R Package to interface with Elsevier and Scopus APIs
The goal of rscopus is to provide an R Scopus Database ‘API’ Interface.
Steps to get API key
In order to use this package, you need an API key from https://dev.elsevier.com/sc_apis.html. You should login from your institution and go to Create API Key. You need to provide a website URL and a label, but the website can be your personal website, and agree to the terms of service.
- Go to https://dev.elsevier.com/user/login. Login or create a free account.
- Click “Create API Key”. Put in a label, such as
rscopus key. Add a website. http://example.com is fine if you do not have a site. - Read and agree to the TOS if you do indeed agree.
- Add
Elsevier_API = "API KEY GOES HERE"to~/.Renvironfile, or addexport Elsevier_API=API KEY GOES HEREto your~/.bash_profile.
Alternatively, you you can either set the API key using rscopus::set_api_key or by options("elsevier_api_key" = api_key). You can access the API key using rscopus::get_api_key.
You should be able to test out the API key using the interactive Scopus APIs.
A note about API keys and IP addresses
The API Key is bound to a set of IP addresses, usually bound to your institution. Therefore, if you are using this for a Shiny application, you must host the Shiny application from your institution servers in some way. Also, you cannot access the Scopus API with this key if you are offsite and must VPN into the server or use a computing cluster with an institution IP.
Example
This is a basic example which shows you how to solve a common problem:
library(rscopus)
library(dplyr)
res = author_df(last_name = "Muschelli", first_name = "John", verbose = FALSE, general = FALSE)
names(res)
#> [1] "auth_order" "affilname_1"
#> [3] "n_auth" "affilname_2"
#> [5] "n_affils" "citations"
#> [7] "journal" "description"
#> [9] "title" "pii"
#> [11] "doi" "eid"
#> [13] "cover_date" "cover_display_date"
#> [15] "prism_url" "dc_identifier"
#> [17] "dc_creator" "prism_issn"
#> [19] "prism_eIssn" "prism_pageRange"
#> [21] "dc_description" "prism_aggregationType"
#> [23] "subtype" "authkeywords"
#> [25] "source_id" "first_name"
#> [27] "last_name" "au_id"
head(res[, c("title", "journal", "description")])
#> title
#> 1 Neuroconductor: An R platform for medical imaging analysis
#> 2 MIMoSA: An Approach to automatically segment T2 hyperintense and T1 hypointense lesions in multiple sclerosis
#> 3 Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
#> 4 MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions
#> 5 Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma
#> 6 Feasibility of Coping Effectiveness Training for Caregivers of Children with Autism Spectrum Disorder: a Genetic Counseling Intervention
#> journal
#> 1 Biostatistics
#> 2 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
#> 3 Scientific Reports
#> 4 Journal of Neuroimaging
#> 5 Neuro-Oncology
#> 6 Journal of Genetic Counseling
#> description
#> 1 Article
#> 2 Conference Paper
#> 3 Article
#> 4 Article
#> 5 Article
#> 6 Article
unique(res$au_id)
#> [1] "40462056100"
unique(as.character(res$affilname_1))
#> [1] "Johns Hopkins Bloomberg School of Public Health"
#> [2] "Johns Hopkins University"
#> [3] "Departments of Biostatistics"
#> [4] "Kennedy Krieger Institute"
#> [5] "Johns Hopkins Medical Institutions"
#> [6] "The Johns Hopkins School of Medicine"
all_dat = author_data(last_name = "Muschelli",
first_name = "John", verbose = FALSE, general = TRUE)
res2 = all_dat$df
res2 = res2 %>%
rename(journal = `prism:publicationName`,
title = `dc:title`,
description = `dc:description`)
head(res[, c("title", "journal", "description")])
#> title
#> 1 Neuroconductor: An R platform for medical imaging analysis
#> 2 MIMoSA: An Approach to automatically segment T2 hyperintense and T1 hypointense lesions in multiple sclerosis
#> 3 Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
#> 4 MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions
#> 5 Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma
#> 6 Feasibility of Coping Effectiveness Training for Caregivers of Children with Autism Spectrum Disorder: a Genetic Counseling Intervention
#> journal
#> 1 Biostatistics
#> 2 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
#> 3 Scientific Reports
#> 4 Journal of Neuroimaging
#> 5 Neuro-Oncology
#> 6 Journal of Genetic Counseling
#> description
#> 1 Article
#> 2 Conference Paper
#> 3 Article
#> 4 Article
#> 5 Article
#> 6 ArticleUsing an Institution Token
As per https://dev.elsevier.com/tecdoc_api_authentication.html: “Using a proprietary token (an”Institutional Token“) created for you by our integration support team”, so you need to contact Scopus to get one. If you have one and it’s located in an object called token, you should be able to use it as:
# token is from Scopus dev
hdr = inst_token_header(token)
res = author_df(last_name = "Muschelli", first_name = "John", verbose = FALSE, general = FALSE, headers = hdr)but I have not tried it extensively.