Unbundling Open Access dimensions: a conceptual discussion to reduce terminology inconsistencies

Authors : Alberto Martín-Martín, Rodrigo Costas, Thed N. van Leeuwen, Emilio Delgado López-Cózar

The current ways in which documents are made freely accessible in the Web no longer adhere to the models established Budapest/Bethesda/Berlin (BBB) definitions of Open Access (OA). Since those definitions were established, OA-related terminology has expanded, trying to keep up with all the variants of OA publishing that are out there.

However, the inconsistent and arbitrary terminology that is being used to refer to these variants are complicating communication about OA-related issues. This study intends to initiate a discussion on this issue, by proposing a conceptual model of OA.

Our model features six different dimensions (authoritativeness, user rights, stability, immediacy, peer-review, and cost). Each dimension allows for a range of different options. We believe that by combining the options in these six dimensions, we can arrive at all the current variants of OA, while avoiding ambiguous and/or arbitrary terminology.

This model can be an useful tool for funders and policy makers who need to decide exactly which aspects of OA are necessary for each specific scenario.

URL : Unbundling Open Access dimensions: a conceptual discussion to reduce terminology inconsistencies

Alternative location : https://arxiv.org/abs/1806.05029

Google Scholar as a data source for research assessment

Authors : Emilio Delgado López-Cózar, Enrique Orduna-Malea, Alberto Martín-Martín

The launch of Google Scholar (GS) marked the beginning of a revolution in the scientific information market. This search engine, unlike traditional databases, automatically indexes information from the academic web. Its ease of use, together with its wide coverage and fast indexing speed, have made it the first tool most scientists currently turn to when they need to carry out a literature search.

Additionally, the fact that its search results were accompanied from the beginning by citation counts, as well as the later development of secondary products which leverage this citation data (such as Google Scholar Metrics and Google Scholar Citations), made many scientists wonder about its potential as a source of data for bibliometric analyses.

The goal of this chapter is to lay the foundations for the use of GS as a supplementary source (and in some disciplines, arguably the best alternative) for scientific evaluation.

First, we present a general overview of how GS works. Second, we present empirical evidences about its main characteristics (size, coverage, and growth rate). Third, we carry out a systematic analysis of the main limitations this search engine presents as a tool for the evaluation of scientific performance.

Lastly, we discuss the main differences between GS and other more traditional bibliographic databases in light of the correlations found between their citation data. We conclude that Google Scholar presents a broader view of the academic world because it has brought to light a great amount of sources that were not previously visible.

URL : https://arxiv.org/abs/1806.04435

The counting house: measuring those who count. Presence of Bibliometrics, Scientometrics, Informetrics, Webometrics and Altmetrics in the Google Scholar Citations, ResearcherID, ResearchGate, Mendeley & Twitter

Authors : Alberto Martin-Martin, Enrique Orduna-Malea, Juan M. Ayllon, Emilio Delgado Lopez-Cozar

Following in the footsteps of the model of scientific communication, which has recently gone through a metamorphosis (from the Gutenberg galaxy to the Web galaxy), a change in the model and methods of scientific evaluation is also taking place.

A set of new scientific tools are now providing a variety of indicators which measure all actions and interactions among scientists in the digital space, making new aspects of scientific communication emerge.

In this work we present a method for capturing the structure of an entire scientific community (the Bibliometrics, Scientometrics, Informetrics, Webometrics, and Altmetrics community) and the main agents that are part of it (scientists, documents, and sources) through the lens of Google Scholar Citations.

Additionally, we compare these author portraits to the ones offered by other profile or social platforms currently used by academics (ResearcherID, ResearchGate, Mendeley, and Twitter), in order to test their degree of use, completeness, reliability, and the validity of the information they provide.

A sample of 814 authors (researchers in Bibliometrics with a public profile created in Google Scholar Citations was subsequently searched in the other platforms, collecting the main indicators computed by each of them.

The data collection was carried out on September, 2015. The Spearman correlation was applied to these indicators (a total of 31) , and a Principal Component Analysis was carried out in order to reveal the relationships among metrics and platforms as well as the possible existence of metric cluster.

URL : https://arxiv.org/abs/1602.02412