Open JonathanReeve opened 3 years ago
@sy2657, can you take this one?
Ok, sure.
On Mon, Jun 21, 2021 at 11:52 PM Jonathan Reeve @.***> wrote:
Here is the beginning of an example where I'm querying the CrossRef API for bibliographic data that I'm then using to augment the graph. https://github.com/JonathanReeve/data-ethics-literature-review/blob/1ed14be780f74c2c04a006e037145320516893df/turtleize/enhanceBibliography.py .
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@sy2657, just leave a note here if you have any questions about this issue, or how best to approach it.
Here's a breakdown of how I imagine this would go:
@Zhuohan-Amber, the process is pretty much the same for #27, only without the semantic scholar IDs. There, the DOI is the thing that gets us the furthest.
Hi, I ran your code for queryCrossRef on a small subset of coursesAndTexts.ttl and it did not print out any data...
Do I do this task for the items of the category, z:UserItem ?
Also how do I save the metadata ? I save (metadata) Title, Authors, Abstract, Comments, Report-no, Category, Journal-ref, DOI, MSC-class, ACM-class in some format ?
Yep, that code isn't working yet. It's just the beginnings of an example. The idea is just: go through each text (z:UserItem
), find more metadata about the text, and then add it to the graph.
The text metadata format is bibliontology. Here's an example for an article, and here's one for a book. Bibliontology uses Dublin Core (dcterms
) for things like titles and authors.
So if you have variables title
and author
, and others, to add to the graph, you can add it with something like:
g.add((item, dcterms:title, title))
g.add((item, dcterms:creator, author))
where item
is the z:UserItem
.
This is a sub-task of #21, and a sibling task of #27.
Let's use the ArXiv API to resolve texts, and use the data retrieved from that API to augment our own bibliographic data.
The easy ones will be ones that have ArXiv IDs:
(That example is very messy.)
This will make #14 a lot easier.