The pros and cons of the use of altmetrics in research assessment

© 2020 The Authors. Published by Levi Library Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: http://doi.org/10.29024/sar.10Many indicators derived from the web have been proposed to supplement citation-based indicators in support of research assessments. These indicators, often called altmetrics, are available commercially from Altmetric.com and Elsevier’s Plum Analytics or can be collected directly. These organisations can also deliver altmetrics to support institutional selfevaluations. The potential advantages of altmetrics for research evaluation are that they may reflect important non-academic impacts and may appear before citations when an article is published, thus providing earlier impact evidence. Their disadvantages often include susceptibility to gaming, data sparsity, and difficulties translating the evidence into specific types of impact. Despite these limitations, altmetrics have been widely adopted by publishers, apparently to give authors, editors and readers insights into the level of interest in recently published articles. This article summarises evidence for and against extending the adoption of altmetrics to research evaluations. It argues that whilst systematicallygathered altmetrics are inappropriate for important formal research evaluations, they can play a role in some other contexts. They can be informative when evaluating research units that rarely produce journal articles, when seeking to identify evidence of novel types of impact during institutional or other self-evaluations, and when selected by individuals or groups to support narrative-based non-academic claims. In addition, Mendeley reader counts are uniquely valuable as early (mainly) scholarly impact indicators to replace citations when gaming is not possible and early impact evidence is needed. Organisations using alternative indicators need recruit or develop in-house expertise to ensure that they are not misused, however

Under the Influence? Intellectual Exchange in Political Science

We study the performance of political science journals in terms of their contribution to intellectual exchange in the discipline. Relying on the interplay of citation patterns, our method is simple, cheap, objective and captures the influence of journals in a meaningful way. We find that the American Political Science Review , World Politics and International Organization lead the field. In contrast to previous sub jective studies, we also find that economics is a key influence on political science, much more so than sociology.Governmen

Hyperspectral imaging combined with data classification techniques as an aid for artwork authentication

In recent years various scientific practices have been adapted to the artwork analysis process. Although a set of techniques is available for art historians and scientists, there is a constant need for rapid and non-destructive methods to empower the art authentication process. In this paper hyperspectral imaging combined with signal processing and classification techniques are proposed as a tool to enhance the process for identification of art forgeries. Using bespoke paintings designed for this work, a spectral library of selected pigments was established and the viability of training and the application of classification techniques based on this data was demonstrated. Using these techniques for the analysis of actual forged paintings resulted in the identification of anachronistic paint, confirming the falsity of the artwork. This paper demonstrates the applicability of infrared (IR) hyperspectral imaging for artwork authentication

Centralization issues in IT governance: The role and responsibilities of the IT Control Officer from a European perspective

The need for transparency in IT governance, due to several factors such as cost and regulatory pressure, has led to organisations putting into place an IT Control Officer to oversee and audit IT activities. This paper examines the initial results of a European CIO-level survey designed to increase the understanding regarding the possible roles of the IT Control Officer and the authority given to that person. This research confirms the intuitive idea that increasing the role of the IT Control Officer also improves IT control. The increasing role in this sense is a more centralised and more senior position with additional responsibilities and administrative controls. This research also examines a perspective on the various intermediate possibilities of decentralised and less senior scenarios

An Examination of Research Data Sharing and Re-Use: Implications for Data Citation Practice

This study examines characteristics of data sharing and data re-use in Genetics and Heredity, where data citation is most common. This study applies an exploratory method because data citation is a relatively new area. The Data Citation Index (DCI) on the Web of Science was selected because DCI provides a single access point to over 500 data repositories worldwide and to over two million data studies and datasets across multiple disciplines and monitors quality research data through a peer review process. We explore data citations for Genetics and Heredity, as a case study by examining formal citations recorded in the DCI and informally by sampling a selection of papers for implicit data citations within publications. Citer-based analysis is conducted in order to remedy self- citation in the data citation phenomena. We explore 148 sampled citing articles in order to identify factors that influence data sharing and data re-use, including references, main text, supplementary data/information, acknowledgments, funding information, author information, and web/author resources. This study is unique in that it relies on a citer-based analysis approach and by analyzing peer-reviewed and published data, data repositories, and citing articles of highly productive authors where data sharing is most prevalent. This research is intended to provide a methodological and practical contribution to the study of data citation

Measuring reseach outputs across borders-a comment

This papers starts from an article published by Chan et al. in Accounting and Business Research in 2006 on accounting research in Europe. It develops the idea that accounting research in Europe is much more diversified than it appears, is not limited to British academics output, and relies upon very diversified vectors (journals or books) across countries. The case of France and Germany are particularly highlighted. More generally, the addresses the question of research evaluation and its consequences on academic communities.Accounting; Control; Research; Europe

The Impact of Research Data Sharing and Reuse on Data Citation in STEM Fields

Despite the open science movement and mandates for the sharing of research data by major funding agencies and influential journals, the citation of data sharing and reuse has not become standard practice in the various science, technology, engineering and mathematics (STEM) fields. Advances in technology have lowered some barriers to data sharing, but it is a socio-technical phenomenon and the impact of the ongoing evolution in scholarly communication practices has yet to be quantified. Furthermore, there is need for a deeper and more nuanced understanding of author self-citation and recitation, the most often cited types of data, disciplinary differences regarding data citation and the extent of interdisciplinarity in data citation. This study employed a mixed methods approach that combined coding with semi-automatic text-searching techniques in order to assess the impact of data sharing and reuse on data citation in STEM fields. The research considered over 500,000 open research data entities, such as datasets, software and data studies, from over 350 repositories worldwide. I also examined 705 bibliographic publications with a total of 15,261 instances of data sharing, reuse, and citation the data, article, discipline and interdisciplinary levels. More specifically, I measured the phenomenon of data sharing in terms of formal data citation, frequently cited data types, and author self-citation, and I explored recitation at the levels of both data- and bibliography-level, and data reuse practices in bibliographies, associations of disciplines, and interdisciplinary contexts. The results of this research revealed, to begin with, disciplinary differences with regard to the impact of data sharing and reuse on data citation in STEM fields. This research also yielded the following additional findings regarding the citation of data by STEM researchers; 1) data sharing practices were diverse across disciplines: 2) data sharing has been increasing in recent years; 3) each discipline made use of major digital repositories; 4) these repositories took various forms depending on the discipline; 5) certain data types were more often cited in each discipline, so that the frequency distribution of the data types was highly skewed; 6) author self-citation and recitation followed similar trends at the data and bibliographic levels, but specific practices varied within each discipline; 7) associations between and across data and author self-citation and recitation at the bibliographic level were observed, with the self-citation rate differing significantly among disciplines;8) data reuse in bibliographies was rare yet diverse; 9) informal citation of data sharing and reuse at the bibliographic level was more common in certain fields, with astronomy/physics showing the highest amount (98%) and technology the lowest (69%); 10) within bibliographic publications, the documentation of data sharing and reuse occurred mainly in the main text; 11) publications in certain disciplines, such as chemistry, computing and engineering, did not attract citations from more than one field (i.e., showed no diversity); and, on the other hand,12) publications in other fields attracted a wide range of interdisciplinary data citations. This dissertation, then, contributes to the understanding of two key areas aspects of the current citation systems. First, the findings have practical implications for individual researchers, decision makers, funding agencies and publishers with regard to giving due credits to those who share their data. Second, this research has methodological implications in terms of reducing the labor required to analyze the full text of associated articles in order to identify evidence of data citation