---
title: "Economics of open science"
chunk: 13/15
source: "https://en.wikipedia.org/wiki/Economics_of_open_science"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:49:05.253185+00:00"
instance: "kb-cron"
---

=== Research efficiency ===
Impacts of open science on research efficiency stem from the benefits of enhanced access to previous work. Due to the complexity of bibliography search, closed subscription system "can lead to high levels of duplication—that is, where separate teams work on the same thing unbeknownst to each other." The issue is not limited to academic research, but affect industrial R&D as well: "an analysis of pharmaceutical patents by 18 large companies showed that 86% of target compounds were investigated by two or more companies" Non-publication of data or intermediary results can also have cascading effects on the overall quality of research. Meta-analysis rely on the reproductibility of pre-existent observations and experiments to identify the scientific consensus on a specific topic or field of research. They can be affected by statistical errors and bias, as well as the pre-selection of statistically significant results. Extensive opening of final and intermediary data sources makes it easier to spot potential mistakes.
Text and data mining projects have more recently become a major focus of studies on potential gain of research efficiency. In contrast with the standard procedures of state of the art, text mining projects process very large corpus and are bound to be limited by the available collections in academic libraries. Additionally, special authorization has to be given from the publishers unless the corpus is published in a free license, as the proper use of automated analyses require making copies accessible among project members. Access procedures may represent a significant investment for text mining projects: "As well as the costs and time required to reach such agreements, it also introduces significant uncertainty into such projects as it is possible that some agreements may not be reached". In 2021, a quantitative analysis of text and data mining research showed that "there is strong evidence that the share of DM research in total research output increases, where researchers do not need to acquire specific consent by rights holders". The restrictive effect of the lack of open access or text and data mining exception is sufficiently noticeable to highlight "an adverse net effect of IP on innovation, in the sense that there is strong evidence for stricter copyright hindering the wide adoption of novel ways to build on copyright works and generate derivative works." In 2012, a JISC report estimated that a facilitated use of text and data mining tools, notably in the context of bibliographic search, could generate significant gains of productivity: "if text mining enabled just a 2% increase in productivity – corresponding to only 45 minutes per academic per working week (...) this would imply over 4.7 million working hours and additional productivity worth between £123.5m and £156.8m in working time per year."