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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>USING LABOR MARKET DATA FOR ANALYSIS AND EDUCATION</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>I. Filozova</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Yu. Gavrilenko</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>A. Ilyina</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>J. Javadzade</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>V. Korenkov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>D. Priakhina</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>T. Velieva</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Dubna State University</institution>
          ,
          <addr-line>Russia, Moscow region, Dubna, 141980, 19 Universitetskaya</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Irina Filozova</institution>
          ,
          <addr-line>Yulia Gavrilenko, Anna Ilyina, Javad Javadzade, Vladimir Korenkov, Daria Priakhina, Tatyana Velieva</addr-line>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Joint Institute for Nuclear Research</institution>
          ,
          <addr-line>Russia, Moscow region, Dubna, 141980, 6 Joliot-Curie</addr-line>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Plekhanov Russian University of Economics</institution>
          ,
          <addr-line>Russia, Moscow, 115093, 36 Stremyanny per</addr-line>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2021</year>
      </pub-date>
      <fpage>5</fpage>
      <lpage>9</lpage>
      <abstract>
        <p>Education systems provide specialists of different levels and specializations for the labor market. However, in the modern dynamic world of artificial intelligence, pandemic, and remote work, the labor market is evolving dramatically from year to year. Universities and colleges must keep track of these changes to adapt educational programs and manage the number of student slots offered for different specializations. Detailed demand statistics from the labor market are a good data source for analysis to gauge current needs and predict future demand. Usually, there is no single source of data on all vacancies and CVs. Therefore, it is necessary to collect, preprocess, analyze and visualize existing fragmented data. In this work, we study different raw data sources, their strong and weak points. A set of basic metrics is proposed to be derived from the data for analysis. Several types of roles are defined as primary users of the aimed system, their features and standard use cases. A conceptual system design is proposed to fulfill the requirements of the labor market analysis task. The evolutionary prototypes of the services are presented.</p>
      </abstract>
      <kwd-group>
        <kwd>labor market</kwd>
        <kwd>monitoring</kwd>
        <kwd>professional standards</kwd>
        <kwd>educational standards</kwd>
        <kwd>informational services</kwd>
        <kwd>Application Programming Interface (API)</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>
        The labor market is a dynamic complex system that influences many different factors, such as
the economic, demographic situation, quality, interests of market participants, technological progress
and digitalization, psychological aspects, etc. The labor market and the vocational education sy stem
are closely related. Ideally, the education system should be able to quickly and adequately adapt to
changes in the labor market in order to meet the real needs of a changing economy. However, reality
does not coincide with the ideal [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. The inadequacy to current market requirements for qualifications
and skills is widespread in developing and developed countries [
        <xref ref-type="bibr" rid="ref2 ref3 ref4 ref5">2-5</xref>
        ]. Therefore, the problem of
analyzing the labor market is multifaceted and relevant for all its participants, since its successful
solution allows the following: to receive up-to-date and reliable information about the labor market; to
assess the level of salary and the degree to which it matches the qualifications and experience of the
company's employees; to implement comprehensive measures for the material motivation of
employees.
      </p>
      <p>
        However, there are factors that complicate labor market analysis. Some of them are the lack of
uniformity in the wording of vacancies by employers and CVs by applicants; a large number of
information sources to be analyzed; the lack of unified systemic approaches to the analysis of the labor
market from the standpoint of changes in the requirements for the qualifications of the manpower and
the reflection of the future needs of the labor market in the content of educational programs. The
problem affects all participants in the labor market: educational organization, employee, student, HR
specialist, federal, regional and local government authorities. The problem consequence is the
difficulty in obtaining an objective assessment of the labor market state, the high work intensity of
labor market analysis. Its successful solution will save the analyst's time, increase the reliability of
information about the labor market and ensure the effective forecasting of labor market needs in
personnel. Labor market information systems are an important tool in the development of labor and
employment policies [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ].
      </p>
    </sec>
    <sec id="sec-2">
      <title>2. Information and analytical platform</title>
      <p>An information and analytical platform for monitoring and forecasting the personnel needs of
the labor market is developed within the Russian Science Foundation grant (project No. 19-71-30008).
This tool is a multifunctional software and hardware complex aimed to support socio-economic
applications, namely, the monitoring, analysis and forecasting of the development of the labor market
in the Russian Federation. The software and hardware platform is designed using open-source
solutions to cover full-cycle data analysis and machine learning experiments, from data gathering to
visualization.</p>
      <p>The platform is based on a set of informational services: Salary Info, Vacancies Info,
Competencies Info, Requirements Info, Responsibilities Info, Downloading Data and Reports,
Analysis of Professional Standards, Reports Configurator.</p>
      <sec id="sec-2-1">
        <title>2.1 Users</title>
        <p>These informational services are focused on the following users: Analyst, User, Operator.</p>
        <p>Analyst reveals the quantitative and qualitative characteristics of the situation on the labor
market to create its social picture in a certain time interval.</p>
        <p>User studies the demand and price of labor in a specific geographic area, taking into account
the education and qualifications of the applicant.</p>
        <p>Operator registers the sources of vacancies in the system, configures the system, i.e. sets
keywords for the search string, sets up the task scheduler; establishes links between the competencies
of the applicant and the requirements for him from the employer.</p>
        <p>Labor market analysts can be regional and local government bodies, recruitment agencies,
educational organizations, HR specialists. Users can be employees, students and interested parties.</p>
      </sec>
      <sec id="sec-2-2">
        <title>2.2 Data &amp; Data Sources</title>
        <p>The main information sources are publications in the media, the Internet, etc. that post the
requirements for candidates for vacancies, specialized resources, such as salary-meters sites, etc. The
data is harvested from open sources. The main data sources are:
●
●
●
●
●
●
●</p>
        <p>HeadHunter official website 一 one of the largest job and employee search sites in the world
(according to the Similarweb rating). The Internet resource contains about 51 million CVs,
1,032 thousand vacancies in the database (https://hh.ru);
SuperJob official website 一 IT-company carrying out the development in the field of
technologies for recruitment and job search (https://www.superjob.ru);
Web portal “Work in Russia” 一 federal state information system of the Federal Service for
Labor and Employment (https://trudvsem.ru);
Official Internet resource of the Ministry of Labor and Social Protection of the Russian
Federation (https://profstandart.rosmintrud.ru/).</p>
        <p>The following data volumes are currently available for analysis for the period from 2015:
Number of Professional Standards: 1,396;
Number of vacancies: ~ 800 thousand/month;</p>
        <p>Total data volume: ~ 10 TB.</p>
      </sec>
      <sec id="sec-2-3">
        <title>2.3 Informational Services</title>
        <p>Salary Service allows an unauthorized user to view information about salaries in the text
(tabular presentation) and graphic form (several kinds of visualization), taking into account the time
interval and region. Figure 1 illustrates the per-region plot for min and max advertised salaries of
researchers.</p>
        <p>Vacancies Service allows an unauthorized user to view information about the most in-demand
vacancies in a specific geographic area (fig. 2) and professional field [fig. 3].</p>
        <p>Competencies Service allows an unauthorized user to receive a report on the demand for
vocational education competencies in the labor market for the selected time interval. It can be useful
for representatives of educational organizations involved in the development and updating of
educational programs since it helps tracking the potential demand for graduates in the labor market.</p>
        <p>Bachelor specialties corresponding to the most demanded vacancies in the labor market for
November 2020 on the example of Plekhanov Russian University of Economics are presented in
figure 4.</p>
        <p>The Top List of Educational Professional Competencies service allows an unauthorized user
to view information about the most in-demand educational professional competencies in the labor
market for a specific time interval. The Top5 list of educational professional competencies for
economic specialties of Plekhanov Russian University of Economics is shown in table 1 (data for
November 2019).
Professional Competence
Ability to apply the basic principles and standards of financial accounting for the
formation of accounting policies and reporting of the organization
Possession of skills in preparing financial statements and understanding the impact of
various methods and methods of financial accounting on the financial results of the
organization
Understanding the role of financial markets and institutions, the ability to analyze
various financial instruments
Possession of methods of making strategic, tactical and operational decisions in the
management of the operational (production) activities of organizations
Ability to develop business plans for the creation and development of new
organizations (areas of activity, products)
% of Demand
27.9%
22.3%
20.7%
14.9%
14.2%</p>
        <p>The “% of Demand” column is the percentage of the number of vacancies in which the
requirements correspond to professional competencies to the total number of vacancies (in a given
professional field).</p>
        <p>The Analysis of Professional Standards service allows an unauthorized user to collate
wordings of the indicators of achievement of educational competencies, positions, duties and labor
functions of an employee (from job descriptions) with extractions from Professional Standards,
concerning with positions, requirements for education and training, labor actions, necessary skills,
knowledge and other characteristics. It will be useful for HR specialists, developers of educational
programs.</p>
        <p>The Reports Configurator service allows an analyst to generate a report on changes in the
labor market in the text and graphic form (histograms and graphs of changes in the studied value),
taking into account the time interval, region and selected indicators (salary, vocational education
competencies, requirements for applicants, duties of the applicant); determine the main quantitative
characteristics of the studied quantity (calculate the main statistical indicators: mathematical
expectation, standard deviation, kurtosis, asymmetry, minimum, maximum, score, coefficient of
variation, variance); highlight the main trends in the development of the indicator and conduct a
primary analytical assessment (build trend models of changes in wages over time, depending on the
selected indicators); analyze the heterogeneity of the territorial distribution of the studied value (divide
regions into clusters, calculate the centroids (mean values) of the clusters and determine their
deviations from the sample mean values).</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>4. Acknowledgement References</title>
      <p>The study was supported by the Russian Science Foundation grant (project No. 19-71-30008).</p>
    </sec>
    <sec id="sec-4">
      <title>3. Conclusion</title>
      <p>In the future, these services will be integrated into a publicly available information and
analytical platform. The creation of the information and analytical platform will expand the ability to
monitor and forecast the situation on the labor market, as well as to analyze staffing needs.</p>
    </sec>
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