--- title: "pubmedR" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{pubmedR: A brief example} %\VignetteEngine{knitr::rmarkdown} \usepackage[utf8]{inputenc} --- ## An R-package to gather bibliographic data from PubMed.   The goal of pubmedR is to gather metadata about publications, grants and clinical trials from PubMed database using NCBI REST APIs.   *http://github.com/massimoaria/pubmedR* *Latest version: `r packageVersion("pubmedR")`, `r Sys.Date()`*   **by Massimo Aria** Full Professor in Social Statistics PhD in Computational Statistics Laboratory and Research Group STAD Statistics, Technology, Data Analysis Department of Economics and Statistics University of Naples Federico II email aria@unina.it http://www.massimoaria.com   ## Installation You can install the developer version of the pubmedR from [GitHub](https://github.com) with: install.packages("devtools") devtools::install_github("massimoaria/pubmedR") You can install the released version of pubmedR from [CRAN](https://CRAN.R-project.org) with: install.packages("pubmedR")     ## Load the package library(pubmedR)     # A brief example Imagine, we want to download a metadata collection of journal articles which (1) have used bibliometric approaches in their researches, (2) have been published for the past 20 years (3) and have been written in the English language. The workflow mainly consists of four steps: 1. Write the query 2. Check the effectiveness of the query 3. Download the collection of document metadata 4. Convert the download object into a "readable" and and "usable" format   By default, the access to NCBI API system is free and does not necessarily require an "API key". In this case, NCBI limits users to making only 3 requests per second. Users who register for an “API key” are able to make up to ten requests per second. Obtaing a key is very simple, you just need to register for ***“my ncbi account”*** (*https://www.ncbi.nlm.nih.gov/account/*) then click on a button in the ***"account settings page"*** (*https://www.ncbi.nlm.nih.gov/account/settings/*). Once you have an API key, set the argument api_key="*your API key*" otherwise api_key="*NULL*": # if you have got an API key api_key <- "your API key" # if you haven't got an API key api_key = NULL   ## First step: Write a query First of all, we define a query to submit at the NCBI PubMed system. For example, imagine we want to download a collection of journal articles using bibliometric analyses, published in the last 20 years in the English language. Translating in the query language, we have to set the following statements: - *documents containing the word bibliometric and its variations in their title or abstract:* **"bibliometric\*[Title/Abstract]"** - *documents are written in the English language:* **"english[LA]"** - *documents that are categorized as Journal Article:* **"Journal Article[PT]"** - *documents published from 2000 to 2020:* **"2000:2020[DP]"** Combining all these elements using the Boolean operator "AND", we obtain the final query: query <- "bibliometric*[Title/Abstract] AND english[LA] AND Journal Article[PT] AND 2000:2020[DP]"   ## Second step: Check the effectiveness of the query Now, we want to know how many documents could be retrieved by our query. To do that, we use the function pmQueryTotalCount: res <- pmQueryTotalCount(query = query, api_key = api_key) res$total_count # [1] 2921 D$query_translation [1] "(bibliometric[Title/Abstract] OR bibliometrica[Title/Abstract] OR bibliometrical[Title/Abstract] OR bibliometrically[Title/Abstract] OR bibliometricas[Title/Abstract] OR bibliometrician[Title/Abstract] OR bibliometricians[Title/Abstract] OR bibliometricly[Title/Abstract] OR bibliometrico[Title/Abstract] OR bibliometricos[Title/Abstract] OR bibliometrics[Title/Abstract] OR bibliometrics'[Title/Abstract] OR bibliometricsmethod[Title/Abstract] OR bibliometricstrade[Title/Abstract]) AND english[LA] AND Journal Article[PT] AND 2000[PDAT] : 2020[PDAT]"   ## Third step: Download the collection of document metadata We could decide to change the query or continue to download the whole collection or a part of it (setting the limit argument lower than res$total_count). Image, we decided to download the whole collection composed by 2921 documents: D <- pmApiRequest(query = query, limit = res$total_count, api_key = NULL) # Documents 200 of 2921 # Documents 400 of 2921 # Documents 600 of 2921 # Documents 800 of 2921 # Documents 1000 of 2921 # Documents 1200 of 2921 # Documents 1400 of 2921 # Documents 1600 of 2921 # Documents 1800 of 2921 # Documents 2000 of 2921 # Documents 2200 of 2921 # Documents 2400 of 2921 # Documents 2600 of 2921 # Documents 2800 of 2921 # Documents 2921 of 2921 The function pmApiRequest returns a list D composed by 5 objects: - "data". It is the xml-structured list containing the bibliographic metadata collection downloaded from the PubMed database. - "query". It a character object containing the original query formulated by the user. - "query_translation". It a character object containing the query, translated by the NCBI Automatic Terms Translation system and submitted to the PubMed database. - "records_downloaded". It is an integer object indicating the total number of records downloaded and stored in "data". - "total_counts". It is an integer object indicating the total number of records matching the query (stored in the "query_translation" object").   ## Fourth step: Convert the download object into a "readable" and and "usable" format ### From the xml-structured object to a "classical" data frame Finally, we transform the xml-structured object D into a data frame, with cases corresponding to documents and variables to Field Tags as used in the **bibliometrix R package** (https://CRAN.R-project.org/package=bibliometrix, https://bibliometrix.org/, https://github.com/massimoaria/bibliometrix). M <- pmApi2df(D) str(M) # 'data.frame': 2918 obs. of 27 variables: # $ AU : chr "DU L;LUO S;LIU G;WANG H;ZHENG L;ZHANG Y" "DUAN L;ZHU G" "YANG C;WANG X;TANG X;BAO X;WANG R" "FERHATOGLU SY;YAPICI N" ... # $ AF : chr "DU, LIANG;LUO, SHANXIA;LIU, GUINA;WANG, HAO;ZHENG, LINGLI;ZHANG, YONGGANG" "DUAN, LI;ZHU, GANG" "YANG, CHENGXIAN;WANG, XUE;TANG, XIAOLI;BAO, XINJIE;WANG, RENZHI" "FERHATOGLU, S YıLMAZ;YAPICI, N" ... # $ TI : chr "THE 100 TOP-CITED STUDIES ABOUT PAIN AND DEPRESSION." "MAPPING THEME TRENDS AND KNOWLEDGE STRUCTURE OF MAGNETIC RESONANCE IMAGING STUDIES OF SCHIZOPHRENIA: A BIBLIOME"| __truncated__ "RESEARCH TRENDS OF STEM CELLS IN ISCHEMIC STROKE FROM 1999 TO 2018: A BIBLIOMETRIC ANALYSIS." "A BIBLIOMETRIC ANALYSIS OF THE ARTICLES FOCUSING ON THE SUBJECT OF BRAIN DEATH PUBLISHED IN SCIENTIFIC CITATION"| __truncated__ ... # $ SO : chr "FRONTIERS IN PSYCHOLOGY" "FRONTIERS IN PSYCHIATRY" "CLINICAL NEUROLOGY AND NEUROSURGERY" "TRANSPLANTATION PROCEEDINGS" ... # $ SO_CO : chr "SWITZERLAND" "SWITZERLAND" "NETHERLANDS" "UNITED STATES" ... # $ LA : chr "ENG" "ENG" "ENG" "ENG" ... # $ DT : chr "JOURNAL ARTICLE" "JOURNAL ARTICLE" "JOURNAL ARTICLE" "JOURNAL ARTICLE" ... # $ DE : chr "BIBLIOMETRIC REVIEW;CITATION;CITATION ANALYSIS;DEPRESSION;PAIN;TOP-CITED" "BIBLIOMETRIC ANALYSIS;CO-OCCURRENCE ANALYSIS;MAGNETIC RESONANCE IMAGING;SCHIZOPHRENIA;SOCIAL NETWORK ANALYSIS;S"| __truncated__ "BIBLIOMETRICS;ISCHEMIC STROKE;PUBLICATIONS;STEM CELLS;VOSVIEWER" "" ... # $ ID : chr "" "" "" "" ... # $ MESH : chr "" "" "" "" ... # $ AB : chr "WITH THE ESTIMATED HIGH PREVALENCE IN THE POPULATION, THE TWO SYMPTOMS OF PAIN AND DEPRESSION THREATEN THE WELL"| __truncated__ "RECENTLY, MAGNETIC RESONANCE IMAGING (MRI) TECHNOLOGY HAS BEEN WIDELY USED TO QUANTITATIVELY ANALYZE BRAIN STRU"| __truncated__ "MANY STUDIES HAVE EVALUATED THE SAFETY AND EFFICACY OF STEM CELLS AS THERAPEUTIC AGENTS FOR ISCHEMIC STROKE. WE"| __truncated__ "ALTHOUGH THE TOPIC OF BRAIN DEATH (BD) HAS BEEN INCREASING IN POPULARITY CONSIDERABLY IN RECENT YEARS BY THE SN"| __truncated__ ... # $ C1 : chr "DEPARTMENT OF PERIODICAL PRESS AND NATIONAL CLINICAL RESEARCH CENTER FOR GERIATRICS, WEST CHINA HOSPITAL, SICHU"| __truncated__ "DEPARTMENT OF PSYCHIATRY, THE FIRST AFFILIATED HOSPITAL OF CHINA MEDICAL UNIVERSITY, SHENYANG, CHINA.;DEPARTMEN"| __truncated__ "DEPARTMENT OF NEUROSURGERY, PEKING UNION MEDICAL COLLEGE HOSPITAL, PEKING UNION MEDICAL COLLEGE & CHINESE ACADE"| __truncated__ "DEPARTMENT OF ANESTHESIOLOGY AND REANIMATION, UNIVERSITY OF HEALTH SCIENCES DR. SIYAMI ERSEK TRAINING AND RESEA"| __truncated__ ... # $ CR : chr "NA" "NA" "NA" "NA" ... # $ TC : num 0 0 0 0 0 0 0 0 0 0 ... # $ SN : chr "1664-1078" "1664-0640" "1872-6968" "1873-2623" ... # $ J9 : chr "FRONT PSYCHOL" "FRONT PSYCHIATRY" "CLIN NEUROL NEUROSURG" "TRANSPLANT. PROC." ... # $ JI : chr "FRONT PSYCHOL" "FRONT PSYCHIATRY" "CLIN NEUROL NEUROSURG" "TRANSPLANT. PROC." ... # $ PY : num 2019 2020 2020 2020 2020 ... # $ VL : chr "10" "11" "192" NA ... # $ DI : chr "10.3389/fpsyg.2019.03072" "10.3389/fpsyt.2020.00027" "10.1016/j.clineuro.2020.105740" "10.1016/j.transproceed.2020.01.034" ... # $ PG : chr "3072" "27" "105740" NA ... # $ UT : chr "32116876" "32116844" "32114325" "32111384" ... # $ PMID : chr "32116876" "32116844" "32114325" "32111384" ... # $ DB : chr "PUBMED" "PUBMED" "PUBMED" "PUBMED" ... # $ AU_UN : chr "DEPARTMENT OF PERIODICAL PRESS AND NATIONAL CLINICAL RESEARCH CENTER FOR GERIATRICS, WEST CHINA HOSPITAL, SICHU"| __truncated__ "DEPARTMENT OF PSYCHIATRY, THE FIRST AFFILIATED HOSPITAL OF CHINA MEDICAL UNIVERSITY, SHENYANG, CHINA.;DEPARTMEN"| __truncated__ "DEPARTMENT OF NEUROSURGERY, PEKING UNION MEDICAL COLLEGE HOSPITAL, PEKING UNION MEDICAL COLLEGE & CHINESE ACADE"| __truncated__ "DEPARTMENT OF ANESTHESIOLOGY AND REANIMATION, UNIVERSITY OF HEALTH SCIENCES DR. SIYAMI ERSEK TRAINING AND RESEA"| __truncated__ ... # $ AU_CO : chr "NA" "NA" "NA" "NA" ... # $ AU1_CO: chr "NA" "NA" "NA" "NA" ...   ## An overview to the collection using bibliometrix Now, we can use some bibliometrix functions to get an overview of the bibliographic collection. bibliometrix is an R-tool for quantitative research in scientometrics and bibliometrics that includes all the main bibliometric methods of analysis (https://CRAN.R-project.org/package=bibliometrix, https://bibliometrix.org/, https://github.com/massimoaria/bibliometrix). First, we install and load the bibliometrix package: install.packages("bibliometrix") library(bibliometrix)   ### Main information about the collection Then, we add some metadata to the pubmed collection, and we use the biblioAnalysis and summary functions to perform a descriptive analysis of the data frame: M <- convert2df(D, dbsource = "pubmed", format = "api") results <- biblioAnalysis(M) summary(results) # Main Information about data # # Documents 2918 # Sources (Journals, Books, etc.) 1275 # Keywords Plus (ID) 2245 # Author's Keywords (DE) 4212 # Period 2000 - 2020 # Average citations per documents 0 # # Authors 8854 # Author Appearances 12928 # Authors of single-authored documents 229 # Authors of multi-authored documents 8625 # Single-authored documents 307 # # Documents per Author 0.33 # Authors per Document 3.03 # Co-Authors per Documents 4.43 # Collaboration Index 3.31 # # Document types # BIOGRAPHY 4 # CASE REPORTS 2 # COMMENT 8 # COMPARATIVE STUDY 97 # EDITORIAL 2 # ENGLISH ABSTRACT 1 # EVALUATION STUDY 19 # HISTORICAL ARTICLE 82 # INTRODUCTORY JOURNAL ARTICLE 2 # JOURNAL ARTICLE 2694 # LETTER 3 # REVIEW 4 # # # Annual Scientific Production # # Year Articles # 2000 10 # 2001 8 # 2002 10 # 2003 16 # 2004 18 # 2005 27 # 2006 37 # 2007 24 # 2008 43 # 2009 58 # 2010 73 # 2011 93 # 2012 121 # 2013 158 # 2014 172 # 2015 225 # 2016 254 # 2017 276 # 2018 380 # 2019 544 # 2020 159 # # Annual Percentage Growth Rate 14.83383 # # # Most Productive Authors # # Authors Articles Authors Articles Fractionalized # 1 SWEILEH WM 62 SWEILEH WM 25.40 # 2 ZYOUD SH 59 ZYOUD SH 18.74 # 3 AL-JABI SW 48 HO YS 13.89 # 4 HO YS 34 AL-JABI SW 13.00 # 5 YOON DY 27 HUH S 9.33 # 6 SAWALHA AF 26 BORNMANN L 9.29 # 7 WANG Y 26 SMITH DR 9.00 # 8 ZHANG Y 24 ÅŽENEL E 7.70 # 9 BORNMANN L 22 YEUNG AWK 6.22 # 10 KHOSA F 22 SHAMIM T 6.00 # # # Top manuscripts per citations # # Paper TC TCperYear # 1 DU L, 2019, FRONT PSYCHOL 0 0 # 2 DUAN L, 2020, FRONT PSYCHIATRY 0 0 # 3 YANG C, 2020, CLIN NEUROL NEUROSURG 0 0 # 4 FERHATOGLU SY, 2020, TRANSPLANT. PROC. 0 0 # 5 CHEN L, 2020, PHYTOMEDICINE 0 0 # 6 KUNZE KN, 2020, AM J SPORTS MED 0 0 # 7 CUOCOLO R, 2020, INSIGHTS IMAGING 0 0 # 8 WU M, 2020, J. MATERN. FETAL. NEONATAL. MED. 0 0 # 9 LEE IS, 2020, J PAIN RES 0 0 # 10 SANT'ANNA FH, 2020, INT. J. SYST. EVOL. MICROBIOL. 0 0 # # # Corresponding Author's Countries # # Country Articles Freq SCP MCP MCP_Ratio # 1 NA 2918 1 2918 0 0 # # # SCP: Single Country Publications # # MCP: Multiple Country Publications # # # Total Citations per Country # # Country Total Citations Average Article Citations # 1 NA 0 0 # # # Most Relevant Sources # # Sources Articles # 1 PLOS ONE 106 # 2 SCIENTOMETRICS 67 # 3 WORLD NEUROSURGERY 55 # 4 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 36 # 5 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 34 # 6 MEDICINE 31 # 7 NEURAL REGENERATION RESEARCH 29 # 8 BMJ OPEN 26 # 9 JOURNAL OF THE MEDICAL LIBRARY ASSOCIATION : JMLA 26 # 10 PEERJ 25 # # # Most Relevant Keywords # # Author Keywords (DE) Articles Keywords-Plus (ID) Articles # 1 BIBLIOMETRICS 667 BIBLIOMETRICS 1545 # 2 BIBLIOMETRIC ANALYSIS 331 HUMANS 1518 # 3 BIBLIOMETRIC 172 PERIODICALS AS TOPIC 592 # 4 CITATION ANALYSIS 123 BIOMEDICAL RESEARCH 483 # 5 H INDEX 97 PUBLISHING 419 # 6 PUBLICATIONS 84 JOURNAL IMPACT FACTOR 323 # 7 CITATIONS 81 PUBLICATIONS 252 # 8 CITATION 69 RESEARCH 252 # 9 WEB OF SCIENCE 66 UNITED STATES 219 # 10 SCIENTOMETRICS 64 FEMALE 174 ```