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Towards FAIR protocols and workflows: the OpenPREDICT use case

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Authors : Remzi Celebi, Joao Rebelo Moreira, Ahmed A. Hassan, Sandeep Ayyar, Lars Ridder, Tobias Kuhn, Michel Dumontier

It is essential for the advancement of science that researchers share, reuse and reproduce each other’s workflows and protocols. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of research data, and emphasize the importance of making digital objects findable and reusable by others.

The question of how to apply these principles not just to data but also to the workflows and protocols that consume and produce them is still under debate and poses a number of challenges. In this paper we describe a two-fold approach of simultaneously applying the FAIR principles to scientific workflows as well as the involved data.

We apply and evaluate our approach on the case of the PREDICT workflow, a highly cited drug repurposing workflow. This includes FAIRification of the involved datasets, as well as applying semantic technologies to represent and store data about the detailed versions of the general protocol, of the concrete workflow instructions, and of their execution traces.

We propose a semantic model to address these specific requirements and was evaluated by answering competency questions. This semantic model consists of classes and relations from a number of existing ontologies, including Workflow4ever, PROV, EDAM, and BPMN.

This allowed us then to formulate and answer new kinds of competency questions. Our evaluation shows the high degree to which our FAIRified OpenPREDICT workflow now adheres to the FAIR principles and the practicality and usefulness of being able to answer our new competency questions.

URL : Towards FAIR protocols and workflows: the OpenPREDICT use case

DOI : https://doi.org/10.7717/peerj-cs.281

What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption

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Authors : Anneke Zuiderwijk, Rhythima Shinde, Wei Jeng

Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers’ drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking.

This study’s purpose is to systematically review the literature on individual researchers’ drivers and inhibitors for sharing and using open research data. This study systematically analyzed 32 open data studies (published between 2004 and 2019 inclusively) and elicited drivers plus inhibitors for both open research data sharing and use in eleven categories total that are: ‘the researcher’s background’, ‘requirements and formal obligations’, ‘personal drivers and intrinsic motivations’, ‘facilitating conditions’, ‘trust’, ‘expected performance’, ‘social influence and affiliation’, ‘effort’, ‘the researcher’s experience and skills’, ‘legislation and regulation’, and ‘data characteristics.’

This study extensively discusses these categories, along with argues how such categories and factors are connected using a thematic analysis. Also, this study discusses several opportunities for altogether applying, extending, using, and testing theories in open research data studies.

With such discussions, an overview of identified categories and factors can be further applied to examine both researchers’ drivers and inhibitors in different research disciplines, such as those with low rates of data sharing and use versus disciplines with high rates of data sharing plus use. What’s more, this study serves as a first vital step towards developing effective incentives for both open data sharing and use behavior.

URL : What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption

DOI : https://doi.org/10.1371/journal.pone.0239283

Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: a multidisciplinary comparison of coverage via citations

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

New sources of citation data have recently become available, such as Microsoft Academic, Dimensions, and the OpenCitations Index of CrossRef open DOI-to-DOI citations (COCI). Although these have been compared to the Web of Science Core Collection (WoS), Scopus, or Google Scholar, there is no systematic evidence of their differences across subject categories.

In response, this paper investigates 3,073,351 citations found by these six data sources to 2,515 English-language highly-cited documents published in 2006 from 252 subject categories, expanding and updating the largest previous study. Google Scholar found 88% of all citations, many of which were not found by the other sources, and nearly all citations found by the remaining sources (89–94%).

A similar pattern held within most subject categories. Microsoft Academic is the second largest overall (60% of all citations), including 82% of Scopus citations and 86% of WoS citations. In most categories, Microsoft Academic found more citations than Scopus and WoS (182 and 223 subject categories, respectively), but had coverage gaps in some areas, such as Physics and some Humanities categories. After Scopus, Dimensions is fourth largest (54% of all citations), including 84% of Scopus citations and 88% of WoS citations.

It found more citations than Scopus in 36 categories, more than WoS in 185, and displays some coverage gaps, especially in the Humanities. Following WoS, COCI is the smallest, with 28% of all citations. Google Scholar is still the most comprehensive source. In many subject categories Microsoft Academic and Dimensions are good alternatives to Scopus and WoS in terms of coverage.

DOI : https://doi.org/10.1007/s11192-020-03690-4

Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation

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Authors : Jedidiah Carlson, Kelley Harris

Engagement with scientific manuscripts is frequently facilitated by Twitter and other social media platforms. As such, the demographics of a paper’s social media audience provide a wealth of information about how scholarly research is transmitted, consumed, and interpreted by online communities.

By paying attention to public perceptions of their publications, scientists can learn whether their research is stimulating positive scholarly and public thought. They can also become aware of potentially negative patterns of interest from groups that misinterpret their work in harmful ways, either willfully or unintentionally, and devise strategies for altering their messaging to mitigate these impacts.

In this study, we collected 331,696 Twitter posts referencing 1,800 highly tweeted bioRxiv preprints and leveraged topic modeling to infer the characteristics of various communities engaging with each preprint on Twitter.

We agnostically learned the characteristics of these audience sectors from keywords each user’s followers provide in their Twitter biographies. We estimate that 96% of the preprints analyzed are dominated by academic audiences on Twitter, suggesting that social media attention does not always correspond to greater public exposure.

We further demonstrate how our audience segmentation method can quantify the level of interest from nonspecialist audience sectors such as mental health advocates, dog lovers, video game developers, vegans, bitcoin investors, conspiracy theorists, journalists, religious groups, and political constituencies.

Surprisingly, we also found that 10% of the preprints analyzed have sizable (>5%) audience sectors that are associated with right-wing white nationalist communities. Although none of these preprints appear to intentionally espouse any right-wing extremist messages, cases exist in which extremist appropriation comprises more than 50% of the tweets referencing a given preprint.

These results present unique opportunities for improving and contextualizing the public discourse surrounding scientific research.

URL : Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation

DOI : https://doi.org/10.1371/journal.pbio.3000860

What senior academics can do to support reproducible and open research: a short, three-step guide

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Authors : Olivia Kowalczyk, Alexandra Lautarescu, Elisabet Blok, Lorenza Dall’Aglio, Samuel Westwood

Increasingly, policies are being introduced to reward and recognise open research practices, while the adoption of such practices into research routines is being facilitated by many grassroots initiatives.

However, despite this widespread endorsement and support, open research is yet to be widely adopted, with early career researchers being the notable exception. For open research to become the norm, initiatives should engage academics from all career stages, particularly senior academics (namely senior lecturers, readers, professors) given their routine involvement in determining the quality of research.

Senior academics, however, face unique challenges in implementing policy change and supporting grassroots initiatives. Given that – like all researchers – senior academics are in part motivated by self-interest, this paper lays out three feasible steps that senior academics can take to improve the quality and productivity of their research, that also serve to engender open research.

These steps include a) change hiring criteria, b) change how scholarly outputs are credited, and c) change to funding and publishing with open research. The guidance we provide is accompanied by live, crowd-sourced material for further reading.

URL : What senior academics can do to support reproducible and open research: a short, three-step guide

Original location : https://psyarxiv.com/jyfr7

Research data management policy and practice in Chinese university libraries

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Authors : Yingshen Huang, Andrew M. Cox, Laura Sbaffi

On April 2, 2018, the State Council of China formally released a national Research Data Management (RDM) policy “Measures for Managing Scientific Data”. In this context and given that university libraries have played an important role in supporting RDM at an institutional level in North America, Europe, and Australasia, the aim of this article is to explore the current status of RDM in Chinese universities, in particular how university libraries have been involved in taking the agenda forward.

This article uses a mixed‐methods data collection approach and draws on a website analysis of university policies and services; a questionnaire for university librarians; and semi‐structured interviews. Findings indicate that Research Data Service at a local level in Chinese Universities are in their infancy.

There is more evidence of activity in developing data repositories than support services. There is little development of local policy. Among the explanations of this may be the existence of a national‐level infrastructure for some subject disciplines, the lack of professionalization of librarianship, and the relatively weak resonance of openness as an idea in the Chinese context.

URL : Research data management policy and practice in Chinese university libraries

DOI : https://doi.org/10.1002/asi.24413

Directory of Open Access Journals in Keywords. Distribution and Themes of Articles

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Authors : Rosangela Schwarz Rodrigues, Breno Kricheldorf Hermes de Araújo, Laura Lavinia Sabino dos Santos, Ana Lidia Campos Brizola

Researchers depend on consultation with previous work in their field, most of which is published in scientific journals. The open access movement has affected journals and articles, providing new alternatives for accessing scientific content, and the Directory of Open Access Journals (DOAJ) is the most specialized and multidisciplinary database of open access journals.

The main goal of this study is to analyze publications that include “DOAJ” in their keywords, to determine how researchers in the areas of Library and Information Science and Social Science are studying it.

The specific objectives are: a) to describe the characteristics of journals indexed in the Web of Science, DOAJ, or SCOPUS that have published articles with “DOAJ” as a keyword; b) to identify the institutional affiliations of the authors of those articles; and c) to classify the articles according to subject area.

We identified 39 articles from 29 journals. The countries with the largest numbers of journals are the United States and the United Kingdom (six journals each). Most of the journals were open access, of which universities were the biggest publishers.

The countries with the largest numbers of authors were India (12), and Italy and Russia (11 each), and the journal that published the most articles was the University of Nebraska’s Library Philosophy and Practice (four articles).

Most articles analyze the quality (65.5%), followed by the growth (25.6%), of the Open Access Movement. An analysis of the subject areas covered revealed significant gaps, as the economic, legal and technological aspects of DOAJ were not represented.

URL : Directory of Open Access Journals in Keywords. Distribution and Themes of Articles

DOI: http://dx.doi.org/10.4403/jlis.it-12630