Ontologies to Reduce Uncertainty in R&D Project Planning

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review


R&D projects often fail to meet predetermined deadlines and budgets, which is due not only to poor organization of the research and development process, but also to the complexity of performance and efficiency evaluation. The evaluation of effectiveness is complicated by the fact that the final result is made up of a sequence of other results. In assessing effectiveness, a significant share of uncertainty lies in the evaluation of labor costs. The aim of the study is to develop tools to reduce information uncertainty and improve the validity of planning decisions for R&D projects. The paper presents ontologies reflecting relationships between R&D processes and activities within processes with R&D results, as well as relationships between R&D results. The purpose of these ontologies is to evaluate the individual stages of the process in terms of performance; to determine the authorship of individual results and, accordingly, to evaluate the work of employees. Models in the form of ontologies and proposed knowledge extraction procedures serve as the basis for the decision support system for R&D project management. With the help of this system the formation of project teams and the allocation of resources to project tasks can be carried out when resolving resource conflicts.
Original languageEnglish
Title of host publicationProceedings of the Fifth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’21)
EditorsS. Kovalev, V. Tarassov, V. Snasel, A. Sukhanov
PublisherSpringer Nature
ISBN (Electronic)978-3-030-87178-9
StatePublished - 2022
Event5th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2021 - Sochi, Russian Federation
Duration: 30 Sep 20214 Oct 2021

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer International Publishing
ISSN (Electronic)2367-3370


Conference5th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2021
Country/TerritoryRussian Federation

Scopus subject areas

  • Artificial Intelligence
  • Information Systems


  • Ontology
  • Research and development
  • Intellectual property
  • Project planning
  • Process evaluation


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