Capturing Trends Using OpenAlex and Wikipedia Page Views as Science Indicators: The Case of Data Protection and Encryption Technologies

Abstract

This paper presents a novel science indicator to identify, analyze, and capture technology trends based on Wikipedia page views and OpenAlex presented at STI2022. Our webometric methodology is grounded in open science practices and applied to crowd-sourced, open, and free data. We explore the relationships between 36 data protection and encryption technologies, by measuring and classifying their time-varying attention. These highly research-intensive technologies are particularly suitable to illustrate our approach. We first find that Blockchain, Hash Function, and Asymmetric Encryption are the technologies that generate significant public interest. Conversely, niche or longstanding technologies such as Disk Encryption and Email Encryption are considered low-interest technologies with no growth. Our findings suggest that monitoring public attention on Wikipedia can serve as a scientific indicator to provide valuable information on technology trends and inform decision-making related to investment, assessment, and technology road-mapping.