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Identification and classification of evaluation indicators for scientific and technical publications and related factors

Authors : Hassan Mahmoudi Topkanlo, Mehrdad CheshmehSohrabi

Introduction

Given the importance of the issue of the widespread impact of scientific and technical publications in today’s world, and the diversity and multiplicity of indicators for measuring these publications, it is a necessity to classify these indicators from different angles and through different tools and methods.

Method

This study used documentary analysis and Delphi technique methods. The members of the Delphi panel were twenty-one experts in metric fields in information science who answered the research questionnaires several times until reaching a consensus.

Analysis

Kendall’s coefficient of concordance and a one-sample t-test were used to measure the agreement of the panel members as raters on the questionnaire items.

Results

A total of thirty-four sub-categories of indicators of assessment were identified which were categorised according to their similarities and differences into eight main categories as follows: measurement method, measurement unit, measurement content, measurement purpose, measurement development, measurement resource, measurability, and measurement environment.

Conclusion

Classification of the indicators of evaluation for scientific and technical publications and related factors can lead to improved understanding, critique, modelling and development of indicators. The findings of this study can be considered a basis for further research and help develop evaluative theoretical foundations in scientific and technical publications and related factors.

URL : Identification and classification of evaluation indicators for scientific and technical publications and related factors

DOI : https://doi.org/10.47989/irpaper953

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Altmetrics of the Open Access Institutional Repositories: A Webometrics Approach

Author : Isidro F. Aguillo

Self-archiving in Institutional Repositories (IRs) is playing a central role in the success of the Open Access initiatives. Deposited documents are more visible and probably they get more downloads and citations, but making them freely available in a local repository is not enough.

Social tools, both public and academic targeting, networking or silo oriented, should be taken into account for reaching larger audiences and increase not only the scholarly but also the social impact.

This communication explores the presence of IRs contents in 28 social tools (Academia, Bibsonomy, CiteUlike, CrossRef, Datadryad, Facebook, Figshare, Google+, GitHub, Instagram, LinkedIn, Pinterest, Reddit, RenRen, ResearchGate, Scribd, SlideShare, Tumblr, Twitter, Vimeo, VKontakte, Weibo, Wikipedia All Languages, Wikipedia English, Wikia, Wikimedia, YouTube and Zenodo) using a webometric approach.

The link mentions of 2185 IRs in the cited tools were collected during July 2017 from Google selected data centers. The results showed that most of the IRs have no strong presence in the most specializes tools and even for the most popular services the figures are not high enough too.

Lack of strategies and bad practices are suggested as possible explanations for the low altmetrics figures.

URL : Altmetrics of the Open Access Institutional Repositories: A Webometrics Approach

Alternative location : https://openaccess.leidenuniv.nl/bitstream/handle/1887/65298/STI2018_paper_37.pdf

Catégories
EN

Search Engines and Alternative Data Sources in Webometric Research: An Exploratory Study

Web contents are interlinked at each other through hyperlinks. Inter-linking nature of web explores significant sources of information. In the context of exploring hyper-linking behaviour of the web and retrieving relevant information, search engines and web crawlers play a predominant role as data sources but search engines had mostly withdrawn their supports after December 2011. An attempt has taken to evaluate search engines (Google, AoL, Bing, Yahoo!) using some criteria and found that AoL has the highest coverage among these search engines.

The paper also identifies various alternative data sources to carry out webometric research. The finding of the study shows that majestic.com is a predominant and comprehensive data source among alternative data sources in webometric research.

URL : Search Engines and Alternative Data Sources in Webometric Research: An Exploratory Study

Alternative location : http://publications.drdo.gov.in/ojs/index.php/djlit/article/view/8883