Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/33133
Title: A BIBLIOMETRIC OVERVIEW OF OPEN SCIENCE RESEARCH
Authors: Bakas, Nikolaos P. 
Athenodorou, Andreas 
Anastasopoulou, Nana 
Kyprianou, Katerina 
Katsikatsos, George 
Markou, George 
Major Field of Science: Engineering and Technology
Field Category: Mathematics;Computer and Information Sciences
Keywords: Open science;Open access, Reproducibility;Open data;Data sharing;Transparency;Replication
Issue Date: 1-Jan-2023
Source: 9th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, Athens, Greece, 12-–14 June 2023
Conference: ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering 
Abstract: Scientific research exhibits a vast increase in terms of published works, as well as produced data, computer codes, and scientific methods. Accordingly, openness is a modern demand in science, and many efforts occur in this direction. The reproducibility of results, data sharing, transparency, and replication are emerging challenges in research, as by following “open science” principles, the research community, as well as society, obtains beneficial outcomes in the best possible way. In this work, we computationally analyse a large volume of papers related to open science. Particularly, we use the Scopus database and search for papers with the term “open science” in the title, abstract or keywords, within the past ten years. In total 4878 papers were identified, in the following categories: Article (N=2770), Conference paper (N=724), Review (N=646), Editorial (N=188), Note (N=176), Book chapter (N=119), Erratum (N=112), Conference review (N=54), Data paper (N=30), Letter (N=29), Book (N=16), and Short survey (N=14). We start with descriptive statistics of the keywor ds appearing in the papers, and continue with inter-items' associations, by computing the contingency matrix. Accordingly, we calculate the objects' potions on the bibliometric map, by using a novel multidimensional scaling algorithm. In order to verify the associations, we permute the contingency matrix to minimise its bandwidth and plot the resulting clusters of keywor ds. Finally, in order to evaluate the evolution of the terms in recent years, we compute the timeseries of the occurrence of keywords and select the ones exhibiting higher trends, based on linear as well as nonlinear model fit. We also compute the normalised timeseries, in order to subtract the overall increase in scientific output. We discuss significant conclusions on open science research, based on a rigorous computational procedure.
URI: https://hdl.handle.net/20.500.14279/33133
ISSN: 26233347
Type: Conference Papers
Affiliation : National Infrastructures for Research and Technology 
The Cyprus Institute 
University of Pretoria 
Publication Type: Peer Reviewed
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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