--- title: "May, 2024" date: 2024-05-01T10:39:00+03:00 author: "Alan Orth" categories: ["Notes"] --- ## 2024-05-01 - 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 ## 2024-05-05 - Spend some time looking at duplicate DOIs again... ## 2024-05-06 - Spend some time looking at duplicate DOIs again... ## 2024-05-07 - Discuss RSS feeds and OpenSearch with IWMI - 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 - I saw a patch for an interesting issue on DSpace GitHub: [Error submitting or deleting items - URI too long when user is in a large number of groups](https://github.com/DSpace/DSpace/issues/9544) - I hadn't realized it, but we have lots of those errors: ```console $ zstdgrep -a 'URI Too Long' log/dspace.log-2024-04-* | wc -l 1423 ``` - Spend some time looking at duplicate DOIs again... ## 2024-05-08 - Spend some time looking at duplicate DOIs again... - I finally finished looking at the duplicate DOIs for journal articles - I updated the list of handle redirects and there are 386 of them! ## 2024-05-09 - Spend some time working on the IFPRI 2020–2021 batch - I started by checking for exact duplicates (1.0 similarity) using DOI, type, and issue date ## 2024-05-12 - I couldn't figure out how to do a complex join on withdrawn items along with their metadata, so I pull out a few like titles, handles, and provenance separately: ```psql dspace=# \COPY (SELECT i.uuid, m.text_value AS uri FROM item i JOIN metadatavalue m ON i.uuid = m.dspace_object_id WHERE withdrawn AND m.metadata_field_id=25) TO /tmp/withdrawn-handles.csv CSV HEADER; dspace=# \COPY (SELECT i.uuid, m.text_value AS title FROM item i JOIN metadatavalue m ON i.uuid = m.dspace_object_id WHERE withdrawn AND m.metadata_field_id=64) TO /tmp/withdrawn-titles.csv CSV HEADER; dspace=# \COPY (SELECT i.uuid, m.text_value AS submitted_by FROM item i JOIN metadatavalue m ON i.uuid = m.dspace_object_id WHERE withdrawn AND m.metadata_field_id=28 AND m.text_value LIKE 'Submitted by%') TO /tmp/withdrawn-submitted-by.csv CSV HEADER; ``` - Then joined them: ```console $ csvjoin -c uuid /tmp/withdrawn-title.csv /tmp/withdrawn-handles.csv /tmp/withdrawn-submitted-by.csv > /tmp/withdrawn.csv ``` - This gives me an insight into who submitted at 334 of the duplicates over the past few years... - I fixed a few hundred titles with leading/trailing whitespace, newlines, and ligatures like ff, fi, fl, ffi, and ffl ## 2024-05-13 - Export a list of IFPRI information products with handle links and CONTENTdm links: ``` $ 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 ``` - I discovered the `/server/api/pid/find` endpoint today, which is much more direct and manageable than the `/server/api/discover/search/objects?query=` endpoint when trying to get metadata for a Handle (item, collection, or community) - The "pid" stands for permanent identifiers apparently, and we can use it like this: ``` https://dspace7test.ilri.org/server/api/pid/find?id=10568/118424 ``` ## 2024-05-15 - I got journal titles for 2,900 journal articles that were missing them from Crossref ## 2024-05-16 Helping IFPRI with some DSpace 7 API support, these are two queries for items issued in 2024: - 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_dt%3A%5B2024-01-01T00%3A00%3A00Z%20TO%20%2A%5D — note the Lucene search syntax is URL encoded version of `:[2024-01-01T00:00:00Z TO *]` 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 I wrote a new version of the `check_duplicates.py` script to help identify duplicates with different types - Initially I called it `check_duplicates_fast.py` but it's actually not faster - I need to find a way to deal with duplicates from IFPRI's repository because there are some mismatched types... ## 2024-05-20 Continue working through alternative duplicate matching for IFPRI - Their item types are sometimes different than ours... - 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 - Also, the difference in issue dates is currently 365, but I should reduce that a bit, perhaps to 270 days (9 months) ## 2024-05-22 - Finalize and upload the IFPRI 2020–2021 batch set - I used a new technique to get missing licenses via Crossref (it's Python 2 because of OpenRefine's Jython): ```python import urllib2 doi = cells['cg.identifier.doi[en_US]'].value url = "https://api.crossref.org/works/" + doi useragent = "Python (mailto:a.o@cgiar.org)" request = urllib2.Request(url.encode("utf-8"), headers={"User-Agent" : useragent}) get = urllib2.urlopen(request) return get.read().decode('utf-8') ``` ## 2024-05-23 - Finalize last of the duplicates I found for the IFPRI 2020–2021 batch set (those that we missed initially due to mismatched types) - Export a new list of IFPRI redirects from CONTENTdm: ```console $ csvgrep -c 'dc.description.provenance[en_US]' -r 'Original URLs? from IFPRI CONTENTdm' cgspace.csv \ | csvcut -c 'id,dc.description.provenance[en_US],dc.identifier.uri[en_US]' \ | tee /tmp/ifpri-redirects.csv \ | csvstat --count 4004 ``` I found a way to get abstracts from PLOS - They offer an API that returns XML including the JATS-formatted abstracts - I created a new column in OpenRefine by fetching specially crafted URLs based on the DOIs using this GREL: ```console "https://journals.plos.org/plosone/article/file?id=" + cells['doi'].value + '&type=manuscript' ``` Then used `value.parseXml()` on the resulting text to extract the abstract's text: ```console value.parseXml().select("abstract")[0].xmlText() ``` This doesn't preserve `

` tags though... - Oh, nice, this does! ```console forEach(value.parseHtml().select("abstract p"), i, i.htmlText()).join("\r\n\r\n") ``` For each paragraph inside an abstract, get the inner text and join them as one string separated by two newlines... - Ah, some articles have multiple abstracts, for example: https://journals.plos.org/plosone/article/file?id=https://doi.org/10.1371/journal.pntd.0001859&type=manuscript - I need to select the abstract that does **not** have any attributes (using [Jsoup selector syntax](https://jsoup.org/apidocs/org/jsoup/select/Selector.html)) ```console forEach(value.parseXml().select("abstract:not([*]) p"), i, i.xmlText()).join("\r\n\r\n") ``` Testing `xsv` (Rust) versus `csvkit` (Python) to filter all items with DOIs from a DSpace dump with 118,000 items: ```console $ time xsv search -s doi 'doi\.org' /tmp/cgspace-minimal.csv | xsv select doi | xsv count 27339 xsv search -s doi 'doi\.org' /tmp/cgspace-minimal.csv 0.06s user 0.03s system 98% cpu 0.091 total xsv select doi 0.02s user 0.02s system 40% cpu 0.091 total xsv count 0.01s user 0.00s system 9% cpu 0.090 total $ time csvgrep -c doi -m 'doi.org' /tmp/cgspace-minimal.csv | csvcut -c doi | csvstat --count 27339 csvgrep -c doi -m 'doi.org' /tmp/cgspace-minimal.csv 1.15s user 0.06s system 95% cpu 1.273 total csvcut -c doi 0.42s user 0.05s system 36% cpu 1.283 total csvstat --count 0.20s user 0.03s system 18% cpu 1.298 total ``` ## 2024-05-27 - Working on IFPRI datasets batch migration - 732 items total - 6 duplicates on CGSpace - 6 duplicates within set that need investigation ## 2024-05-28 - I'm thinking of increasing the frequency of thumbnail generation on CGSpace - Currently the `dspace filter-media` script runs once at 3AM for all media types and seems to take ~10 minutes to run for all 118,000 items... - I think I will make the thumbnailer run explicitly more often using `-p "ImageMagick PDF Thumbnail"`