Work

Model for selecting big data technology infrastructures for Science and Technology Institutions: Quality requirements and metrics

Year: 2024

Type: article

Abstract: This work aims to present a conceptual model for selecting big data technology infrastructures for Science and Technology institutions (STIs) based on a multicriteria approach, including specific criteria and metrics applied to the referred context. Big data refers to large datasets in organizations, in general, and STIs, in particular, that operate with large and rapidly growing volumes of diverse data. Unlike traditional operational databases, big data technologies are not formally modelled for query and retrieval and are not accompanied by detailed metadata. Based on this conceptualization and literature review, multicriteria decision-making methods (MCDM) were compared to justify choosing a hybrid methodological approach for the modelling phase. In summary, the application of the proposed model for selecting big data technology infrastructures for STIs can be used as a practical guide, indicating the best scenarios for the provision of these infrastructures for the future of research and development (R&D) management.

Source: Measurement Sensors

DOI: 10.1016/j.measen.2024.101530

Authors: Elias de Morais Paes, Maria Fatima Ludovico de Almeida

Institution: Pontifícia Universidade Católica do Rio de Janeiro

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,800