0.091 total
</span></span><span style="display:flex;"><span>xsv count 0.01s user 0.00s system 9% cpu 0.090 total
</span></span><span style="display:flex;"><span>$ time csvgrep -c doi -m <span style="color:#e6db74">'doi.org'</span> /tmp/cgspace-minimal.csv | csvcut -c doi | csvstat --count
</span></span><span style="display:flex;"><span>27339
</span></span><span style="display:flex;"><span>csvgrep -c doi -m 'doi.org' /tmp/cgspace-minimal.csv 1.15s user 0.06s system 95% cpu 1.273 total
</span></span><span style="display:flex;"><span>csvcut -c doi 0.42s user 0.05s system 36% cpu 1.283 total
</span></span><span style="display:flex;"><span>csvstat --count 0.20s user 0.03s system 18% cpu 1.298 total
</span></span></code></pre></div><h2 id="2024-05-27">2024-05-27</h2>
<ul>
<li>Working on IFPRI datasets batch migration
<ul>
<li>732 items total</li>
<li>6 duplicates on CGSpace</li>
<li>6 duplicates within set that need investigation</li>
</ul>
</li>
</ul>
<h2 id="2024-05-28">2024-05-28</h2>
<ul>
<li>I’m thinking of increasing the frequency of thumbnail generation on CGSpace
<ul>
<li>Currently the <code>dspace filter-media</code> script runs once at 3AM for all media types and seems to take ~10 minutes to run for all 118,000 items…</li>
<li>I think I will make the thumbnailer run explicitly more often using <code>-p "ImageMagick PDF Thumbnail"</code></li>
</ul>
</li>
</ul>
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