vallenderlab / journalanalysis Goto Github PK
View Code? Open in Web Editor NEWA repository for exploring journals that we would like to publish under.
Home Page: https://vallenderlab.github.io/JournalAnalysis/
A repository for exploring journals that we would like to publish under.
Home Page: https://vallenderlab.github.io/JournalAnalysis/
There's got to be more sources for the journal impact factor. We can combine it with our current data sets #2.
There might also be an API for various data like this.
Currently the header for the dataframes looks like this:
> colnames(x$combined)
[1] "id" "source" "pmid" "doi"
[5] "title" "authorString" "journalTitle" "pubYear"
[9] "journalIssn" "pubType" "isOpenAccess" "inEPMC"
[13] "inPMC" "hasPDF" "hasBook" "citedByCount"
[17] "hasReferences" "hasTextMinedTerms" "hasDbCrossReferences" "hasLabsLinks"
[21] "hasTMAccessionNumbers" "firstPublicationDate" "pageInfo" "pmcid"
[25] "issue" "journalVolume" "hasSuppl" "ISSN.1"
[29] "ISSN.2.x" "Rank" "Title" "Type"
[33] "SJR" "SJR.Best.Quartile" "H.index" "Total.Docs...2016."
[37] "Total.Docs...3years." "Total.Refs." "Total.Cites..3years." "Citable.Docs...3years."
[41] "Cites...Doc...2years." "Ref....Doc." "Country" "Categories"
[45] "ISSN" "ISSN.2.y" "ISSN.2" "ISSN.1.y"
These can be made to look better and some can be deleted from the main output in the get_publication_data function.
It may be beneficial to combine these datasets and standardize the format of each variable. For instance the ISSN numbers are very different, and require a lot of overhead to match the data with europepmc's ISSN data.
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