Open AccessThe computer-aided system of e-publication contests
Author(s) -
Svetlana Vlasova,
Н. Е. Каленов,
К. Н. Костюк
Publication year - 2020
Publication title -
naučnye i tehničeskie biblioteki
Language(s) - English
Resource type - Journals
eISSN - 2686-8601
pISSN - 1027-3689
DOI - 10.33186/1027-3689-2020-10-119-138
Subject(s) - contest , computer science , world wide web , metadata , the internet , point (geometry) , objectivity (philosophy) , digital library , multimedia , data science , library science , political science , art , philosophy , geometry , mathematics , poetry , literature , epistemology , law
The authors discuss Internet-based contests aimed to reveal high-grade (approved by experts) scientific publications and graduates’ qualifying papers. Such contests are to facilitate science and education. They are held on the federal level or regionally, within an individual discipline or university. Contest performance and objectivity depend significantly on expert board to assess the entries. The modern Inter-net technologies enable to submit digital versions of printed publication and to involve experts of geographically remote regions. This approach is introduced by Direct-Media Publishers that has been the organizer and co-founder of a number of contests of students’, post-graduates’ and scientists’ papers. In 2019, a specialized computer-aided system was designed based on the expert acquisition system operating efficiently at the RAS Library for Natural Sciences. In the expert acquisition system, publications’ information value is assessed by their abstracts with a simple point system. In the contest system, experts shall be submitted to full texts to be assessed in the more complicated way. The system has to be tuned individually to each contest. The system is described in full detail. It supports acquiring and maintaining databases of experts and entries, expertise functionality (study of entries and assessing process), results analysis with marks awarded. The experts database comprises brief information on experts while the entries database comprises publication metadata which enables to identify and classify them within the classification adopted for a contest. The system was tested within 2019 “Science Foundation” and «BeFirst» contests.