Scopus API in Matlab

by Anastasia Ramig

These recipe examples use the Elsevier Scopus API. Code was tested with MATLAB R2021b and sample data downloaded from the Scopus API on April 26, 2022 via http://api.elsevier.com and http://www.scopus.com. This tutorial content is intended to help facillitate academic research. Before continuing or reusing any of this code, please be aware of Elsevier’s API policies and appropiate use-cases. You will also need to register for an API key in order to use the Scopus API.

Setup

We will start by setting up the API key. Save your key in a text file in the same directory as the current Matlab folder and import your key as follows:

%% import API key from file
myAPIKey = importdata("apiKey.txt");

1. Get Author Data

Number of Records for Author

%% setup API information and pull data
api_url = "https://api.elsevier.com/content/search/scopus?query=";
author_id = "AU-ID(55764087400)&apiKey=";
q = webread(api_url + author_id + myAPIKey)

Output:

q = struct with fields:
   search_results: [1x1 struct]

%% create an array of ones to pre-allocate doi_list
doi_list = {ones(length(q.search_results.entry), 1)};

%% create a list of dois from the data
for i = 1:length(q.search_results.entry)
   doi_list{i} = q.search_results.entry{i,1}.prism_doi;
end
doi_list

Output:

doi_list = 1x20 cell
'10.1021/acs.jchemed.1c00904''10.5860/crln.82.9.428''10.1021/acs.iecr.8b02573''10.1021/acs.jchemed.6b00602''10.5062/F4TD9VBX''10.1021/acs.macromol.6b02005''10.1186/s13321-016-0181-z''10.1021/acs.chemmater.5b04431''10.1021/acs.jchemed.5b00512''10.1021/acs.jchemed.5b00375''10.5860/crln.76.9.9384''10.5860/crln.76.2.9259''10.1021/ed400887t''10.1016/j.acalib.2014.03.015''10.5062/F4XS5SB9''10.1021/ma300328u''10.1021/mz200108a''10.1021/ma201170y''10.1021/ma200184u''10.1021/cm102374t'

%% create an array of ones to pre-allocate titles_list
titles_list = {ones(length(q.search_results.entry), 1)};

%% create a list of titles from the data
for i = 1:length(q.search_results.entry)
   titles_list{i} = q.search_results.entry{i,1}.dc_title;
end
titles_list

Output:

titles_list = 1x20 cell
'Using NCBI Entrez Direct (EDirect) for Small Molecule Chemical Informati…  'Using the linux operating system full-time tips and experiences from a s…  'Analysis of the Frequency and Diversity of 1,3-Dialkylimidazolium Ionic …  'Rapid Access to Multicolor Three-Dimensional Printed Chemistry and Bioch…  'Text analysis of chemistry thesis and dissertation titles''Phototunable Thermoplastic Elastomer Hydrogel Networks''Programmatic conversion of crystal structures into 3D printable files us…  'Dangling-End Double Networks: Tapping Hidden Toughness in Highly Swollen…  'Replacing the Traditional Graduate Chemistry Literature Seminar with a C…  '3D Printed Block Copolymer Nanostructures''Hypotheses in librarianship: Applying the scientific method''Recruiting students to campus: Creating tangible and digital products in…  '3D printed molecules and extended solid models for teaching symmetry and…  'Repurposing Space in a Science and Engineering Library: Considerations f…  'A model for managing 3D printing services in academic libraries''Morphological phase behavior of poly(RTIL)-containing diblock copolymer …  'Network formation in an orthogonally self-assembling system''Access to nanostructured hydrogel networks through photocured body-cente…  'Synthesis and ordered phase separation of imidazolium-based alkyl-ionic …  'Thermally stable photocuring chemistry for selective morphological trapp…

%% create an array of ones to pre-allocate citedby_count
citedby_count = {ones(length(q.search_results.entry), 1)};

%% create a list of counts of how much each title was cited
for i = 1:length(q.search_results.entry)
   citedby_count{i} = q.search_results.entry{i,1}.citedby_count;
end
citedby_count

Output:

citedby_count = 1x20 cell
'0'          '0'          '17'         '25'         '5'          '11'         '20'         '6'          '10'         '25'         '0'          '0'          '98'         '6'          '34'         '40'         '31'         '18'         '45'         '11'

%% find the total number of cites
citesTotal = str2double(citedby_count);
totalCites = sum(citesTotal)

Output:

totalCites = 402

2. Get Author Data in a Loop

Number of Records for Author

%% import author text data as a cell array
authorList = importdata("authorData.txt")

Output:

authorList = 5x1 cell
'{Emy Decker, 36660678600}'
'{Lindsey Lowry, 57210944451}'
'{Karen Chapman, 35783926100}'
'{Kevin Walker, 56133961300}'
'{Sara Whitver, 57194760730}'

%% create a list of author names and delete the extra bracket from it
authorList2 = cellfun(@(x) strsplit(x, ","), authorList, 'UniformOutput', false);
for i = 1:length(authorList2)
   str = authorList2{i, 1}{1, 1};
   old = "{";
   new = "";
   authorList2{i, 1}{1, 1} = replace(str, old, new);
end

%% extract the author ids
author_ids = {ones(length(authorList2), 1)};
for i = 1:length(authorList2)
   pat = digitsPattern;
   author_ids{i} = extract(authorList2{i, 1}{1, 2}, pat);
end

%% preallocate an array for the number of records
numRecords = {ones(length(author_ids), 1)};

%% find the number of records for each author and add it to the author list
for i = 1:length(numRecords{1, 1})
   q1 = webread(api_url + "AU-ID(" + author_ids{1, i} + ")&apiKey=" + myAPIKey);
   numRecords{i} = length(q1.search_results.entry);
   pause(1)
   authorList2{i, 1}{1, 3} = numRecords{i};
end
disp(cell2table(authorList2))

Output:

                     authorList2
________________________________________________

{'Emy Decker'   }    {' 36660678600}'}    {[14]}
{'Lindsey Lowry'}    {' 57210944451}'}    {[ 4]}
{'Karen Chapman'}    {' 35783926100}'}    {[25]}
{'Kevin Walker' }    {' 56133961300}'}    {[ 8]}
{'Sara Whitver' }    {' 57194760730}'}    {[ 4]}

Get Record Data

clear info
%% extract the dois and cites for each author
for i = 1:length(author_ids)
   q_records = webread(api_url + "AU-ID(" + author_ids{1, i}+")&apiKey=" + myAPIKey);
   n = length(q_records.search_results.entry);

   %% preallocate cell array for the dois and cites
   doiList = cell(1, length(author_ids));
   citeList = cell(1, length(author_ids));
   for k = 1:n
      try
            doiList{1, i}{k, 1} = q_records.search_results.entry{k, 1}.prism_doi;
            citeList{1, i}{k, 1} = q_records.search_results.entry{k, 1}.citedby_count;
      catch
      end
   end
   pause(1)

   %% add the dois and cites to an overall information array
   info{1, 1}{1, i} = doiList{1, i};
   info{2, 1}{1, i} = citeList{1, i};
end

%% create arrays for the dois and cites
dois = {};
cites = {};
for i = 1:width(info{1, 1})
   dois = vertcat(dois, info{1, 1}{1, i});
   cites = vertcat(cites, info{2, 1}{1, i});
end

%% create a conclusive array
authorArray = horzcat(dois, cites);
nameArray = {};

%% create an array of author names
for i = 1:(length(numRecords))
   nameLength = int16(numRecords{i});
   authorName = cellstr(repmat(authorList2{i, 1}{1, 1}, nameLength, 1));
   nameArray = vertcat(nameArray, authorName);
end

%% add the author names to the informational array
authorArray = horzcat(authorArray, nameArray)

Output:

authorArray = 55x3 cell
   1 2       3
1    '10.1108/RSR-08-2021-0051'      '0'     'Emy Decker'
2    '10.1080/1072303X.2021.1929642' '0'     'Emy Decker'
3    '10.1080/15367967.2021.1900740' '8'     'Emy Decker'
4    '10.1080/15367967.2020.1826951' '0'     'Emy Decker'
5    '10.1080/10691316.2020.1781725' '0'     'Emy Decker'
6    '10.1145/3347709.3347805'       '0'     'Emy Decker'
7    '10.4018/978-1-5225-5631-2.ch09'        '3'     'Emy Decker'
...
...
...

Save Record Data to a file

%% save the search for each author to a mat file
for author = 1:length(author_ids)
   authorName = authorList2{author, 1}{1, 1};
   q2 = webread(api_url + "AU-ID" + "(" + author_ids{1, author} + ")&apiKey=" + myAPIKey);
   pause(1)
   filename = authorName + ".mat";
   save filename q2;
end

%% save the author arrays to individual text files
for i = 1:(length(numRecords))
   clear individualAuthorData;
   individualDois = info{1, 1}{1, i};
   individualCites = info{2, 1}{1, i};

   nameLength = int16(numRecords{i});
   authorName = cellstr(repmat(authorList2{i, 1}{1, 1}, nameLength, 1));

   individualAuthorData = horzcat(individualDois, individualCites);
   individualAuthorData = horzcat(individualAuthorData, authorName);

   writecell(individualAuthorData, (authorList2{i, 1}{1, 1} + ".txt"), "Delimiter", "\t");
end

3. Get References via a Title Search

Number of Title Match Records

Search Scopus for all references containing ‘ChemSpider” in the record title.

%% set up the API information
api_url = "https://api.elsevier.com/content/search/scopus?query=";
author_id = "TITLE(ChemSpider)&apiKey=";

%% find the information for ChemSpider and get the total number of results
q3 = webread(api_url + author_id + myAPIKey);
q3.search_results.opensearch_totalResults

Repeat this in a loop to get number of Scopus records for each title search.

%% create a list of titles
titleList = ["ChemSpider", "PubChem", "ChEMBL", "Reaxys", "SciFinder"];
length(titleList)

%% create an array of ones to pre-allocate numRecordsTitle
clear numRecordsTitle
numRecordsTitle = {ones(length(titleList), 1)};

%% obtain the number of records for each title in the list and create an array
for i = 1:length(titleList)
   qt = webread(api_url + "TITLE(" + titleList(i) + ")&apiKey=" + myAPIKey);
   numt = qt.search_results.opensearch_totalResults;
   numRecordsTitle{1, i}{1, 1} = titleList(i);
   numRecordsTitle{1, i}{1, 2} = numt;
   pause(1)
end

Download Title Match Record Data

Download records and create a list of selected metadata.

%% create a list of titles and preallocate an array
titleList = ["ChemSpider", "PubChem", "ChEMBL", "Reaxys", "SciFinder"];
scopusTitleData = {ones(length(titleList), 1)};
%% find the dois, titles, and dates for each title in the list and put them into an array
for t = 1:length(titleList)
   qt = webread(api_url + "TITLE(" + titleList(t) + ")&apiKey=" + myAPIKey);
   n = length(qt.search_results.entry);
   doiTitles = cell(1, length(titleList));
   titles = cell(1, length(titleList));
   dates = cell(1, length(titleList));
   for k = 1:n
      try
            doiTitles{1, t}{k, 1} = qt.search_results.entry{k, 1}.prism_doi;
            titles{1, t}{k, 1} = qt.search_results.entry{k, 1}.dc_title;
            dates{1, t}{k, 1} = qt.search_results.entry{k, 1}.prism_coverDate;
      catch
      end
   end
   pause(1)
   infoTitles{1, 1}{1, t} = doiTitles{1, t};
   infoTitles{2, 1}{1, t} = titles{1, t};
   infoTitles{3, 1}{1, t} = dates{1, t};
end

%% create an overall array of the information found above
titleDois = {};
titlesFinal = {};
datesFinal = {};
for t = 1:width(info{1, 1})
   titleDois = vertcat(titleDois, infoTitles{1, 1}{1, t});
   titlesFinal = vertcat(titlesFinal, infoTitles{2, 1}{1, t});
   datesFinal = vertcat(datesFinal, infoTitles{3, 1}{1, t});
end
titleArray = horzcat(titleDois, titlesFinal);
titleArray = horzcat(titleArray, datesFinal);
%% create an array of names and add it to the overall array
titlesNameArray = {};
for t = 1:length(titleList)
   nameLength = length(infoTitles{1, 1}{1, t});
   titlesAuthorName = cellstr(repmat(titleList(t), nameLength, 1));
   titlesNameArray = vertcat(titlesNameArray, titlesAuthorName);
end
titleArray = horzcat(titleArray, titlesNameArray)

Output:

   titleArray = 88x4 cell
   1 2       3       4
1    '10.1039/c5np90022k'    'Editorial: ChemSpider-a tool for Natural Products research'    '2015-08-01'    'ChemSpider'
2    '10.1021/bk-2013-1128.ch020'    'ChemSpider: How a free community resource of data can support the teaching of nmr spectroscopy'        '2013-01-01'    'ChemSpider'
3    '10.1007/s13361-011-0265-y'     'Identification of "known unknowns" utilizing accurate mass data and chemspider'        '2012-01-01'    'ChemSpider'
4    '10.1002/9781118026038.ch22'    'Chemspider: A Platform for Crowdsourced Collaboration to Curate Data Derived From Public Compound Databases'   '2011-05-03'    'ChemSpider'
5    '10.1021/ed100697w'     'Chemspider: An online chemical information resource'   '2010-11-01'    'ChemSpider'
6    '10.1016/j.bioorg.2022.105648'  'Structure-based discovery of a specific SHP2 inhibitor with enhanced blood–brain barrier penetration from PubChem database'    '2022-04-01'    'PubChem'
7    '10.1016/j.jmb.2022.167514'     'PubChem Protein, Gene, Pathway, and Taxonomy Data Collections: Bridging Biology and Chemistry through Target-Centric Views of PubChem Data'    '2022-01-01'    'PubChem'
8    '10.1007/s40011-021-01335-x'    'Identification a Novel Inhibitor for Aldo–Keto Reductase 1 C3 by Virtual Screening of PubChem Database'        '2022-01-01'    'PubChem'
9    '10.1007/978-1-0716-2067-0_27'  'Plant Reactome and PubChem: The Plant Pathway and (Bio)Chemical Entity Knowledgebases' '2022-01-01'    'PubChem'
10   '10.1016/j.molstruc.2021.130968'        '3CL<sup>pro</sup> and PL<sup>pro</sup> affinity, a docking study to fight COVID19 based on 900 compounds from PubChem and literature. Are there new drugs to be found?'        '2021-12-05'    'PubChem'
11   '10.1093/glycob/cwab078'        'Enhancing the interoperability of glycan data flow between ChEBI, PubChem and GlyGen'  '2021-11-01'    'PubChem'
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